The Embassy of Good Science - User contributions [en]

Instruction:4bc3edc0-d493-4f35-a742-e4cee5569562

2026-04-20T15:58:18Z

0009-0002-1788-6517:

{{Instruction
|Title=New Tools and Services for Reproducibility
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=TIER2 aims to better understand the causes, consequences and possible solutions of perceived poor levels of reproductivity of research across research contexts. With a focus on social, life, and computer sciences, as well as research publishers and funders, the project aims to increase awareness, build capacity, and propose innovative solutions sensitive to varied research cultures. Central to its approach are eight Pilot activities designed to develop, implement, and evaluate new reproducibility-related tools and practices.
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|Important For=Researcher
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|Instruction Step Title=Pilot 1 - Decision Aid
|Instruction Step Text=<span lang="EN-US">TIER2's Decision Aid provides clarity on the meaning, relevance, and feasibility of ‘reproducibility’ for researchers to aid them in identifying what type of reproducibility is relevant for their research and indicate what they must consider regarding how feasible such ‘reproducibility’ would be for them.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 2 - Reproducibility Management Plan (RMP)
|Instruction Step Text=<span lang="EN-US">The [https://osf.io/pn27g Reproducibility Management Plan (RMP) Pilot] aims to create a prototype of key thematic subjects and questions that will serve as the starting point to support reproducibility at the planning stage of research. Work involves defining what an RMP is, integrating it into the ARGOS service, and testing its effectiveness with feedback from the community. The pilot addresses researchers, beneficiaries and funders for its adoption.</span><div>
Please find the integrated ARGOS tool here: <u>https://argos.openaire.eu/portal/</u><u>.</u>

Downloadable version of the RMP prototype template: [https://eur04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fosf.io%2Fa7z9x%2F&data=05%7C02%7Cb.leitner%40amsterdamumc.nl%7C71711775f8024a483ef208de9ef07be0%7C68dfab1a11bb4cc6beb528d756984fb6%7C0%7C0%7C639122952853827480%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=l4dQwkweKHzOmsoxqcI%2Bha6Uw0mttgXrLiBEC7lCM9o%3D&reserved=0 https://osf.io/a7z9x/].

<u><span lang="EN-US">Tutorials on OpenPlato:</span></u>

#<u>'''<span lang="EN-US">ARGOS Service for Admins</span>'''<span lang="EN-US">: https://openplato.eu/course/view.php?id=150</span></u>
#<u>'''<span lang="EN-US">ARGOS Info Pack</span>'''<span lang="EN-US">: https://openplato.eu/course/view.php?id=547</span></u>
#<u>'''<span lang="EN-US">ARGOS Service for Users</span>'''<span lang="EN-US">: https://openplato.eu/course/view.php?id=122</span></u>
</div><div>
<u><span lang="EN-US">Reports on co-creation activities: <nowiki>https://osf.io/fp7zt/</nowiki></span></u>
</div>
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|Instruction Step Title=Pilot 3 - Reproducible Workflows
|Instruction Step Text=<span lang="EN-US">In this pilot, [https://schema-lab.hypatia-comp.athenarc.gr/ SCHEMA] was developed as an open-source framework, comprising SCHEMA api for programmatic execution and SCHEMA lab for a user-friendly web interface to support reproducible computational research through containerized execution, metadata capturing and experiment management. It provides a scalable environment that enables researchers to design and run reproducible computational workflows and experiments.</span>
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{{Instruction Step Trainee
|Instruction Step Title=Pilot 4 - The Reproducibility Checklist
|Instruction Step Text=<span lang="EN-US"><span lang="EN-GB">The <span lang="DE">[https://eur04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FGESIS-Methods-Hub%2Fguidelines-for-methods%2Fblob%2Fmain%2FREADME-template.md&data=05%7C02%7Cb.leitner%40amsterdamumc.nl%7C98306bdc1d14436a474308de062e488a%7C68dfab1a11bb4cc6beb528d756984fb6%7C0%7C0%7C638954993173754302%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=8wKJxWZb4qfVKLG%2F%2Bgn4HWuQCxrkIvrUyENg%2FEEwiWM%3D&reserved=0 Reproducibility Checklist for Computational Social Science Research]</span> provides a simple, structured framework to enhance the reproducibility of computational methods shared on [https://eur04.safelinks.protection.outlook.com/?url=http%3A%2F%2Fmethodshub.gesis.org%2F&data=05%7C02%7Cb.leitner%40amsterdamumc.nl%7C98306bdc1d14436a474308de062e488a%7C68dfab1a11bb4cc6beb528d756984fb6%7C0%7C0%7C638954993173788095%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=fZvqBgWjUcBuH%2FNJKGAl8WYPcNRsRQujUc8k%2FbPcG3Q%3D&reserved=0 Methods Hub]. Designed for minimal effort and maximum usability, the checklist helps researchers document and share their data and code in a consistent, verifiable way that fosters trust and collaboration within the social science community. This pilot contributes to more efficient, transparent, and reproducible computational social science by integrating practical usability with clear documentation standards.</span></span>

<span lang="EN-US">The [https://github.com/GESIS-Methods-Hub/guidelines-for-methods/blob/main/README-template.md <u>checklist tempelate</u>] is publicly available through GitHub [https://github.com/GESIS-Methods-Hub/guidelines-for-methods <u>project repositoriy</u>] and is accompanied by [https://github.com/GESIS-Methods-Hub/guidelines-for-methods/blob/main/guidelines.md <u>user guidance</u>] for researchers who want to submit a method. These resources explain how to apply the checklist in practice, both independently and in connection with [https://methodshub.gesis.org/ <u>Methods Hub</u>].</span>
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{{Instruction Step Trainee
|Instruction Step Title=Pilot 5 - The Reproducibility Promotion Plan for Funders (RPP)
|Instruction Step Text=<span lang="EN-US">The Reproducibility Promotion Plan for Funders (RPP) has developed a policy template with recommendations for funders to foster reproducible practices both in the research they fund across three key areas of funding work: evaluation and monitoring, policy and definitions, and incentives. The RPP provides actionable recommendations and best practice examples that funders and funding institutions can adapt to meet their specific needs.</span>

All drafts of the RPP can be found on [https://osf.io/3fpbj/ OSF].

[[File:RPP4F One Pager.jpg|center|thumb]]
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{{Instruction Step Trainee
|Instruction Step Title=Pilot 6 - The Reproducibility Monitoring Dashboard
|Instruction Step Text=<span lang="EN-US">The Reproducibility Monitoring Dashboard hosts tools that enable funding agencies to track and monitor the reusability of research artifacts across various projects, programs, topics, and disciplines. This auto-generated dashboard assesses the impacts of policies related to data and code sharing.</span> <div>
# <u><span lang="EN-US">OSF link for development materials: https://osf.io/wnvtx/</span></u>
# <u><span lang="EN-US">Dashboard prototype for EU-funded Machine Learning projects: https://app.powerbi.com/view?r=eyJrIjoiZTc0MmU1ZTktNzAyMy00ZTk1LWFkZmYtNDVmYjU2YzdhMzZhIiwidCI6IjZhZTA3NzAyLWM1ZjctNGYzOC05Yjg3LWFjYWQ2MmE3NWQ5MyIsImMiOjl9</span></u>
</div>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 7 - Editorial Workflows to Increase Data Sharing
|Instruction Step Text=<span lang="EN-GB">A key aspect of (computational) reproducibility is availability of data. However, sharing of research data is still not the norm across disciplines. Developed co-creatively with stakeholders from major publishers, the workflow and email template provide a low-effort approach for publishers to nudge researchers towards sharing their data for journals operating under a “share upon request” policy. Documentation on the workflow and email template can be found in [https://doi.org/10.17605/OSF.IO/S7GJV TIER2 D5.2].</span>
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{{Instruction Step Trainee
|Instruction Step Title=Pilot 8- An Editorial Reference Handbook for Reproducibility and FAIRness
|Instruction Step Text=<div>
<span lang="EN-US">The [https://publishers.fairassist.org/ <u>Editorial Reference Handbook</u>] informs and assists journals to operationalise a set of checks necessary to make the data underlying published research findings more findable, accessible, interoperable and reusable (FAIR) to underpin reproducibility. The Handbook targets in-house staff managing the manuscripts primarily, but it will also benefit reviewers, authors and even those providing services to publishers by making the fundamental checks and requirements transparent and understandable.</span>
</div><div>
<span lang="EN-US">The Handbook includes three interlinked components: a checklist of 12 elements, a flowchart that outlines the ideal internal manuscript submission workflow (who should perform the checks and when), and a guidance to help users to implement the checks effectively, with definitions and tips.</span>
</div><div>
<span lang="EN-US">The Handbook fills a gap, because no common guidance existed on the practical implementation of these checks across a complex publishing workflow and the variety of individuals and teams involved. This pilot saw the participation of more than 30 individuals, from more than 20 journals of major publishers: CUP, Cell Press, EMBO Press, Taylor & Francis, GigaScience Press, OUP, PLOS, Springer Nature.</span>
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Resource:6a5c8717-8440-4bc2-8afa-7ad68b7da3f0

2026-03-06T11:24:41Z

0009-0002-1788-6517:

{{Resource
|Resource Type=Education
|Title=M-Power Workshop Facilitator Instructions
|Has Related Initiative=Initiative:6f8cdcc6-cf56-4dde-bd5d-3b14db1c2a6f
|Is About=A interactive workshop aimed at <span lang="EN-US"> exploring what empowerment is for early career researchers (ECRs) and PhDs, in the context of daily life in academia. And to raise awareness of the role PhDs hold in influencing research culture.</span>

Find in depth instructions here: [https://osf.io/9t2mg/files/x5b9m M-Power Facilitator Instructions.pdf]

Print out for guiding questions here: [https://osf.io/rhw94 Guiding questions]

The slides for the workshop here: [https://osf.io/z97sb M-Power Workshop Slides]
|Important For=Trainer
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|Has Link=https://osf.io/9t2mg/files/x5b9m
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Resource:6a5c8717-8440-4bc2-8afa-7ad68b7da3f0

2026-03-06T10:47:49Z

0009-0002-1788-6517: Created page with "{{Resource |Resource Type=Education |Title=M-Power Workshop Facilitator Instructions |Has Related Initiative=Initiative:6f8cdcc6-cf56-4dde-bd5d-3b14db1c2a6f |Is About=A intera..."

Instruction:3fa94a70-3004-4923-b87c-94757393935a

2026-03-06T10:42:27Z

0009-0002-1788-6517:

{{Instruction
|Title=M-Power Workshop
|Has Related Initiative=Initiative:6f8cdcc6-cf56-4dde-bd5d-3b14db1c2a6f
|Instruction Goal=<span lang="EN-US">Explore what empowerment is for early career researchers (ECRs) and PhDs, in the context of daily life in academia. And to raise awareness of the role PhDs hold in influencing research culture. </span>
|Has Duration=2
|Important For=Doctoral Student; Early Career Researcher; Research Supervisor / Mentor; Researcher
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|Is About=<span lang="EN-US">Explore what empowerment is for early career researchers (ECRs) and PhDs, in the context of daily life in academia. And to raise awareness of the role PhDs hold in influencing research culture. </span>
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{{Instruction Step Trainee
|Instruction Step Title=Introduction (15 minutes)
|Instruction Step Text= Define empowerment, we use the broadest definition of empowerment to provide an overview and help spark ideas for the participants what it may mean to them in academia. <span lang="EN-US">Within the workshop we use the definition from the Cambridge Dictionary: “The process of gaining freedom and power to do what you want or to control what happens to you.”</span>

<span lang="EN-US">Discuss what can affect empowerment in academia, discuss that this is not always the case but it can occur:</span>

<span lang="EN-US"> i. Hierarchical structures</span>

Academia, particularly in traditional institutions, often operates with a rigid hierarchical structure. The power dynamics can limit the autonomy of lower-ranking faculty (e.g., adjunct professors or junior faculty) and staff. Senior leaders, such as department heads, deans, and administrators, often make the major decisions regarding curriculum, policies, or resources, which can lead to a sense of disempowerment among those lower in the hierarchy. Faculty might feel their ideas are overlooked, or that they have little influence over institutional priorities.

<span lang="EN-US"> ii. Lack of transparency</span>

Transparency in decision-making, particularly regarding policies, budget allocations, promotions, and institutional priorities, is vital for empowerment. When decisions are made behind closed doors, or when information is not shared equitably across the institution, it can create an environment where individuals feel excluded and powerless. A lack of clarity about how decisions are made or what criteria are used for promotions can make people feel that their efforts are futile or that they have no control over their professional trajectory.

<span lang="EN-US"> iii. Lack of ability to affect meaningful change in your working environment</span>

<span lang="EN-US">Empowerment in academia is often linked to the ability to influence and shape one's environment. This could include having a voice in curriculum development, research priorities, institutional policy, or even the physical and social environment of the workplace. When individuals feel that they have no real impact on decisions affecting their work or workplace culture, they may feel disillusioned or disengaged.</span>

<span lang="EN-US">Discuss that these variables are usually a result of research culture within institutions, departments, or research teams. Continue by defining what research culture is. Research culture encompasses the behaviors, values, expectations, attitudes and norms of research communities. It influences researches’ career paths and determines the way that research is conducted and communicated (Royal Society, 2025). When discussing the definition, mention that this is a broad definition. Research culture is often more complex, and is composed and affected by many different variables. You may touch on the existing negative associations researchers have with research culture, that it can lead to exploitation, discrimination, and even bullying when research culture is abused. You should also discuss how negative research culture can affect social and psychological safety, responsible conduct of research, mental health, and research misbehaviors/quality of work. It is important to highlight that these variables do not work in isolation but they are a result of the integration and mixture between individual, systematic, and cultural factors. Discussing that individuals are affected by the system, causing behavioral and attitudinal issues, which in turn may fuel bad cultural norms. It is important to highlight this explicitly, so that participants do not feel isolated in their experiences or that they understand that differences in outcomes are not just dependent on them, and that they do not bare all responsibilities.</span>

Continue by telling participants they will as a group have to choose out of the four scenarios two to work through in the workshop. Describe the four scenarios:

* <span lang="EN-US">Collaborative Working</span>
* Taking Initative
* Supervision
* Conflict of Interest
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{{Instruction Step Trainee
|Instruction Step Title=Scenario 1: Collaborative Working
|Instruction Step Text=<span lang="EN-US">A PhD candidate is new to a laboratory, and they face some conflict with a peer when it comes to booking the laboratory space and equipment. This scenario is focused on how to work together collaboratively and how to handle misunderstandings.</span>
|Instruction Step Interactive Content=Resource:H5P-555
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{{Instruction Step Trainee
|Instruction Step Title=Scenario 2: Reproducibility (Taking Initative)
|Instruction Step Text=<span lang="EN-US">A PhD candidate, would like to bring new practices (specifically focused on reproducibility) to their research team but they face a lot pushback from their colleagues especially more senior ones. This scenario is focused on how to approach colleagues who are resilient to change.</span>
|Instruction Step Interactive Content=Resource:H5P-556
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{{Instruction Step Trainee
|Instruction Step Title=Scenario 3: Supervision
|Instruction Step Text=<span lang="EN-US">A PhD candidate, meets with their esteemed but chaotic promotor every 6 weeks, where their unpreparedness and inconsistent advice leave them feeling unsupported. This scenario is focused on handling conflicts and communication issues with a supervisor.</span>
|Instruction Step Interactive Content=Resource:H5P-557
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{{Instruction Step Trainee
|Instruction Step Title=Scenario 4: Conflict of Interest
|Instruction Step Text=<span lang="EN-US"> A PhD candidate realizes their supervisor may have different interests in the outcome of their scientific output due to their investments and connections. This scenario is focused on how to open up and discuss possible conflicts of interests.</span>
|Instruction Step Interactive Content=Resource:H5P-558
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{{Instruction Step Trainee
|Instruction Step Title=First scenario (45 minutes)
|Instruction Step Text=<span lang="EN-US">1. Read the introductory text of the first scenario, ask if everything is clear.</span>

<span lang="EN-US">2. Play the introductory video of the scenario which sets up the dilemma. The next screen will show the four possible ways to act in this situation. Read these aloud for the participants.</span>

<span lang="EN-US">3. After the introductory video, ask participants to individually write down on a piece of paper (this should take approximately 5 minutes):</span>

<span lang="EN-US">a.    What they observe in this scenario</span>

<span lang="EN-US">b. What they recognize in this situation</span>

<span lang="EN-US">c.    Which action choice would they pick (A, B, C, or D) and why</span>

<span lang="EN-US">4. Allocate each corner of the room to one of the action choices (e.g. corner 1 = A), ask participants to stand up and to stand in the corner of the room which corresponds to their choice. Participants may choose to be in between action choices (e.g. between A & D), just ask them where they stand.</span>

<span lang="EN-US">5. Go around each action choice and ask participants why they picked that choice. Do this until every participant has shared their views, or participants feel others have already shared their views. Also ask them reflect on what they saw in the scenario if it is a familiar scenario.</span>

<span lang="EN-US">6. Briefly ask if anyone would change their initial answer after this discussion, if yes ask what would they change it to and why.</span>

<span lang="EN-US">7. Ask participants to sit back down, and watch the outcomes videos of each action choice. Start with the video with the most responses.</span>

<span lang="EN-US">8. After watching all the videos and seeing the different outcomes discuss as a group:</span>

* <span lang="EN-US">a.    If they were able to choose again, would they choose differently? If yes, what and why?</span>
* <span lang="EN-US">b. Which action did they find most empowering?</span>
* <span lang="EN-US">c.    What did they learn from this scenario?</span>

<span lang="EN-US">9. Ask participants if there is anything they would like to add. Help summarize the discussion and the outcomes which were discussed. Draw attention to that there are many more different ways to act in these situations, and that it is important to evaluate and reflect on what they need in the situation.</span>
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{{Instruction Step Trainee
|Instruction Step Title=Second Scenario (45 minutes)
|Instruction Step Text=<span lang="EN-US">1. Read the introductory text of the second scenario, ask if everything is clear.</span>

<span lang="EN-US">2. Play the introductory video of the scenario which sets up the dilemma. The next screen will show the four possible ways to act in this situation. Read these aloud for the participants.</span>

<span lang="EN-US">3. After the introductory video, ask participants to individually write down on a piece of paper (this should take approximately 5 minutes):</span>

<span lang="EN-US">a.    What they observe in this scenario</span>

<span lang="EN-US">b. What they recognize in this situation</span>

<span lang="EN-US">c.    Which action choice would they pick (A, B, C, or D) and why</span>

<span lang="EN-US">4. Allocate each corner of the room to one of the action choices (e.g. corner 1 = A), ask participants to stand up and to stand in the corner of the room which corresponds to their choice. Participants may choose to be in between action choices (e.g. between A & D), just ask them where they stand.</span>

<span lang="EN-US">5. Go around each action choice and ask participants why they picked that choice. Do this until every participant has shared their views, or participants feel others have already shared their views. Also ask them reflect on what they saw in the scenario if it is a familiar scenario.</span>

<span lang="EN-US">6. Briefly ask if anyone would change their initial answer after this discussion, if yes ask what would they change it to and why.</span>

<span lang="EN-US">7. Ask participants to sit back down, and watch the outcomes videos of each action choice. Start with the video with the most responses.</span>

<span lang="EN-US">8. After watching all the videos and seeing the different outcomes discuss as a group:</span>

* a.    If they were able to choose again, would they choose differently? If yes, what and why?
* b. Which action did they find most empowering?
* c.    What did they learn from this scenario?

<span lang="EN-US">9. Ask participants if there is anything they would like to add. Help summarize the discussion and the outcomes which were discussed. Draw attention to that there are many more different ways to act in these situations, and that it is important to evaluate and reflect on what they need in the situation.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Group reflections and conclusions (20 minutes)
|Instruction Step Text=<span lang="EN-US">1. Ask each participant to in 1-2 minutes think of one or two takeaways from the workshop & discussions.</span>

<span lang="EN-US">2. Then ask participants to reflect on empowerment, what it means for them and what they need to feel empowered in their role as a PhD & researcher. Probe them to think about how they can empower themselves in their daily work.</span>

<span lang="EN-US">3. Continue the discussion by drawing to the importance of empowerment and how it connects to academia. It is important to be able to recognize/hear bad or unsafe situations and to speak up in these scenarios. Empowerment in academia is crucial for fostering a positive and productive environment. It enhances the quality of work by allowing individuals to take ownership of their projects, boosting motivation and creativity. With greater control over their academic journey, students and researchers are more engaged and persistent. Empowerment also promotes well-being by helping individuals manage stress and set healthy boundaries, while ensuring they feel safe to speak up about unsafe or unethical situations. It fosters inclusive, collaborative work environments where everyone’s voice is valued, leading to more innovative and effective outcomes. Ultimately, empowerment creates a culture where individuals are motivated, supported, and capable of contributing meaningfully to their academic communities.</span>

<span lang="EN-US">4. Ask participants if there are any questions, or any points they would like to discuss.</span>

<span lang="EN-US">5. Discuss the importance of communication for empowerment. Discuss this from the perspective of communicating with peers as an important resource for empowerment, it can help reflect on situations from a different perspective and provide support. But it is also important to discuss communication with others in dilemma situations, it is important to be clear and transparent and if they think something wrong they should speak to someone (e.g. directly to the person, or confidential counselors). Increasing awareness and learning to recognize unsafe or dilemmas can help other and themselves in handling situations in the future. Conclude that dilemmas will always exist, but it is up to individuals to change the way they approach them and these changes continue through awareness, communication, and recognition.</span>

<span lang="EN-US">6. Finish the session by alleviating the responsibilities from the PhDs, tell them it is not only their responsibility to ‘fix the system’. They have a large network of support networks if they feel they need help. Share the contact information & responsibilities of graduate schools and confidential counselors. End the workshop by highlighting that each dilemma and each individual may require a different approach and their empowerment is what the individual needs in that situation and therefore can be different for everyone. It is important to evaluate what the individual wants to achieve in the situation and act accordingly.</span>
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{{Instruction Step Trainer
|Instruction Step Title=Scenario 1: Collaborative Working
|Instruction Step Text=<span lang="EN-US">A PhD candidate is new to a laboratory, and they face some conflict with a peer when it comes to booking the laboratory space and equipment. This scenario is focused on how to work together collaboratively and how to handle misunderstandings.</span>
|Instruction Step Interactive Content=Resource:H5P-555
}}
{{Instruction Step Trainer
|Instruction Step Title=Scenario 2: Reproducibility (Taking Initiative)
|Instruction Step Text=<span lang="EN-US">A PhD candidate, would like to bring new practices (specifically focused on reproducibility) to their research team but they face a lot pushback from their colleagues especially more senior ones. This scenario is focused on how to approach colleagues who are resilient to change.</span>
|Instruction Step Interactive Content=Resource:H5P-556
}}
{{Instruction Step Trainer
|Instruction Step Title=Scenario 3: Supervision
|Instruction Step Text=<span lang="EN-US">A PhD candidate, meets with their esteemed but chaotic promotor every 6 weeks, where their unpreparedness and inconsistent advice leave them feeling unsupported. This scenario is focused on handling conflicts and communication issues with a supervisor.</span>
|Instruction Step Interactive Content=Resource:H5P-557
}}
{{Instruction Step Trainer
|Instruction Step Title=Scenario 4: Conflict of Interest
|Instruction Step Text=<span lang="EN-US">A PhD candidate realizes their supervisor may have different interests in the outcome of their scientific output due to their investments and connections. This scenario is focused on how to open up and discuss possible conflicts of interests.</span>
|Instruction Step Interactive Content=Resource:H5P-558
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|Related To Theme=Theme:B2331451-5a6a-4aa2-a3d5-c68d2c96c8e1
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{{Tags
|Involves=Early Career Researchers; PhD; PhD Supervisors
}}

Instruction:3fa94a70-3004-4923-b87c-94757393935a

2026-03-06T09:27:24Z

0009-0002-1788-6517: Created page with "{{Instruction |Title=M-Power Workshop |Has Related Initiative=Initiative:6f8cdcc6-cf56-4dde-bd5d-3b14db1c2a6f |Instruction Goal=<span lang="EN-US">Explore what empowerment is..."

Instruction:7c159fc9-db27-4623-9432-9c37b8889f89

2025-12-12T15:04:28Z

0009-0002-1788-6517:

{{Instruction
|Title=Communities and collaborators
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=On this page we present the TIER2 Reproducibility Network Award, the stakeholder community building activities and efforts of TIER2, our consortia partners (iRise and OSIRIS), and finally the UKRN Primers initative.
|Has Duration=1
|Important For=All stakeholders in research
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|Instruction Step Title=Reproducibility Network Award
|Instruction Step Text=<div>
==='''<span lang="EN-GB">What is a Reproducibility Network?</span>''' ===
</div><div><div>
<span lang="EN-GB">A national Reproducibility Network <u>(RN)</u> is a countrywide peer-led consortium that aims to improve research practices by promoting, supporting, and investigating factors contributing to robust research including, but not limited to, reproducibility, replicability, and Open Science. Activities may include promoting training activities, disseminating best practices, supporting research on reproducible research practices, and advocacy for reproducible and open research. </span>
</div><div>
<span lang="EN-GB">An RN typically serves as a hub to connect researchers to exchange ideas and good practices, promoting collaboration among researchers from a range of scientific disciplines. These networks provide infrastructure, facilitate opportunities for researchers and initiatives to support and amplify each other’s efforts, and foster community building as well as shared problem solving. </span>
</div><div>
<span lang="EN-GB">RNs can serve as connectors to other stakeholder groups such as universities, funders, or academic publishers.</span>
</div></div>

===Benefits for setting up an Reproducibility Network?===

<span lang="EN-GB">By providing seed funding for the establishment of a new RN, you actively contribute to the strengthening of reproducibility and Open Science in your local ecosystem. The widespread presence of RNs is crucial, as they function as points of contact for scientific communities who, across e.g., disciplinary, demographic, and geographic contexts, face different challenges and barriers. RNs can provide local and tailored support and keep in mind the different stages of readiness of their local communities for implementing reproducible research practices.</span>

==="Lessons learned" from the TIER2 award===
1. '''<span lang="EN-GB">Build strong community links.</span>''' <span lang="EN-GB">Involve already existing and successful RNs in the establishment of new RNs. This ensures that new RNs receive valuable guidance, input and support early in the establishment process.</span>

2. '''<span lang="EN-GB">Expand connections and broaden the reach.</span>''' <span lang="EN-GB">Reach out to researchers and other relevant stakeholders, such as universities, as this is important for local support and the sustainability of the RN. However, identifying and connecting with researchers in Horizon Europe Widening Participation countries (WIDERA countries) who are active in reproducible research and Open Science practices can be challenging.</span>

3. '''<span lang="EN-GB">Facilitate international support.</span>''' <span lang="EN-GB">Several RNs across the globe exist and more are being established. Build strong international connections amongst them to facilitate the sharing of resources and best practices, this will help to coordinate and amplify efforts.</span>

4. '''<span lang="EN-GB">Focus on the local ecosystem.</span>''' <span lang="EN-GB">RNs are national networks that promote transparent and trustworthy practices in their local research ecosystems. Recognize local needs, geopolitical conditions as well as barriers and available resources.</span>

===How has TIER2 supported the awarded networks?===

1. TIER2 members and award organizers have facilitated connections between awardees and existing international Reproducibility and Open Science networks. via email contacts as well as through virtual and in-person meetings.

2. <span lang="EN-GB">TIER2 award organizers, have added awardees, with their consent, to various mailing lists and newsletters from different international RNs.</span>

3.<span lang="EN-GB">Further, TIER2 award organizers have invited awardees to attend and speak at several Open Science and reproducibility events to meet (steering group) members from other RNs and (inter-)national initiatives.</span>

<span lang="EN-GB">4. TIER2 project members as well as award organizers have provided the awardees with resources and information on relevant topics, including different RN structures, website layout and structure, as well as language.</span>

===Awardess of the TIER2 Reproducibility Network Award===

TIER2 is proud to announce the two awarded consortia based in Ukraine and Georgia who will receive the monetary awards from the Reproducibility Network open call this summer. Multiple scientific consortia from Horizon Europe “[https://www.era-learn.eu/support-for-partnerships/additional-activities/openness-inclusivness-transparency/widening-and-inclusiveness Widening Participation]” countries submitted applications describing their plans and motivations for establishing a Reproducibility Network in their home country which TIER2 would support with a €5000 prize.

[[File:Ukraine and Georgia RN.png|center|thumb]]

====Ukrainian Consortium====
The Ukrainian consortium, from the Institute for Open Science and Innovation ([https://www.facebook.com/inosi.org/ INOSI]), [https://twitter.com/optima_open OPTIMA] Project Consortium & [https://lpnu.ua/en Lviv Polytechnic National University], comprises researchers with a broad scientific background, ranging from informatics to chemistry and ecology. The core of the consortium has already experience working together in promoting Open Science in Ukraine, particularly within the OPTIMA project and within the Working Group on the [https://www.kmu.gov.ua/en/news/ukraina-pryiednalas-do-krain-ies-shcho-maiut-zatverdzhenyi-plan-realizatsii-pryntsypiv-vidkrytoi-nauky National Plan for Open Science development] in Ukraine. In response to what motivated them in participating in the open call, they state that: ''“Ukraine needs good science to make good decisions in all spheres. This is particularly relevant during the war and will be needed for the post-war recovery. Reproducibility (as a part of the Open Science concept) can boost the value of academic research in Ukraine making science a real game-changer for progress''”. Regarding their future plans for the Ukrainian Reproducibility Network, they share: “''In the short term, the ambition is to kickstart the network of experts, able to lead the discussion on reproducibility and become a role model on the national level. In the long term, the ambition is, of course, to make reproducibility in research a standard by default. This has to be supported by co-creation and sharing best practices, research on research, and making an impact on national policy. We hope that the network will be viable and ambitious enough to compete for international grant funding to achieve this''”. With regard to the global state of reproducibility & scientific integrity, they say: “''The progress on the global level is visible, but it's only the beginning of a long way forward. The key to achieving the goal is a strong research culture that is often missing in many academic communities. Openness and transparency in performing and communicating research are the basic things to be established''.”

====Georgian Consortium====
The consortium from Georgia, comprises three researchers from different institutions: the Department of Human Anatomy at Tbilisi State Medical University ([https://tsmu.edu/ts/home TSMU]), the Faculty of Medicine at Tbilisi State University ([https://www.tsu.ge/en TSU]), the Institute of Morphology, and the Scientific Department at Caucasus International University ([https://ciu.edu.ge/?lang=en CIU]). Brought together as team members of a research group, they were drafting a proposal for a Horizon Europe (HE) project when their HE grant coordinator alerted them about the TIER2 open call announcement. The team was immediately drawn to it, sharing that:

“''During our individual and collective research endeavors, we frequently encountered challenges in reproducing experiment results, a phenomenon that was not isolated to our work but across the global research landscape. [...] a consolidated effort was needed to elevate the state of research in our nation. [...] Moreover, the opportunity to foster a Reproducibility Network (RN) in Georgia provided a platform to unite our nation's fragmented research endeavors, drive standards in research methodologies, and integrate with the global scientific community''”.

Regarding their short-term plans after receiving the award, they list the following: “''Organize the foundational meeting, bringing together stakeholders from various Georgian research institutions, to lay down the operational blueprint for the RN; Launch training sessions that cover core skills in reproducibility, data management, and research design; Conduct sessions in universities and community centers to educate and foster trust in scientific research: Set up an official RN website and leverage social media for real-time updates and engagements”.''

''In the long term, the team envisions to “Establish partnerships with International Reproducibility Networks, facilitating knowledge exchange and joint research projects and collaborate with Georgian institutions to advocate for policies emphasizing reproducibility and transparency''”. Their global vision for the state of reproducibility and scientific integrity “''is one where every piece of research, irrespective of its domain or geography, stands the test of time and validation. We envision a scientific landscape where collaboration, transparency, and inclusivity aren't just ideals but are deeply integrated into research methodologies''.”

They share that the way forward is to prioritize

“''1)Education & Training: Equip researchers, especially the younger generation, with the necessary tools and knowledge to ensure reproducibility.''

''2)Open Science: Promote Open Access publications, making research universally accessible and subject to broader scrutiny.''

''3)Interdisciplinary Collaborations: Foster collaborations across disciplines, pooling expertise and resources to tackle complex research challenges.''

''4)Technological Integration: Leverage technology, especially AI and data analytics, to aid in ensuring research consistency and integrity.''

''If we could change one thing, it would be the isolated nature of scientific endeavors prevalent in many regions, like Georgia. We would foster a globally interconnected research network where findings, methodologies, and tools are shared seamlessly, accelerating scientific progress and ensuring its robustness''”.

Lastly, the Georgian consortium highlights what they would change in the global reproducibility landscape if they could:

“''1)Revise Academic Incentives: The current "publish or perish" culture sometimes prioritizes quantity over quality. We'd advocate for a system where researchers are rewarded for the reproducibility and integrity of their work, not just the volume. 2)Enhanced Training: Incorporate reproducibility and Open Science training at early academic stages, ensuring that upcoming researchers are well-equipped with the necessary skills and ethos. 3)Global Collaboration Platforms: Creation of digital platforms that facilitate global collaboration, data sharing, and mutual validation of research findings, breaking down silos and fostering a truly global scientific community''.”

====Serbian Consortium====
[[File:Serbian RN.png|center|thumb]]

<span lang="EN-US">[https://tier2-project.eu/ TIER2] is excited to announce the winner of the 2024 Open Call aimed at fostering the establishment of a third Reproducibility Network (RN) in “Widening Participation” countries - Serbia. The goal of Reproducibility Networks is to promote rigorous research practices, facilitate interdisciplinary collaborations and discussions, and enhance the trustworthiness of scientific work. The Serbian consortium will thus receive a €5,000 grant to organise an initial meeting, laying the groundwork for establishing an RN in their country.</span>

<span lang="EN-US">The Serbian consortium, consisting of nine organisations – six institutes and three faculties –, brings together diverse academic backgrounds with a shared commitment to improving research culture in Serbia. They focus on integrating Open Science, reproducibility, and inclusive policies into institutions and education. The consortium has previously collaborated on initiatives like the [https://nitra.gov.rs/en/ Team for Open Science in Serbia] and [https://nitra.gov.rs/en/inovacije/projekat-saige the Saige project], organising workshops and training to promote open science practices.</span>

<span lang="EN-US">Motivated by challenges such as low research investment and a scientific system that prioritises quantity over quality, they believe establishing a Reproducibility Network will enhance collaboration and help to address these issues. In the short term, they plan to promote the network through conferences, a kick-off event, and online platforms. Long-term, they aim to integrate Open Science into curricula, incentivise reproducibility, support initiatives beyond major centers, advocate for policy changes, and build international collaborations.</span>

<span lang="EN-US">Their vision for global reproducibility is one where research is transparent, ethical, and rigorous:</span>

<span lang="EN-US">''“In this ideal state, researchers across all disciplines adhere to principles of Open Science, ensuring that their methods, data, and results are accessible and reproducible.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

<span lang="EN-US">They advocate for integrating these principles into education, establishing incentive systems, and fostering collaboration:</span>

<span lang="EN-US">''“We should integrate reproducibility and Open Science practices into university curricula and professional development programs to equip researchers with the necessary skills and knowledge to conduct reproducible research.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

===Resources to set up a Reproducibility Network===

*[https://osf.io/ndwsj Application template]
*[https://osf.io/tsmxh Reviewer guidelines]

==='''<span lang="EN-GB">Call to action – what could you do?</span>'''===
<div>
*'''<span lang="EN-GB">Are you a researcher?</span>''' <span lang="EN-GB">Join an existing RN in your country or, if none exist, identify supporters and form your own network.</span>
</div><div>
*'''<span lang="EN-GB">Are you a funder?</span>''' <span lang="EN-GB">Offer your support by providing (additional) funding for personnel costs, events on reproducibility practices and Open Science, or training opportunities. Further, establish your own award calls to support the establishment of more RNs.</span>
</div><div>
*'''<span lang="EN-GB">Are you a publisher?</span>''' <span lang="EN-GB">Support the wide range of outputs generated by RNs, for example via special issues or journals, to help them increase their reach.</span>
</div>

===Not sure, if your country has an established Reproducibility Network?===

<span lang="EN-GB">Visit the Global Networks page hosted by the UKRN to find out if a Reproducibility Network already exists in your country: https://www.ukrn.org/global-networks/.</span> <div></div>
}}
{{Instruction Step Trainee
|Instruction Step Title=Stakeholder communities
|Instruction Step Text====Why build communities and engage stakeholders?===
<div>
<span lang="EN-GB">TIER2 actively engages with researchers from different research areas (social, life, and computer sciences) and two cross-disciplinary stakeholder groups (funders and publishers) to enhance reproducibility across contexts.</span>
</div><div>
<span lang="EN-GB">Through our co-creation and engagement activities, we are actively fostering communication within and across stakeholder groups creating communities of practices. Opportunities for knowledge exchange and sharing of perspectives further enhances our TIER2 community building efforts</span>
</div><div>
<span lang="EN-GB">We are emphasizing our stakeholder engagement and collaboration especially during the selection, prioritization, development, implementation, and evaluation phases of our new reproducibility-related tools and practices, designed within out eight pilot activities. Through co-creation activities, we explore opportunities for closer collaboration within and across stakeholder communities and facilitate the sharing of resources and expertise. By fostering a sense of ownership and involvement, we ensure that the new tools and practices, created within the project, are valuable and useful to the communities as well as beneficial to all parties involved.</span>

</div>

===<span lang="EN-US">Resources to plan and conduct open and inclusive co-creation activities:</span>===

*[https://osf.io/7zpyd/files/hyf9z Types of co-creation events]
*[https://osf.io/7zpyd/files/sy3za DEIA resources for virtual co-creation events]

[[File:TIER2 Stakeholder Communities.jpg|thumb|Infographic illustrating the stakeholder communities and the activities they are involved with within TIER2.]]
[[File:WCRI Co-creation Poster.jpg|thumb|Strategies for fostering research integrity through community co-creation. ]]
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{{Instruction Step Trainee
|Instruction Step Title=Primers Inititative
|Instruction Step Text=<span lang="EN-US">The primer initiative from the United Kingdom Reproducibility Network was designed introduce a broad audience to important topics and aspects of open and reproducible scholarship. Each primer is a 3-to-4-page summary document which describes the open or reproducible research practice, why one might be interested in it, and how they can be applied or adopted with thorough guidance.</span>

More information on the Primers Initative can be found here: <u>[https://www.ukrn.org/primers/ <span lang="EN-US">https://www.ukrn.org/primers/</span>]</u> .
}}
{{Instruction Step Trainee
|Instruction Step Title=Consortia Partners
|Instruction Step Text=<span lang="EN-US">TIER2 brings a unique combination of skills and perspectives, consisting of eleven partners from seven countries, well spread across Europe. The partner organisations all bring a wealth of expertise and experience regarding the target communities (computer science, life science, social science), research culture reform, technical aspects of infrastructure and services, as well as expertise in social sciences and humanities, and gender aspects of R&I. </span>

==[https://irise-project.eu/ iRise]==
[[File:IRISE .png|thumb]]
iRise aims to deepen understanding of reproducibility drivers, evaluate their effectiveness and provide concrete solutions to enhance scientific evidence.

Their direct objectives are:

- Develop working definitions and a general framework for diagnosing and addressing reproducibility problems, define costs, benefits and opportunities, and assess the utility of theoretical evidence in forecasting the success of interventions.

- Perform scoping and systematic reviews to identify and evaluate existing interventions to improve reproducibility.

- Explore the interface between reproducibility and research culture, and in particular considerations and mainstreaming of equity, diversity, and inclusion (EDI).

- Consult and engage key stakeholder groups in prioritising practices and practical tool development for adoption to increase reproducibility.

- Test efficacy and feasibility of specific interventions to increase reproducibility.

==[https://osiris4r.eu/ OSIRIS]==
[[File:OSIRIS .png|thumb]]
Open Science to Increase Reproducibility in Science (OSIRIS) aims to facilitate the shift by systematically gathering knowledge on the underlying drivers, testing effective evidence-based solutions, identifying incentives for reproducibility by stakeholders, and embedding reproducibility in research design.
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{{Instruction Step Trainee
|Instruction Step Title=FAIRsharing Collections of Standards
|Instruction Step Text=<span lang="EN-GB">These FAIRsharing Collections provide a focal point for the discoverability and visualisation of standards (reporting requirements, terminologies, models/formats, identifier schemas) in the Social Science (147 standards: https://fairsharing.org/6224), Life Sciences (1043 standard: https://fairsharing.org/6225), as well as data policies from publishers and funders (272 policies). These Collections are dynamic, living representations of discipline-specific community’s recommendation and requirements by policy makers. At-a-glance views of other disciplines is available by selecting the relevant subject areas at: https://fairsharing.org/browse/subject</span>

<span lang="EN-GB">Detailed information of the content of these three specific Collection, showing coverages and relationships, is available in their respective narrative reports available at https://doi.org/10.17605/OSF.IO/H4R6M</span>
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Instruction:62bee3f2-de7c-4bc6-ae88-fe8b93f5d1f6

2025-11-07T14:02:31Z

0009-0002-1788-6517:

{{Instruction
|Title=What is reproducibility?
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=This module provides an in-depth introduction to reproducibility through the work of TIER2 and iRise. The purpose and concept of reproducibility is introduced, working definitions are provided for important concepts in relation to reproducibility and replicability, and the futures of reproducibility and illustrated from the perspective of different stakeholders.
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|Important For=All stakeholders in research; Funders; Publishers; Researchers
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|Instruction Step Title=Enabling and Redoing
|Instruction Step Text=The research team within TIER2 present an analytical framework that supports epistemic diversity by examining the potential relevance and degree of feasibility of reproducibility for different modes of knowledge production. The research team find current general typologies with the same aim wanting. They propose top-down derived enumerative lists of kinds of reproducibility organised according to vaguely defined fields, disciplines, methods or so-called research types. Current typologies cannot sufficiently characterise different kinds of research and their varying research context at the granularity needed to deal with how epistemic diversity and reproducibility relate. They also do not clarify the prevailing conceptual confusion surrounding reproducibility and replication. To clarify matters, they propose ''redoing'' to commonly describe the acts of reproducing and replicating and ''enabling'' to describe the acts of making something reproducible and replicable. They suggest mapping practices and epistemic functions to characterise what parts of a study should be redone or enabled and for what intended purposes. The research team propose knowledge production modes (KPM) as an organising construct to situate redoing and enabling within knowledge production’s epistemic, social, and contextual conditions. Epistemologies determine epistemic norms and criteria. Social conditions influence how research is organised, practised, rewarded, reported, and discussed. Contextual conditions put boundaries and restrictions on research, for example, due to subject matter, environment, availability of resources, and technologies, which are the ‘local’ conditions. Their framework clarifies the potential ''relevance'' of redoing and the degree of ''feasibility'' of redoing and enabling for a specific knowledge production mode. Relevance comprises research goals and epistemology. Epistemology is the basic assumption behind knowledge production modes. It determines how knowledge claims are produced and justified with systems of justification, the criteria for good/trustworthy research, and, thus, the epistemic norms. Different ways of knowing have different epistemic norms, practices, and criteria. Feasibility comprises the nature and complexity of the subject under investigation, the necessary investment for redoing or enabling, and the degree of theoretical and methodological uncertainty associated with the actual research. The proposed framework works bottom-up in that knowledge production modes are not defined a priori but derived from the analytical framework. The framework, therefore, supports epistemic diversity by being open and non-hierarchical and working at a sufficient level of granularity to discern the diverse conditions of knowledge production. The research team propose a framework that can clarify, not a cookbook. Enabling in some form always seems relevant in empirical work irrespective of ways of knowing—the same is not true for redoing.

For the full paper click here: [https://osf.io/preprints/metaarxiv/ujnd9_v1 MetaArXiv Preprints - Knowledge Production Modes: The Relevance and Feasibility of Reproducibility]

'''Reference'''

Ulpts, S., & Schneider, J. W. (2023, September 25). Knowledge Production Modes: The Relevance and Feasibility of Reproducibility. <nowiki>https://doi.org/10.31222/osf.io/ujnd9</nowiki>
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{{Instruction Step Trainee
|Instruction Step Title=Defining Reproducibility
|Instruction Step Text=Defining reproducibility and replicability, has been a challenge in the research community, as different interpretations and even contradicting definitions are often used. Defining these terms has proven to be challenging as their use and understanding differs between fields of research. However, the European funded iRise consortium developed a reproducibility glossary by critically reviewing existing scientific literature. The glossary provides working definitions for the use of terms reproducibility, replicability and replication, as well as related concepts.

'''References'''

Voelkl, B., Heyard, R., Fanelli, D., Wever, K., Held, L., Würbel, H., Zellers, S., & Maniadis, Z. (2024). Glossary of common terminology resulting from scoping reviews. https://osf.io/ewybt.
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{{Instruction Step Trainee
|Instruction Step Title=Futures of Reproducibility
|Instruction Step Text=<div>
<span lang="EN-GB">Improving reproducibility is a multifaceted challenge requiring both behavioural and cultural change.</span> <span lang="EN-US">The adoption of reproducibility practices has been sparked and embraced by the Open Science movement. However, a lot of researchers are not fully aware of the implications of reproducibility and how Open Science and reproducibility are connected and intertwined (Haven et al., 2022). To increase awareness and change research practices several steps should be taken (Nosek, 2019). First, the infrastructure for the desired behaviour should be provided to make it possible. Second, the user interface and experience of the infrastructure should be improved to make the behaviour easy. Third, communities of practice should be fostered to make the behaviour visible and so increasingly normative. Fourth, incentives to enact the behaviour should be provided to make it rewarding. Last, policies should be enacted to make the behaviour required (Nosek, 2019). To further this work, we sought to explore the future of reproducibility for different stakeholders and question what should be the next steps for reproducibility and how diverse epistemic contexts can adopt reproducibility in different forms. In this deliverable, we aim to add nuance to the reproducibility debate through flexible investigation of diverse epistemic contexts (researchers from the field of machine learning and researchers working with qualitative methods), exploring the future of reproducibility through the lens of diverse research stakeholders – researchers, funders, and publishers.</span>
</div><div>
<span lang="EN-US">In this context, we look to the future of reproducibility by exploring the preferred scenarios for multiple stakeholders, including how these scenarios can be realized. We reflect on the steps that are necessary for adherence to reproducibility-enabling practices and what different epistemic contexts need to make reproducibility a priority. Lastly, we reflect on what are the new problems that we may face when aiming to improve reproducibility. We believe exploring the possible futures for reproducibility is essential to discover the next steps for different members of the scientific community to take to realize the preferred future and the actions to avoid steering away from the dystopian futures.</span>
</div><div>
<span lang="EN-US">We aim to highlight the essential role of institutions, funders and publishers in this endeavor to make reproducibility a priority by recognizing, rewarding, evaluating and monitoring reproducibility. Ultimately, we hope to steer and move forward the debate on reproducibility in the research community by</span> <span lang="EN-GB">addressing a set of core research questions related to how key stakeholders in the academic community envision the way in which matters of reproducibility should be addressed in the future. More specifically, it asks representatives from research funders, scholarly publishers, and researchers from diverse disciplinary backgrounds:</span>
</div><div>
<span lang="EN-GB">1. What are the preferred futures of reproducibility?</span>
</div><div>
<span lang="EN-GB">2. What are the enablers and barriers on the way to the preferred future or reproducibility more generally?</span>
</div><div>
Below we present the results of our study below.
</div>

For more information, please refer to the full paper: [https://osf.io/preprints/metaarxiv/gx9jq_v1 MetaArXiv Preprints - How to get there from here? Barriers and enablers on the road towards reproducibility in research].
|Instruction Step Interactive Content=Resource:H5P-116
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{{Instruction Step Trainee
|Instruction Step Title=Open Science interventions to improve reproducibility and replicability of research
|Instruction Step Text=<div>Various interventions – especially those related to open science – have been proposed to improve the reproducibility and replicability of scientific research. To assess whether and which interventions have been formally tested for their effectiveness in improving reproducibility and replicability, the research team from TIER2 and OSIRIS conducted a scoping review of the literature on interventions to improve reproducibility. They systematically searched Medline, Embase, Web of Science, PsycINFO, Scopus and Eric, on August 18, 2023. Grey literature was requested from experts in the fields of reproducibility and open science. Any study empirically evaluating the effectiveness of interventions aimed at improving the reproducibility or replicability of scientific methods and findings wasincluded. An intervention could be any action taken by either individual researchers or scientific institutions (e.g., research institutes, publishers and funders). We summarized the retrieved evidence narratively and in an evidence gap map. Of the 104 distinct studies we included, 15 directly measured the effect of an intervention on reproducibility or replicability, while the other research questions addressed a proxy outcome that might be expected to increase reproducibility or replicability, such as data sharing, methods transparency or preregistration. Thirty research questions within included studies were non-comparative and 27 were comparative but cross-sectional, precluding any causal inference. Possible limitations of our review may be the search and selection strategy, which was done by a large team including researchers from different disciplines and different expertise levels. Despite studies investigating a range of interventions and addressing various outcomes, our findings indicate that in general the evidence-base for which various interventions to improve reproducibility of research remains remarkably limited in many respects.
The full pre-print is available here: [https://osf.io/preprints/metaarxiv/a8rmu_v1 MetaArXiv Preprints - Open Science interventions to improve reproducibility and replicability of research: a scoping review preprint]

Dudda, L., Kormann, E., Kozula, M., DeVito, N. J., Klebel, T., Dewi, A. P. M., … Leeflang, M. (2024, June 17). Open Science interventions to improve reproducibility and replicability of research: a scoping review preprint. <nowiki>https://doi.org/10.31222/osf.io/a8rmu</nowiki>
</div>
}}
{{Instruction Step Trainee
|Instruction Step Title=TIER2 Reproducibility Training Modules
|Instruction Step Text=Designed for researchers, publishers, and funders, these specialised courses deliver both theoretical knowledge and practical tools to enhance reproducible research practices.

Our comprehensive training program explores the core principles, methodologies, and discipline-specific challenges of research reproducibility, providing actionable strategies that participants can implement in their work.

Currently, three specialised modules are available online:

*Reproducibility primer for publishers
*Reproducibility primer for funders
*Reproducibility primer for qualitative research
*Reproducibility primer for AI-driven research

Additional modules covering epistemic diversity studies, tools and best practices, and more will be released soon to complete our training program.

Getting started is simple:

#Create a [https://openplato.eu/login/index.php free account] on the OpenPlato platform
#Enrol in either the comprehensive [https://openplato.eu/course/view.php?id=543 TIER2 Reproducibility Training Course] or individual modules based on your interests
#Learn at your own pace with the interactive content
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Instruction:62bee3f2-de7c-4bc6-ae88-fe8b93f5d1f6

2025-11-07T12:01:59Z

0009-0002-1788-6517:

Instruction:62bee3f2-de7c-4bc6-ae88-fe8b93f5d1f6

2025-11-07T12:01:21Z

0009-0002-1788-6517:

{{Instruction
|Title=What is reproducibility?
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=This module provides an in-depth introduction to reproducibility through the work of TIER2 and iRise. The purpose and concept of reproducibility is introduced, working definitions are provided for important concepts in relation to reproducibility and replicability, and the futures of reproducibility and illustrated from the perspective of different stakeholders.
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|Instruction Step Title=Enabling and Redoing
|Instruction Step Text=The research team within TIER2 present an analytical framework that supports epistemic diversity by examining the potential relevance and degree of feasibility of reproducibility for different modes of knowledge production. The research team find current general typologies with the same aim wanting. They propose top-down derived enumerative lists of kinds of reproducibility organised according to vaguely defined fields, disciplines, methods or so-called research types. Current typologies cannot sufficiently characterise different kinds of research and their varying research context at the granularity needed to deal with how epistemic diversity and reproducibility relate. They also do not clarify the prevailing conceptual confusion surrounding reproducibility and replication. To clarify matters, they propose ''redoing'' to commonly describe the acts of reproducing and replicating and ''enabling'' to describe the acts of making something reproducible and replicable. They suggest mapping practices and epistemic functions to characterise what parts of a study should be redone or enabled and for what intended purposes. The research team propose knowledge production modes (KPM) as an organising construct to situate redoing and enabling within knowledge production’s epistemic, social, and contextual conditions. Epistemologies determine epistemic norms and criteria. Social conditions influence how research is organised, practised, rewarded, reported, and discussed. Contextual conditions put boundaries and restrictions on research, for example, due to subject matter, environment, availability of resources, and technologies, which are the ‘local’ conditions. Their framework clarifies the potential ''relevance'' of redoing and the degree of ''feasibility'' of redoing and enabling for a specific knowledge production mode. Relevance comprises research goals and epistemology. Epistemology is the basic assumption behind knowledge production modes. It determines how knowledge claims are produced and justified with systems of justification, the criteria for good/trustworthy research, and, thus, the epistemic norms. Different ways of knowing have different epistemic norms, practices, and criteria. Feasibility comprises the nature and complexity of the subject under investigation, the necessary investment for redoing or enabling, and the degree of theoretical and methodological uncertainty associated with the actual research. The proposed framework works bottom-up in that knowledge production modes are not defined a priori but derived from the analytical framework. The framework, therefore, supports epistemic diversity by being open and non-hierarchical and working at a sufficient level of granularity to discern the diverse conditions of knowledge production. The research team propose a framework that can clarify, not a cookbook. Enabling in some form always seems relevant in empirical work irrespective of ways of knowing—the same is not true for redoing.

For the full paper click here: [https://osf.io/preprints/metaarxiv/ujnd9_v1 MetaArXiv Preprints - Knowledge Production Modes: The Relevance and Feasibility of Reproducibility]

'''Reference'''

Ulpts, S., & Schneider, J. W. (2023, September 25). Knowledge Production Modes: The Relevance and Feasibility of Reproducibility. <nowiki>https://doi.org/10.31222/osf.io/ujnd9</nowiki>
}}
{{Instruction Step Trainee
|Instruction Step Title=Defining Reproducibility
|Instruction Step Text=Defining reproducibility and replicability, has been a challenge in the research community, as different interpretations and even contradicting definitions are often used. Defining these terms has proven to be challenging as their use and understanding differs between fields of research. However, the European funded iRise consortium developed a reproducibility glossary by critically reviewing existing scientific literature. The glossary provides working definitions for the use of terms reproducibility, replicability and replication, as well as related concepts.

'''References'''

Voelkl, B., Heyard, R., Fanelli, D., Wever, K., Held, L., Würbel, H., Zellers, S., & Maniadis, Z. (2024). Glossary of common terminology resulting from scoping reviews. https://osf.io/ewybt.
}}
{{Instruction Step Trainee
|Instruction Step Title=Futures of Reproducibility
|Instruction Step Text=<div>
<span lang="EN-GB">Improving reproducibility is a multifaceted challenge requiring both behavioural and cultural change.</span> <span lang="EN-US">The adoption of reproducibility practices has been sparked and embraced by the Open Science movement. However, a lot of researchers are not fully aware of the implications of reproducibility and how Open Science and reproducibility are connected and intertwined (Haven et al., 2022). To increase awareness and change research practices several steps should be taken (Nosek, 2019). First, the infrastructure for the desired behaviour should be provided to make it possible. Second, the user interface and experience of the infrastructure should be improved to make the behaviour easy. Third, communities of practice should be fostered to make the behaviour visible and so increasingly normative. Fourth, incentives to enact the behaviour should be provided to make it rewarding. Last, policies should be enacted to make the behaviour required (Nosek, 2019). To further this work, we sought to explore the future of reproducibility for different stakeholders and question what should be the next steps for reproducibility and how diverse epistemic contexts can adopt reproducibility in different forms. In this deliverable, we aim to add nuance to the reproducibility debate through flexible investigation of diverse epistemic contexts (researchers from the field of machine learning and researchers working with qualitative methods), exploring the future of reproducibility through the lens of diverse research stakeholders – researchers, funders, and publishers.</span>
</div><div>
<span lang="EN-US">In this context, we look to the future of reproducibility by exploring the preferred scenarios for multiple stakeholders, including how these scenarios can be realized. We reflect on the steps that are necessary for adherence to reproducibility-enabling practices and what different epistemic contexts need to make reproducibility a priority. Lastly, we reflect on what are the new problems that we may face when aiming to improve reproducibility. We believe exploring the possible futures for reproducibility is essential to discover the next steps for different members of the scientific community to take to realize the preferred future and the actions to avoid steering away from the dystopian futures.</span>
</div><div>
<span lang="EN-US">We aim to highlight the essential role of institutions, funders and publishers in this endeavor to make reproducibility a priority by recognizing, rewarding, evaluating and monitoring reproducibility. Ultimately, we hope to steer and move forward the debate on reproducibility in the research community by</span> <span lang="EN-GB">addressing a set of core research questions related to how key stakeholders in the academic community envision the way in which matters of reproducibility should be addressed in the future. More specifically, it asks representatives from research funders, scholarly publishers, and researchers from diverse disciplinary backgrounds:</span>
</div><div>
<span lang="EN-GB">1. What are the preferred futures of reproducibility?</span>
</div><div>
<span lang="EN-GB">2. What are the enablers and barriers on the way to the preferred future or reproducibility more generally?</span>
</div><div>
Below we present the results of our study below.
</div>

For more information, please refer to the full paper: [https://osf.io/preprints/metaarxiv/gx9jq_v1 MetaArXiv Preprints - How to get there from here? Barriers and enablers on the road towards reproducibility in research].
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{{Instruction Step Trainee
|Instruction Step Title=Open Science interventions to improve reproducibility and replicability of research
|Instruction Step Text=<div>Various interventions – especially those related to open science – have been proposed to improve the reproducibility and replicability of scientific research. To assess whether and which interventions have been formally tested for their effectiveness in improving reproducibility and replicability, the research team from TIER2 and OSIRIS conducted a scoping review of the literature on interventions to improve reproducibility. They systematically searched Medline, Embase, Web of Science, PsycINFO, Scopus and Eric, on August 18, 2023. Grey literature was requested from experts in the fields of reproducibility and open science. Any study empirically evaluating the effectiveness of interventions aimed at improving the reproducibility or replicability of scientific methods and findings wasincluded. An intervention could be any action taken by either individual researchers or scientific institutions (e.g., research institutes, publishers and funders). We summarized the retrieved evidence narratively and in an evidence gap map. Of the 104 distinct studies we included, 15 directly measured the effect of an intervention on reproducibility or replicability, while the other research questions addressed a proxy outcome that might be expected to increase reproducibility or replicability, such as data sharing, methods transparency or preregistration. Thirty research questions within included studies were non-comparative and 27 were comparative but cross-sectional, precluding any causal inference. Possible limitations of our review may be the search and selection strategy, which was done by a large team including researchers from different disciplines and different expertise levels. Despite studies investigating a range of interventions and addressing various outcomes, our findings indicate that in general the evidence-base for which various interventions to improve reproducibility of research remains remarkably limited in many respects.
The full pre-print is available here: [https://osf.io/preprints/metaarxiv/a8rmu_v1 MetaArXiv Preprints - Open Science interventions to improve reproducibility and replicability of research: a scoping review preprint]

Dudda, L., Kormann, E., Kozula, M., DeVito, N. J., Klebel, T., Dewi, A. P. M., … Leeflang, M. (2024, June 17). Open Science interventions to improve reproducibility and replicability of research: a scoping review preprint. <nowiki>https://doi.org/10.31222/osf.io/a8rmu</nowiki>
</div>
}}
{{Instruction Step Trainee
|Instruction Step Title=TIER2 Reproducibility Training Modules
|Instruction Step Text=Designed for researchers, publishers, and funders, these specialised courses deliver both theoretical knowledge and practical tools to enhance reproducible research practices.

Our comprehensive training program explores the core principles, methodologies, and discipline-specific challenges of research reproducibility, providing actionable strategies that participants can implement in their work.

Currently, three specialised modules are available online:

* Reproducibility primer for publishers
* Reproducibility primer for funders
* Reproducibility primer for qualitative research
* Reproducibility primer for AI-driven research

Additional modules covering epistemic diversity studies, tools and best practices, and more will be released soon to complete our training program.

Getting started is simple:

# Create a [https://openplato.eu/login/index.php free account] on the OpenPlato platform
# Enrol in either the comprehensive [https://openplato.eu/course/view.php?id=543 TIER2 Reproducibility Training Course] or individual modules based on your interests
# Learn at your own pace with the interactive content
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|Involves=TIER2
|Has Good Practice And Misconduct=Reproducibility
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Instruction:4bc3edc0-d493-4f35-a742-e4cee5569562

2025-10-30T09:56:04Z

0009-0002-1788-6517:

{{Instruction
|Title=New Tools and Services for Reproducibility
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=TIER2 aims to better understand the causes, consequences and possible solutions of perceived poor levels of reproductivity of research across research contexts. With a focus on social, life, and computer sciences, as well as research publishers and funders, the project aims to increase awareness, build capacity, and propose innovative solutions sensitive to varied research cultures. Central to its approach are eight Pilot activities designed to develop, implement, and evaluate new reproducibility-related tools and practices.
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|Important For=All stakeholders in research
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|Instruction Step Title=Pilot 1 - Decision Aid
|Instruction Step Text=<span lang="EN-US">TIER2's Decision Aid provides clarity on the meaning, relevance, and feasibility of ‘reproducibility’ for researchers to aid them in identifying what type of reproducibility is relevant for their research and indicate what they must consider regarding how feasible such ‘reproducibility’ would be for them.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 2 - Reproducibility Management Plan (RMP)
|Instruction Step Text=<span lang="EN-US">The [https://osf.io/pn27g Reproducibility Management Plan (RMP) Pilot] aims to create a prototype of key thematic subjects and questions that will serve as the starting point to support reproducibility at the planning stage of research. Work involves defining what an RMP is, integrating it into the ARGOS service, and testing its effectiveness with feedback from the community. The pilot addresses researchers, beneficiaries and funders for its adoption.</span><div>
Please find the integrated ARGOS tool here: <u>https://argos.openaire.eu/portal/</u><u>.</u>

<u><span lang="EN-US">Tutorials on OpenPlato:</span></u>

# <u>'''<span lang="EN-US">ARGOS Service for Admins</span>'''<span lang="EN-US">: https://openplato.eu/course/view.php?id=150</span></u>
# <u>'''<span lang="EN-US">ARGOS Info Pack</span>'''<span lang="EN-US">: https://openplato.eu/course/view.php?id=547</span></u>
# <u>'''<span lang="EN-US">ARGOS Service for Users</span>'''<span lang="EN-US">: https://openplato.eu/course/view.php?id=122</span></u>
</div><div>
<u><span lang="EN-US">Reports on co-creation activities: <nowiki>https://osf.io/fp7zt/</nowiki></span></u>
</div>
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{{Instruction Step Trainee
|Instruction Step Title=Pilot 3 - Reproducible Workflows
|Instruction Step Text=<span lang="EN-US">In this pilot, [https://schema-lab.hypatia-comp.athenarc.gr/ SCHEMA] was developed as an open-source framework, comprising SCHEMA api for programmatic execution and SCHEMA lab for a user-friendly web interface to support reproducible computational research through containerized execution, metadata capturing and experiment management. It provides a scalable environment that enables researchers to design and run reproducible computational workflows and experiments.</span>
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{{Instruction Step Trainee
|Instruction Step Title=Pilot 4 - The Reproducibility Checklist
|Instruction Step Text=<span lang="EN-US"><span lang="EN-GB">The <span lang="DE">[https://eur04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FGESIS-Methods-Hub%2Fguidelines-for-methods%2Fblob%2Fmain%2FREADME-template.md&data=05%7C02%7Cb.leitner%40amsterdamumc.nl%7C98306bdc1d14436a474308de062e488a%7C68dfab1a11bb4cc6beb528d756984fb6%7C0%7C0%7C638954993173754302%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=8wKJxWZb4qfVKLG%2F%2Bgn4HWuQCxrkIvrUyENg%2FEEwiWM%3D&reserved=0 Reproducibility Checklist for Computational Social Science Research]</span> provides a simple, structured framework to enhance the reproducibility of computational methods shared on [https://eur04.safelinks.protection.outlook.com/?url=http%3A%2F%2Fmethodshub.gesis.org%2F&data=05%7C02%7Cb.leitner%40amsterdamumc.nl%7C98306bdc1d14436a474308de062e488a%7C68dfab1a11bb4cc6beb528d756984fb6%7C0%7C0%7C638954993173788095%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=fZvqBgWjUcBuH%2FNJKGAl8WYPcNRsRQujUc8k%2FbPcG3Q%3D&reserved=0 Methods Hub]. Designed for minimal effort and maximum usability, the checklist helps researchers document and share their data and code in a consistent, verifiable way that fosters trust and collaboration within the social science community. This pilot contributes to more efficient, transparent, and reproducible computational social science by integrating practical usability with clear documentation standards.</span></span>

<span lang="EN-US">The [https://github.com/GESIS-Methods-Hub/guidelines-for-methods/blob/main/README-template.md <u>checklist tempelate</u>] is publicly available through GitHub [https://github.com/GESIS-Methods-Hub/guidelines-for-methods <u>project repositoriy</u>] and is accompanied by [https://github.com/GESIS-Methods-Hub/guidelines-for-methods/blob/main/guidelines.md <u>user guidance</u>] for researchers who want to submit a method. These resources explain how to apply the checklist in practice, both independently and in connection with [https://methodshub.gesis.org/ <u>Methods Hub</u>].</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 5 - The Reproducibility Promotion Plan for Funders (RPP)
|Instruction Step Text=<span lang="EN-US">The Reproducibility Promotion Plan for Funders (RPP) has developed a policy template with recommendations for funders to foster reproducible practices both in the research they fund across three key areas of funding work: evaluation and monitoring, policy and definitions, and incentives. The RPP provides actionable recommendations and best practice examples that funders and funding institutions can adapt to meet their specific needs.</span>

All drafts of the RPP can be found on [https://osf.io/3fpbj/ OSF].

[[File:RPP4F One Pager.jpg|center|thumb]]
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{{Instruction Step Trainee
|Instruction Step Title=Pilot 6 - The Reproducibility Monitoring Dashboard
|Instruction Step Text=<span lang="EN-US">The Reproducibility Monitoring Dashboard hosts tools that enable funding agencies to track and monitor the reusability of research artifacts across various projects, programs, topics, and disciplines. This auto-generated dashboard assesses the impacts of policies related to data and code sharing.</span> <div>
# <u><span lang="EN-US">OSF link for development materials: https://osf.io/wnvtx/</span></u>
# <u><span lang="EN-US">Dashboard prototype for EU-funded Machine Learning projects: https://app.powerbi.com/view?r=eyJrIjoiZTc0MmU1ZTktNzAyMy00ZTk1LWFkZmYtNDVmYjU2YzdhMzZhIiwidCI6IjZhZTA3NzAyLWM1ZjctNGYzOC05Yjg3LWFjYWQ2MmE3NWQ5MyIsImMiOjl9</span></u>
</div>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 7 - Editorial Workflows to Increase Data Sharing
|Instruction Step Text=<span lang="EN-GB">A key aspect of (computational) reproducibility is availability of data. However, sharing of research data is still not the norm across disciplines. Developed co-creatively with stakeholders from major publishers, the workflow and email template provide a low-effort approach for publishers to nudge researchers towards sharing their data for journals operating under a “share upon request” policy. Documentation on the workflow and email template can be found in [https://doi.org/10.17605/OSF.IO/S7GJV TIER2 D5.2].</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 8- An Editorial Reference Handbook for Reproducibility and FAIRness
|Instruction Step Text=<div>
<span lang="EN-US">The [https://publishers.fairassist.org/ <u>Editorial Reference Handbook</u>] informs and assists journals to operationalise a set of checks necessary to make the data underlying published research findings more findable, accessible, interoperable and reusable (FAIR) to underpin reproducibility. The Handbook targets in-house staff managing the manuscripts primarily, but it will also benefit reviewers, authors and even those providing services to publishers by making the fundamental checks and requirements transparent and understandable.</span>
</div><div>
<span lang="EN-US">The Handbook includes three interlinked components: a checklist of 12 elements, a flowchart that outlines the ideal internal manuscript submission workflow (who should perform the checks and when), and a guidance to help users to implement the checks effectively, with definitions and tips.</span>
</div><div>
<span lang="EN-US">The Handbook fills a gap, because no common guidance existed on the practical implementation of these checks across a complex publishing workflow and the variety of individuals and teams involved. This pilot saw the participation of more than 30 individuals, from more than 20 journals of major publishers: CUP, Cell Press, EMBO Press, Taylor & Francis, GigaScience Press, OUP, PLOS, Springer Nature.</span>
</div>
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Initiative:286109fc-03cb-4a08-bd45-c0276eae3079

2025-10-29T15:22:57Z

0009-0002-1788-6517:

{{Initiative
|Title=TIER2
|Image=Download.png
|Has Link=https://tier2-project.eu/
|Is About=TIER2 (enhancing '''T'''rust, '''I'''ntegrity and '''E'''fficiency in '''R'''esearch through next-level '''R'''eproducibility) will increase reproducibility of scientific research results that will bring trust, integrity, and efficiency to the European Research Area (ERA) and the global Research and Innovation (R&I) system. The project will boost knowledge on reproducibility, create tools, engage communities, implement interventions and policy across different contexts to increase re-use and overall quality of research results. TIER2 aims to build an evidence-base on the extent and efficacy of existing reproducibility practices and co-create new tools to enhance reproducibility across diverse contexts.

Publications from and relating to the TIER2 project can be found [https://tier2-project.eu/library?type=3&Filter%5Bsort%5D=year+desc&search= here].
}}

Instruction:7c159fc9-db27-4623-9432-9c37b8889f89

2025-10-22T11:41:40Z

0009-0002-1788-6517:

{{Instruction
|Title=Communities and collaborators
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=On this page we present the TIER2 Reproducibility Network Award, the stakeholder community building activities and efforts of TIER2, our consortia partners (iRise and OSIRIS), and finally the UKRN Primers initative.
|Has Duration=1
|Important For=All stakeholders in research
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{{Instruction Step Trainee
|Instruction Step Title=Reproducibility Network Award
|Instruction Step Text=<div>
==='''<span lang="EN-GB">What is a Reproducibility Network?</span>''' ===
</div><div><div>
<span lang="EN-GB">A national Reproducibility Network <u>(RN)</u> is a countrywide peer-led consortium that aims to improve research practices by promoting, supporting, and investigating factors contributing to robust research including, but not limited to, reproducibility, replicability, and Open Science. Activities may include promoting training activities, disseminating best practices, supporting research on reproducible research practices, and advocacy for reproducible and open research. </span>
</div><div>
<span lang="EN-GB">An RN typically serves as a hub to connect researchers to exchange ideas and good practices, promoting collaboration among researchers from a range of scientific disciplines. These networks provide infrastructure, facilitate opportunities for researchers and initiatives to support and amplify each other’s efforts, and foster community building as well as shared problem solving. </span>
</div><div>
<span lang="EN-GB">RNs can serve as connectors to other stakeholder groups such as universities, funders, or academic publishers.</span>
</div></div>

===Benefits for setting up an Reproducibility Network?===

<span lang="EN-GB">By providing seed funding for the establishment of a new RN, you actively contribute to the strengthening of reproducibility and Open Science in your local ecosystem. The widespread presence of RNs is crucial, as they function as points of contact for scientific communities who, across e.g., disciplinary, demographic, and geographic contexts, face different challenges and barriers. RNs can provide local and tailored support and keep in mind the different stages of readiness of their local communities for implementing reproducible research practices.</span>

==="Lessons learned" from the TIER2 award===
1. '''<span lang="EN-GB">Build strong community links.</span>''' <span lang="EN-GB">Involve already existing and successful RNs in the establishment of new RNs. This ensures that new RNs receive valuable guidance, input and support early in the establishment process.</span>

2. '''<span lang="EN-GB">Expand connections and broaden the reach.</span>''' <span lang="EN-GB">Reach out to researchers and other relevant stakeholders, such as universities, as this is important for local support and the sustainability of the RN. However, identifying and connecting with researchers in Horizon Europe Widening Participation countries (WIDERA countries) who are active in reproducible research and Open Science practices can be challenging.</span>

3. '''<span lang="EN-GB">Facilitate international support.</span>''' <span lang="EN-GB">Several RNs across the globe exist and more are being established. Build strong international connections amongst them to facilitate the sharing of resources and best practices, this will help to coordinate and amplify efforts.</span>

4. '''<span lang="EN-GB">Focus on the local ecosystem.</span>''' <span lang="EN-GB">RNs are national networks that promote transparent and trustworthy practices in their local research ecosystems. Recognize local needs, geopolitical conditions as well as barriers and available resources.</span>

===How has TIER2 supported the awarded networks?===

1. TIER2 members and award organizers have facilitated connections between awardees and existing international Reproducibility and Open Science networks. via email contacts as well as through virtual and in-person meetings.

2. <span lang="EN-GB">TIER2 award organizers, have added awardees, with their consent, to various mailing lists and newsletters from different international RNs.</span>

3.<span lang="EN-GB">Further, TIER2 award organizers have invited awardees to attend and speak at several Open Science and reproducibility events to meet (steering group) members from other RNs and (inter-)national initiatives.</span>

<span lang="EN-GB">4. TIER2 project members as well as award organizers have provided the awardees with resources and information on relevant topics, including different RN structures, website layout and structure, as well as language.</span>

===Awardess of the TIER2 Reproducibility Network Award===

TIER2 is proud to announce the two awarded consortia based in Ukraine and Georgia who will receive the monetary awards from the Reproducibility Network open call this summer. Multiple scientific consortia from Horizon Europe “[https://www.era-learn.eu/support-for-partnerships/additional-activities/openness-inclusivness-transparency/widening-and-inclusiveness Widening Participation]” countries submitted applications describing their plans and motivations for establishing a Reproducibility Network in their home country which TIER2 would support with a €5000 prize.

[[File:Ukraine and Georgia RN.png|center|thumb]]

====Ukrainian Consortium====
The Ukrainian consortium, from the Institute for Open Science and Innovation ([https://www.facebook.com/inosi.org/ INOSI]), [https://twitter.com/optima_open OPTIMA] Project Consortium & [https://lpnu.ua/en Lviv Polytechnic National University], comprises researchers with a broad scientific background, ranging from informatics to chemistry and ecology. The core of the consortium has already experience working together in promoting Open Science in Ukraine, particularly within the OPTIMA project and within the Working Group on the [https://www.kmu.gov.ua/en/news/ukraina-pryiednalas-do-krain-ies-shcho-maiut-zatverdzhenyi-plan-realizatsii-pryntsypiv-vidkrytoi-nauky National Plan for Open Science development] in Ukraine. In response to what motivated them in participating in the open call, they state that: ''“Ukraine needs good science to make good decisions in all spheres. This is particularly relevant during the war and will be needed for the post-war recovery. Reproducibility (as a part of the Open Science concept) can boost the value of academic research in Ukraine making science a real game-changer for progress''”. Regarding their future plans for the Ukrainian Reproducibility Network, they share: “''In the short term, the ambition is to kickstart the network of experts, able to lead the discussion on reproducibility and become a role model on the national level. In the long term, the ambition is, of course, to make reproducibility in research a standard by default. This has to be supported by co-creation and sharing best practices, research on research, and making an impact on national policy. We hope that the network will be viable and ambitious enough to compete for international grant funding to achieve this''”. With regard to the global state of reproducibility & scientific integrity, they say: “''The progress on the global level is visible, but it's only the beginning of a long way forward. The key to achieving the goal is a strong research culture that is often missing in many academic communities. Openness and transparency in performing and communicating research are the basic things to be established''.”

====Georgian Consortium====
The consortium from Georgia, comprises three researchers from different institutions: the Department of Human Anatomy at Tbilisi State Medical University ([https://tsmu.edu/ts/home TSMU]), the Faculty of Medicine at Tbilisi State University ([https://www.tsu.ge/en TSU]), the Institute of Morphology, and the Scientific Department at Caucasus International University ([https://ciu.edu.ge/?lang=en CIU]). Brought together as team members of a research group, they were drafting a proposal for a Horizon Europe (HE) project when their HE grant coordinator alerted them about the TIER2 open call announcement. The team was immediately drawn to it, sharing that:

“''During our individual and collective research endeavors, we frequently encountered challenges in reproducing experiment results, a phenomenon that was not isolated to our work but across the global research landscape. [...] a consolidated effort was needed to elevate the state of research in our nation. [...] Moreover, the opportunity to foster a Reproducibility Network (RN) in Georgia provided a platform to unite our nation's fragmented research endeavors, drive standards in research methodologies, and integrate with the global scientific community''”. Regarding their short-term plans after receiving the award, they list the following: “''Organize the foundational meeting, bringing together stakeholders from various Georgian research institutions, to lay down the operational blueprint for the RN; Launch training sessions that cover core skills in reproducibility, data management, and research design; Conduct sessions in universities and community centers to educate and foster trust in scientific research: Set up an official RN website and leverage social media for real-time updates and engagements”. In the long term, the team envisions to “Establish partnerships with International Reproducibility Networks, facilitating knowledge exchange and joint research projects and collaborate with Georgian institutions to advocate for policies emphasizing reproducibility and transparency''”. Their global vision for the state of reproducibility and scientific integrity “''is one where every piece of research, irrespective of its domain or geography, stands the test of time and validation. We envision a scientific landscape where collaboration, transparency, and inclusivity aren't just ideals but are deeply integrated into research methodologies''.”

They share that the way forward is to prioritize

“''1)Education & Training: Equip researchers, especially the younger generation, with the necessary tools and knowledge to ensure reproducibility.''

''2)Open Science: Promote Open Access publications, making research universally accessible and subject to broader scrutiny.''

''3)Interdisciplinary Collaborations: Foster collaborations across disciplines, pooling expertise and resources to tackle complex research challenges.''

''4)Technological Integration: Leverage technology, especially AI and data analytics, to aid in ensuring research consistency and integrity.''

''If we could change one thing, it would be the isolated nature of scientific endeavors prevalent in many regions, like Georgia. We would foster a globally interconnected research network where findings, methodologies, and tools are shared seamlessly, accelerating scientific progress and ensuring its robustness''”.

Lastly, the Georgian consortium highlights what they would change in the global reproducibility landscape if they could: “''1)Revise Academic Incentives: The current "publish or perish" culture sometimes prioritizes quantity over quality. We'd advocate for a system where researchers are rewarded for the reproducibility and integrity of their work, not just the volume. 2)Enhanced Training: Incorporate reproducibility and Open Science training at early academic stages, ensuring that upcoming researchers are well-equipped with the necessary skills and ethos. 3)Global Collaboration Platforms: Creation of digital platforms that facilitate global collaboration, data sharing, and mutual validation of research findings, breaking down silos and fostering a truly global scientific community''.”

====Serbian Consortium====
[[File:Serbian RN.png|center|thumb]]

<span lang="EN-US">[https://tier2-project.eu/ TIER2] is excited to announce the winner of the 2024 Open Call aimed at fostering the establishment of a third Reproducibility Network (RN) in “Widening Participation” countries - Serbia. The goal of Reproducibility Networks is to promote rigorous research practices, facilitate interdisciplinary collaborations and discussions, and enhance the trustworthiness of scientific work. The Serbian consortium will thus receive a €5,000 grant to organise an initial meeting, laying the groundwork for establishing an RN in their country.</span>

<span lang="EN-US">The Serbian consortium, consisting of nine organisations – six institutes and three faculties –, brings together diverse academic backgrounds with a shared commitment to improving research culture in Serbia. They focus on integrating Open Science, reproducibility, and inclusive policies into institutions and education. The consortium has previously collaborated on initiatives like the [https://nitra.gov.rs/en/ Team for Open Science in Serbia] and [https://nitra.gov.rs/en/inovacije/projekat-saige the Saige project], organising workshops and training to promote open science practices.</span>

<span lang="EN-US">Motivated by challenges such as low research investment and a scientific system that prioritises quantity over quality, they believe establishing a Reproducibility Network will enhance collaboration and help to address these issues. In the short term, they plan to promote the network through conferences, a kick-off event, and online platforms. Long-term, they aim to integrate Open Science into curricula, incentivise reproducibility, support initiatives beyond major centers, advocate for policy changes, and build international collaborations.</span>

<span lang="EN-US">Their vision for global reproducibility is one where research is transparent, ethical, and rigorous:</span>

<span lang="EN-US">''“In this ideal state, researchers across all disciplines adhere to principles of Open Science, ensuring that their methods, data, and results are accessible and reproducible.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

<span lang="EN-US">They advocate for integrating these principles into education, establishing incentive systems, and fostering collaboration:</span>

<span lang="EN-US">''“We should integrate reproducibility and Open Science practices into university curricula and professional development programs to equip researchers with the necessary skills and knowledge to conduct reproducible research.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

=== Resources to set up a Reproducibility Network ===

* [https://osf.io/ndwsj Application template]
* [https://osf.io/tsmxh Reviewer guidelines]

==='''<span lang="EN-GB">Call to action – what could you do?</span>'''===
<div>
*'''<span lang="EN-GB">Are you a researcher?</span>''' <span lang="EN-GB">Join an existing RN in your country or, if none exist, identify supporters and form your own network.</span>
</div><div>
*'''<span lang="EN-GB">Are you a funder?</span>''' <span lang="EN-GB">Offer your support by providing (additional) funding for personnel costs, events on reproducibility practices and Open Science, or training opportunities. Further, establish your own award calls to support the establishment of more RNs.</span>
</div><div>
*'''<span lang="EN-GB">Are you a publisher?</span>''' <span lang="EN-GB">Support the wide range of outputs generated by RNs, for example via special issues or journals, to help them increase their reach.</span>
</div>

===Not sure, if your country has an established Reproducibility Network?===

<span lang="EN-GB">Visit the Global Networks page hosted by the UKRN to find out if a Reproducibility Network already exists in your country: https://www.ukrn.org/global-networks/.</span> <div></div>
}}
{{Instruction Step Trainee
|Instruction Step Title=Stakeholder communities
|Instruction Step Text====Why build communities and engage stakeholders?===
<div>
<span lang="EN-GB">TIER2 actively engages with researchers from different research areas (social, life, and computer sciences) and two cross-disciplinary stakeholder groups (funders and publishers) to enhance reproducibility across contexts.</span>
</div><div>
<span lang="EN-GB">Through our co-creation and engagement activities, we are actively fostering communication within and across stakeholder groups creating communities of practices. Opportunities for knowledge exchange and sharing of perspectives further enhances our TIER2 community building efforts</span>
</div><div>
<span lang="EN-GB">We are emphasizing our stakeholder engagement and collaboration especially during the selection, prioritization, development, implementation, and evaluation phases of our new reproducibility-related tools and practices, designed within out eight pilot activities. Through co-creation activities, we explore opportunities for closer collaboration within and across stakeholder communities and facilitate the sharing of resources and expertise. By fostering a sense of ownership and involvement, we ensure that the new tools and practices, created within the project, are valuable and useful to the communities as well as beneficial to all parties involved.</span>

</div>

===<span lang="EN-US">Resources to plan and conduct open and inclusive co-creation activities:</span>===

*[https://osf.io/7zpyd/files/hyf9z Types of co-creation events]
*[https://osf.io/7zpyd/files/sy3za DEIA resources for virtual co-creation events]

[[File:TIER2 Stakeholder Communities.jpg|thumb|Infographic illustrating the stakeholder communities and the activities they are involved with within TIER2.]]
[[File:WCRI Co-creation Poster.jpg|thumb|Strategies for fostering research integrity through community co-creation. ]]
}}
{{Instruction Step Trainee
|Instruction Step Title=Primers Inititative
|Instruction Step Text=<span lang="EN-US">The primer initiative from the United Kingdom Reproducibility Network was designed introduce a broad audience to important topics and aspects of open and reproducible scholarship. Each primer is a 3-to-4-page summary document which describes the open or reproducible research practice, why one might be interested in it, and how they can be applied or adopted with thorough guidance.</span>

More information on the Primers Initative can be found here: <u>[https://www.ukrn.org/primers/ <span lang="EN-US">https://www.ukrn.org/primers/</span>]</u> .
}}
{{Instruction Step Trainee
|Instruction Step Title=Consortia Partners
|Instruction Step Text=<span lang="EN-US">TIER2 brings a unique combination of skills and perspectives, consisting of eleven partners from seven countries, well spread across Europe. The partner organisations all bring a wealth of expertise and experience regarding the target communities (computer science, life science, social science), research culture reform, technical aspects of infrastructure and services, as well as expertise in social sciences and humanities, and gender aspects of R&I. </span>

==[https://irise-project.eu/ iRise]==
[[File:IRISE .png|thumb]]
iRise aims to deepen understanding of reproducibility drivers, evaluate their effectiveness and provide concrete solutions to enhance scientific evidence.

Their direct objectives are:

- Develop working definitions and a general framework for diagnosing and addressing reproducibility problems, define costs, benefits and opportunities, and assess the utility of theoretical evidence in forecasting the success of interventions.

- Perform scoping and systematic reviews to identify and evaluate existing interventions to improve reproducibility.

- Explore the interface between reproducibility and research culture, and in particular considerations and mainstreaming of equity, diversity, and inclusion (EDI).

- Consult and engage key stakeholder groups in prioritising practices and practical tool development for adoption to increase reproducibility.

- Test efficacy and feasibility of specific interventions to increase reproducibility.

==[https://osiris4r.eu/ OSIRIS]==
[[File:OSIRIS .png|thumb]]
Open Science to Increase Reproducibility in Science (OSIRIS) aims to facilitate the shift by systematically gathering knowledge on the underlying drivers, testing effective evidence-based solutions, identifying incentives for reproducibility by stakeholders, and embedding reproducibility in research design.
}}
{{Instruction Remarks Trainee}}
{{Custom TabContent Close Trainee}}
{{Custom TabContent Trainer Open}}
{{Instruction Steps Foldout Trainer}}
{{Instruction Perspective Trainer}}
{{Instruction Remarks Trainer}}
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{{Related To}}
{{Tags}}

Instruction:7c159fc9-db27-4623-9432-9c37b8889f89

2025-10-22T11:40:35Z

0009-0002-1788-6517:

{{Instruction
|Title=Communities and collaborators
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=On this page we present the TIER2 Reproducibility Network Award, the stakeholder community building activities and efforts of TIER2, our consortia partners (iRise and OSIRIS), and finally the UKRN Primers initative.
|Has Duration=1
|Important For=All stakeholders in research
}}
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{{Instruction Perspective Trainee}}
{{Instruction Step Trainee
|Instruction Step Title=Reproducibility Network Award
|Instruction Step Text=<div>
==='''<span lang="EN-GB">What is a Reproducibility Network?</span>''' ===
</div><div><div>
<span lang="EN-GB">A national Reproducibility Network <u>(RN)</u> is a countrywide peer-led consortium that aims to improve research practices by promoting, supporting, and investigating factors contributing to robust research including, but not limited to, reproducibility, replicability, and Open Science. Activities may include promoting training activities, disseminating best practices, supporting research on reproducible research practices, and advocacy for reproducible and open research. </span>
</div><div>
<span lang="EN-GB">An RN typically serves as a hub to connect researchers to exchange ideas and good practices, promoting collaboration among researchers from a range of scientific disciplines. These networks provide infrastructure, facilitate opportunities for researchers and initiatives to support and amplify each other’s efforts, and foster community building as well as shared problem solving. </span>
</div><div>
<span lang="EN-GB">RNs can serve as connectors to other stakeholder groups such as universities, funders, or academic publishers.</span>
</div></div>

===Benefits for setting up an Reproducibility Network?===

<span lang="EN-GB">By providing seed funding for the establishment of a new RN, you actively contribute to the strengthening of reproducibility and Open Science in your local ecosystem. The widespread presence of RNs is crucial, as they function as points of contact for scientific communities who, across e.g., disciplinary, demographic, and geographic contexts, face different challenges and barriers. RNs can provide local and tailored support and keep in mind the different stages of readiness of their local communities for implementing reproducible research practices.</span>

==="Lessons learned" from the TIER2 award===
1. '''<span lang="EN-GB">Build strong community links.</span>''' <span lang="EN-GB">Involve already existing and successful RNs in the establishment of new RNs. This ensures that new RNs receive valuable guidance, input and support early in the establishment process.</span>

2. '''<span lang="EN-GB">Expand connections and broaden the reach.</span>''' <span lang="EN-GB">Reach out to researchers and other relevant stakeholders, such as universities, as this is important for local support and the sustainability of the RN. However, identifying and connecting with researchers in Horizon Europe Widening Participation countries (WIDERA countries) who are active in reproducible research and Open Science practices can be challenging.</span>

3. '''<span lang="EN-GB">Facilitate international support.</span>''' <span lang="EN-GB">Several RNs across the globe exist and more are being established. Build strong international connections amongst them to facilitate the sharing of resources and best practices, this will help to coordinate and amplify efforts.</span>

4. '''<span lang="EN-GB">Focus on the local ecosystem.</span>''' <span lang="EN-GB">RNs are national networks that promote transparent and trustworthy practices in their local research ecosystems. Recognize local needs, geopolitical conditions as well as barriers and available resources.</span>

===How has TIER2 supported the awarded networks?===

1. TIER2 members and award organizers have facilitated connections between awardees and existing international Reproducibility and Open Science networks. via email contacts as well as through virtual and in-person meetings.

2. <span lang="EN-GB">TIER2 award organizers, have added awardees, with their consent, to various mailing lists and newsletters from different international RNs.</span>

3.<span lang="EN-GB">Further, TIER2 award organizers have invited awardees to attend and speak at several Open Science and reproducibility events to meet (steering group) members from other RNs and (inter-)national initiatives.</span>

<span lang="EN-GB">4. TIER2 project members as well as award organizers have provided the awardees with resources and information on relevant topics, including different RN structures, website layout and structure, as well as language.</span>

===Awardess of the TIER2 Reproducibility Network Award===

TIER2 is proud to announce the two awarded consortia based in Ukraine and Georgia who will receive the monetary awards from the Reproducibility Network open call this summer. Multiple scientific consortia from Horizon Europe “[https://www.era-learn.eu/support-for-partnerships/additional-activities/openness-inclusivness-transparency/widening-and-inclusiveness Widening Participation]” countries submitted applications describing their plans and motivations for establishing a Reproducibility Network in their home country which TIER2 would support with a €5000 prize.

[[File:Ukraine and Georgia RN.png|center|thumb]]

====Ukrainian Consortium====
The Ukrainian consortium, from the Institute for Open Science and Innovation ([https://www.facebook.com/inosi.org/ INOSI]), [https://twitter.com/optima_open OPTIMA] Project Consortium & [https://lpnu.ua/en Lviv Polytechnic National University], comprises researchers with a broad scientific background, ranging from informatics to chemistry and ecology. The core of the consortium has already experience working together in promoting Open Science in Ukraine, particularly within the OPTIMA project and within the Working Group on the [https://www.kmu.gov.ua/en/news/ukraina-pryiednalas-do-krain-ies-shcho-maiut-zatverdzhenyi-plan-realizatsii-pryntsypiv-vidkrytoi-nauky National Plan for Open Science development] in Ukraine. In response to what motivated them in participating in the open call, they state that: ''“Ukraine needs good science to make good decisions in all spheres. This is particularly relevant during the war and will be needed for the post-war recovery. Reproducibility (as a part of the Open Science concept) can boost the value of academic research in Ukraine making science a real game-changer for progress''”. Regarding their future plans for the Ukrainian Reproducibility Network, they share: “''In the short term, the ambition is to kickstart the network of experts, able to lead the discussion on reproducibility and become a role model on the national level. In the long term, the ambition is, of course, to make reproducibility in research a standard by default. This has to be supported by co-creation and sharing best practices, research on research, and making an impact on national policy. We hope that the network will be viable and ambitious enough to compete for international grant funding to achieve this''”. With regard to the global state of reproducibility & scientific integrity, they say: “''The progress on the global level is visible, but it's only the beginning of a long way forward. The key to achieving the goal is a strong research culture that is often missing in many academic communities. Openness and transparency in performing and communicating research are the basic things to be established''.”

====Georgian Consortium====
The consortium from Georgia, comprises three researchers from different institutions: the Department of Human Anatomy at Tbilisi State Medical University ([https://tsmu.edu/ts/home TSMU]), the Faculty of Medicine at Tbilisi State University ([https://www.tsu.ge/en TSU]), the Institute of Morphology, and the Scientific Department at Caucasus International University ([https://ciu.edu.ge/?lang=en CIU]). Brought together as team members of a research group, they were drafting a proposal for a Horizon Europe (HE) project when their HE grant coordinator alerted them about the TIER2 open call announcement. The team was immediately drawn to it, sharing that:

“''During our individual and collective research endeavors, we frequently encountered challenges in reproducing experiment results, a phenomenon that was not isolated to our work but across the global research landscape. [...] a consolidated effort was needed to elevate the state of research in our nation. [...] Moreover, the opportunity to foster a Reproducibility Network (RN) in Georgia provided a platform to unite our nation's fragmented research endeavors, drive standards in research methodologies, and integrate with the global scientific community''”. Regarding their short-term plans after receiving the award, they list the following: “''Organize the foundational meeting, bringing together stakeholders from various Georgian research institutions, to lay down the operational blueprint for the RN; Launch training sessions that cover core skills in reproducibility, data management, and research design; Conduct sessions in universities and community centers to educate and foster trust in scientific research: Set up an official RN website and leverage social media for real-time updates and engagements”. In the long term, the team envisions to “Establish partnerships with International Reproducibility Networks, facilitating knowledge exchange and joint research projects and collaborate with Georgian institutions to advocate for policies emphasizing reproducibility and transparency''”. Their global vision for the state of reproducibility and scientific integrity “''is one where every piece of research, irrespective of its domain or geography, stands the test of time and validation. We envision a scientific landscape where collaboration, transparency, and inclusivity aren't just ideals but are deeply integrated into research methodologies''.”

They share that the way forward is to prioritize

“''1)Education & Training: Equip researchers, especially the younger generation, with the necessary tools and knowledge to ensure reproducibility.''

''2)Open Science: Promote Open Access publications, making research universally accessible and subject to broader scrutiny.''

''3)Interdisciplinary Collaborations: Foster collaborations across disciplines, pooling expertise and resources to tackle complex research challenges.''

''4)Technological Integration: Leverage technology, especially AI and data analytics, to aid in ensuring research consistency and integrity.''

''If we could change one thing, it would be the isolated nature of scientific endeavors prevalent in many regions, like Georgia. We would foster a globally interconnected research network where findings, methodologies, and tools are shared seamlessly, accelerating scientific progress and ensuring its robustness''”.

Lastly, the Georgian consortium highlights what they would change in the global reproducibility landscape if they could: “''1)Revise Academic Incentives: The current "publish or perish" culture sometimes prioritizes quantity over quality. We'd advocate for a system where researchers are rewarded for the reproducibility and integrity of their work, not just the volume. 2)Enhanced Training: Incorporate reproducibility and Open Science training at early academic stages, ensuring that upcoming researchers are well-equipped with the necessary skills and ethos. 3)Global Collaboration Platforms: Creation of digital platforms that facilitate global collaboration, data sharing, and mutual validation of research findings, breaking down silos and fostering a truly global scientific community''.”

====Serbian Consortium====
[[File:Serbian RN.png|center|thumb]]

<span lang="EN-US">[https://tier2-project.eu/ TIER2] is excited to announce the winner of the 2024 Open Call aimed at fostering the establishment of a third Reproducibility Network (RN) in “Widening Participation” countries - Serbia. The goal of Reproducibility Networks is to promote rigorous research practices, facilitate interdisciplinary collaborations and discussions, and enhance the trustworthiness of scientific work. The Serbian consortium will thus receive a €5,000 grant to organise an initial meeting, laying the groundwork for establishing an RN in their country.</span>

<span lang="EN-US">The Serbian consortium, consisting of nine organisations – six institutes and three faculties –, brings together diverse academic backgrounds with a shared commitment to improving research culture in Serbia. They focus on integrating Open Science, reproducibility, and inclusive policies into institutions and education. The consortium has previously collaborated on initiatives like the [https://nitra.gov.rs/en/ Team for Open Science in Serbia] and [https://nitra.gov.rs/en/inovacije/projekat-saige the Saige project], organising workshops and training to promote open science practices.</span>

<span lang="EN-US">Motivated by challenges such as low research investment and a scientific system that prioritises quantity over quality, they believe establishing a Reproducibility Network will enhance collaboration and help to address these issues. In the short term, they plan to promote the network through conferences, a kick-off event, and online platforms. Long-term, they aim to integrate Open Science into curricula, incentivise reproducibility, support initiatives beyond major centers, advocate for policy changes, and build international collaborations.</span>

<span lang="EN-US">Their vision for global reproducibility is one where research is transparent, ethical, and rigorous:</span>

<span lang="EN-US">''“In this ideal state, researchers across all disciplines adhere to principles of Open Science, ensuring that their methods, data, and results are accessible and reproducible.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

<span lang="EN-US">They advocate for integrating these principles into education, establishing incentive systems, and fostering collaboration:</span>

<span lang="EN-US">''“We should integrate reproducibility and Open Science practices into university curricula and professional development programs to equip researchers with the necessary skills and knowledge to conduct reproducible research.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

=== Resources to set up a Reproducibility Network ===

* [https://osf.io/ndwsj Application template]
* [https://osf.io/tsmxh Reviewer guidelines]

==='''<span lang="EN-GB">Call to action – what could you do?</span>'''===
<div>
*'''<span lang="EN-GB">Are you a researcher?</span>''' <span lang="EN-GB">Join an existing RN in your country or, if none exist, identify supporters and form your own network.</span>
</div><div>
*'''<span lang="EN-GB">Are you a funder?</span>''' <span lang="EN-GB">Offer your support by providing (additional) funding for personnel costs, events on reproducibility practices and Open Science, or training opportunities. Further, establish your own award calls to support the establishment of more RNs.</span>
</div><div>
*'''<span lang="EN-GB">Are you a publisher?</span>''' <span lang="EN-GB">Support the wide range of outputs generated by RNs, for example via special issues or journals, to help them increase their reach.</span>
</div>

===Not sure, if your country has an established Reproducibility Network?===

<span lang="EN-GB">Visit the Global Networks page hosted by the UKRN to find out if a Reproducibility Network already exists in your country: https://www.ukrn.org/global-networks/.</span> <div></div>
}}
{{Instruction Step Trainee
|Instruction Step Title=Stakeholder communities
|Instruction Step Text====Why build communities and engage stakeholders?===
<div>
<span lang="EN-GB">TIER2 actively engages with researchers from different research areas (social, life, and computer sciences) and two cross-disciplinary stakeholder groups (funders and publishers) to enhance reproducibility across contexts.</span>
</div><div>
<span lang="EN-GB">Through our co-creation and engagement activities, we are actively fostering communication within and across stakeholder groups creating communities of practices. Opportunities for knowledge exchange and sharing of perspectives further enhances our TIER2 community building efforts</span>
</div><div>
<span lang="EN-GB">We are emphasizing our stakeholder engagement and collaboration especially during the selection, prioritization, development, implementation, and evaluation phases of our new reproducibility-related tools and practices, designed within out eight pilot activities. Through co-creation activities, we explore opportunities for closer collaboration within and across stakeholder communities and facilitate the sharing of resources and expertise. By fostering a sense of ownership and involvement, we ensure that the new tools and practices, created within the project, are valuable and useful to the communities as well as beneficial to all parties involved.</span>

</div>

===<span lang="EN-US">Resources to plan and conduct open and inclusive co-creation activities:</span>===

*[https://osf.io/7zpyd/files/hyf9z Types of co-creation events]
*[https://osf.io/7zpyd/files/sy3za DEIA resources for virtual co-creation events]

[[File:TIER2 Stakeholder Communities.jpg|thumb|Infographic illustrating the stakeholder communities and the activities they are involved with within TIER2.]]
[[File:WCRI Co-creation Poster.jpg|thumb|Strategies for fostering research integrity through community co-creation. ]]
}}
{{Instruction Step Trainee
|Instruction Step Title=Primers Inititative
|Instruction Step Text=<span lang="EN-US">The primer initiative from the United Kingdom Reproducibility Network was designed introduce a broad audience to important topics and aspects of open and reproducible scholarship. Each primer is a 3-to-4-page summary document which describes the open or reproducible research practice, why one might be interested in it, and how they can be applied or adopted with thorough guidance.</span>

More information on the Primers Initative can be found here: <u>[https://www.ukrn.org/primers/ <span lang="EN-US">https://www.ukrn.org/primers/</span>]</u> .
}}
{{Instruction Step Trainee
|Instruction Step Title=Consortia Partners
|Instruction Step Text=<span lang="EN-US">TIER2 brings a unique combination of skills and perspectives, consisting of eleven partners from seven countries, well spread across Europe. The partner organisations all bring a wealth of expertise and experience regarding the target communities (computer science, life science, social science), research culture reform, technical aspects of infrastructure and services, as well as expertise in social sciences and humanities, and gender aspects of R&I. </span>

==[https://irise-project.eu/ iRise]==
[[File:IRISE .png|thumb]]
iRise aims to deepen understanding of reproducibility drivers, evaluate their effectiveness and provide concrete solutions to enhance scientific evidence.

Their direct objectives are:

- Develop working definitions and a general framework for diagnosing and addressing reproducibility problems, define costs, benefits and opportunities, and assess the utility of theoretical evidence in forecasting the success of interventions.

- Perform scoping and systematic reviews to identify and evaluate existing interventions to improve reproducibility.

- Explore the interface between reproducibility and research culture, and in particular considerations and mainstreaming of equity, diversity, and inclusion (EDI).

- Consult and engage key stakeholder groups in prioritising practices and practical tool development for adoption to increase reproducibility.

- Test efficacy and feasibility of specific interventions to increase reproducibility.

==[https://osiris4r.eu/ OSIRIS]==
[[File:OSIRIS .png|thumb]]
Open Science to Increase Reproducibility in Science (OSIRIS) aims to facilitate the shift by systematically gathering knowledge on the underlying drivers, testing effective evidence-based solutions, identifying incentives for reproducibility by stakeholders, and embedding reproducibility in research design.
}}
{{Instruction Remarks Trainee}}
{{Custom TabContent Close Trainee}}
{{Custom TabContent Trainer Open}}
{{Instruction Steps Foldout Trainer}}
{{Instruction Perspective Trainer}}
{{Instruction Remarks Trainer}}
{{Custom TabContent Close Trainer}}
{{Related To}}
{{Tags}}

Instruction:7c159fc9-db27-4623-9432-9c37b8889f89

2025-10-22T11:39:03Z

0009-0002-1788-6517:

{{Instruction
|Title=Communities and collaborators
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=On this page we present the TIER2 Reproducibility Network Award, the stakeholder community building activities and efforts of TIER2, our consortia partners (iRise and OSIRIS), and finally the UKRN Primers initative.
|Has Duration=1
|Important For=All stakeholders in research
}}
{{Custom TabContent Trainee Open}}
{{Instruction Steps Foldout Trainee}}
{{Instruction Perspective Trainee}}
{{Instruction Step Trainee
|Instruction Step Title=Reproducibility Network Award
|Instruction Step Text=<div>
==='''<span lang="EN-GB">What is a Reproducibility Network?</span>''' ===
</div><div><div>
<span lang="EN-GB">A national Reproducibility Network <u>(RN)</u> is a countrywide peer-led consortium that aims to improve research practices by promoting, supporting, and investigating factors contributing to robust research including, but not limited to, reproducibility, replicability, and Open Science. Activities may include promoting training activities, disseminating best practices, supporting research on reproducible research practices, and advocacy for reproducible and open research. </span>
</div><div>
<span lang="EN-GB">An RN typically serves as a hub to connect researchers to exchange ideas and good practices, promoting collaboration among researchers from a range of scientific disciplines. These networks provide infrastructure, facilitate opportunities for researchers and initiatives to support and amplify each other’s efforts, and foster community building as well as shared problem solving. </span>
</div><div>
<span lang="EN-GB">RNs can serve as connectors to other stakeholder groups such as universities, funders, or academic publishers.</span>
</div></div>

===Benefits for setting up an Reproducibility Network?===

<span lang="EN-GB">By providing seed funding for the establishment of a new RN, you actively contribute to the strengthening of reproducibility and Open Science in your local ecosystem. The widespread presence of RNs is crucial, as they function as points of contact for scientific communities who, across e.g., disciplinary, demographic, and geographic contexts, face different challenges and barriers. RNs can provide local and tailored support and keep in mind the different stages of readiness of their local communities for implementing reproducible research practices.</span>

==="Lessons learned" from the TIER2 award===
1. '''<span lang="EN-GB">Build strong community links.</span>''' <span lang="EN-GB">Involve already existing and successful RNs in the establishment of new RNs. This ensures that new RNs receive valuable guidance, input and support early in the establishment process.</span>

2. '''<span lang="EN-GB">Expand connections and broaden the reach.</span>''' <span lang="EN-GB">Reach out to researchers and other relevant stakeholders, such as universities, as this is important for local support and the sustainability of the RN. However, identifying and connecting with researchers in Horizon Europe Widening Participation countries (WIDERA countries) who are active in reproducible research and Open Science practices can be challenging.</span>

3. '''<span lang="EN-GB">Facilitate international support.</span>''' <span lang="EN-GB">Several RNs across the globe exist and more are being established. Build strong international connections amongst them to facilitate the sharing of resources and best practices, this will help to coordinate and amplify efforts.</span>

4. '''<span lang="EN-GB">Focus on the local ecosystem.</span>''' <span lang="EN-GB">RNs are national networks that promote transparent and trustworthy practices in their local research ecosystems. Recognize local needs, geopolitical conditions as well as barriers and available resources.</span>

===How has TIER2 supported the awarded networks?===

1. TIER2 members and award organizers have facilitated connections between awardees and existing international Reproducibility and Open Science networks. via email contacts as well as through virtual and in-person meetings.

2. <span lang="EN-GB">TIER2 award organizers, have added awardees, with their consent, to various mailing lists and newsletters from different international RNs.</span>

3.<span lang="EN-GB">Further, TIER2 award organizers have invited awardees to attend and speak at several Open Science and reproducibility events to meet (steering group) members from other RNs and (inter-)national initiatives.</span>

<span lang="EN-GB">4. TIER2 project members as well as award organizers have provided the awardees with resources and information on relevant topics, including different RN structures, website layout and structure, as well as language.</span>

===Awardess of the TIER2 Reproducibility Network Award===

TIER2 is proud to announce the two awarded consortia based in Ukraine and Georgia who will receive the monetary awards from the Reproducibility Network open call this summer. Multiple scientific consortia from Horizon Europe “[https://www.era-learn.eu/support-for-partnerships/additional-activities/openness-inclusivness-transparency/widening-and-inclusiveness Widening Participation]” countries submitted applications describing their plans and motivations for establishing a Reproducibility Network in their home country which TIER2 would support with a €5000 prize.

[[File:Ukraine and Georgia RN.png|center|thumb]]

====Ukrainian Consortium====
The Ukrainian consortium, from the Institute for Open Science and Innovation ([https://www.facebook.com/inosi.org/ INOSI]), [https://twitter.com/optima_open OPTIMA] Project Consortium & [https://lpnu.ua/en Lviv Polytechnic National University], comprises researchers with a broad scientific background, ranging from informatics to chemistry and ecology. The core of the consortium has already experience working together in promoting Open Science in Ukraine, particularly within the OPTIMA project and within the Working Group on the [https://www.kmu.gov.ua/en/news/ukraina-pryiednalas-do-krain-ies-shcho-maiut-zatverdzhenyi-plan-realizatsii-pryntsypiv-vidkrytoi-nauky National Plan for Open Science development] in Ukraine. In response to what motivated them in participating in the open call, they state that: ''“Ukraine needs good science to make good decisions in all spheres. This is particularly relevant during the war and will be needed for the post-war recovery. Reproducibility (as a part of the Open Science concept) can boost the value of academic research in Ukraine making science a real game-changer for progress''”. Regarding their future plans for the Ukrainian Reproducibility Network, they share: “''In the short term, the ambition is to kickstart the network of experts, able to lead the discussion on reproducibility and become a role model on the national level. In the long term, the ambition is, of course, to make reproducibility in research a standard by default. This has to be supported by co-creation and sharing best practices, research on research, and making an impact on national policy. We hope that the network will be viable and ambitious enough to compete for international grant funding to achieve this''”. With regard to the global state of reproducibility & scientific integrity, they say: “''The progress on the global level is visible, but it's only the beginning of a long way forward. The key to achieving the goal is a strong research culture that is often missing in many academic communities. Openness and transparency in performing and communicating research are the basic things to be established''.”

====Georgian Consortium====
The consortium from Georgia, comprises three researchers from different institutions: the Department of Human Anatomy at Tbilisi State Medical University ([https://tsmu.edu/ts/home TSMU]), the Faculty of Medicine at Tbilisi State University ([https://www.tsu.ge/en TSU]), the Institute of Morphology, and the Scientific Department at Caucasus International University ([https://ciu.edu.ge/?lang=en CIU]). Brought together as team members of a research group, they were drafting a proposal for a Horizon Europe (HE) project when their HE grant coordinator alerted them about the TIER2 open call announcement. The team was immediately drawn to it, sharing that:

“''During our individual and collective research endeavors, we frequently encountered challenges in reproducing experiment results, a phenomenon that was not isolated to our work but across the global research landscape. [...] a consolidated effort was needed to elevate the state of research in our nation. [...] Moreover, the opportunity to foster a Reproducibility Network (RN) in Georgia provided a platform to unite our nation's fragmented research endeavors, drive standards in research methodologies, and integrate with the global scientific community''”. Regarding their short-term plans after receiving the award, they list the following: “''Organize the foundational meeting, bringing together stakeholders from various Georgian research institutions, to lay down the operational blueprint for the RN; Launch training sessions that cover core skills in reproducibility, data management, and research design; Conduct sessions in universities and community centers to educate and foster trust in scientific research: Set up an official RN website and leverage social media for real-time updates and engagements”. In the long term, the team envisions to “Establish partnerships with International Reproducibility Networks, facilitating knowledge exchange and joint research projects and collaborate with Georgian institutions to advocate for policies emphasizing reproducibility and transparency''”. Their global vision for the state of reproducibility and scientific integrity “''is one where every piece of research, irrespective of its domain or geography, stands the test of time and validation. We envision a scientific landscape where collaboration, transparency, and inclusivity aren't just ideals but are deeply integrated into research methodologies''.”

They share that the way forward is to prioritize

“''1)Education & Training: Equip researchers, especially the younger generation, with the necessary tools and knowledge to ensure reproducibility.''

''2)Open Science: Promote Open Access publications, making research universally accessible and subject to broader scrutiny.''

''3)Interdisciplinary Collaborations: Foster collaborations across disciplines, pooling expertise and resources to tackle complex research challenges.''

''4)Technological Integration: Leverage technology, especially AI and data analytics, to aid in ensuring research consistency and integrity.''

''If we could change one thing, it would be the isolated nature of scientific endeavors prevalent in many regions, like Georgia. We would foster a globally interconnected research network where findings, methodologies, and tools are shared seamlessly, accelerating scientific progress and ensuring its robustness''”.

Lastly, the Georgian consortium highlights what they would change in the global reproducibility landscape if they could: “''1)Revise Academic Incentives: The current "publish or perish" culture sometimes prioritizes quantity over quality. We'd advocate for a system where researchers are rewarded for the reproducibility and integrity of their work, not just the volume. 2)Enhanced Training: Incorporate reproducibility and Open Science training at early academic stages, ensuring that upcoming researchers are well-equipped with the necessary skills and ethos. 3)Global Collaboration Platforms: Creation of digital platforms that facilitate global collaboration, data sharing, and mutual validation of research findings, breaking down silos and fostering a truly global scientific community''.”

====Serbian Consortium====
[[File:Serbian RN.png|center|thumb]]

<span lang="EN-US">[https://tier2-project.eu/ TIER2] is excited to announce the winner of the 2024 Open Call aimed at fostering the establishment of a third Reproducibility Network (RN) in “Widening Participation” countries - Serbia. The goal of Reproducibility Networks is to promote rigorous research practices, facilitate interdisciplinary collaborations and discussions, and enhance the trustworthiness of scientific work. The Serbian consortium will thus receive a €5,000 grant to organise an initial meeting, laying the groundwork for establishing an RN in their country.</span>

<span lang="EN-US">The Serbian consortium, consisting of nine organisations – six institutes and three faculties –, brings together diverse academic backgrounds with a shared commitment to improving research culture in Serbia. They focus on integrating Open Science, reproducibility, and inclusive policies into institutions and education. The consortium has previously collaborated on initiatives like the [https://nitra.gov.rs/en/ Team for Open Science in Serbia] and [https://nitra.gov.rs/en/inovacije/projekat-saige the Saige project], organising workshops and training to promote open science practices.</span>

<span lang="EN-US">Motivated by challenges such as low research investment and a scientific system that prioritises quantity over quality, they believe establishing a Reproducibility Network will enhance collaboration and help to address these issues. In the short term, they plan to promote the network through conferences, a kick-off event, and online platforms. Long-term, they aim to integrate Open Science into curricula, incentivise reproducibility, support initiatives beyond major centers, advocate for policy changes, and build international collaborations.</span>

<span lang="EN-US">Their vision for global reproducibility is one where research is transparent, ethical, and rigorous:</span>

<span lang="EN-US">''“In this ideal state, researchers across all disciplines adhere to principles of Open Science, ensuring that their methods, data, and results are accessible and reproducible.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

<span lang="EN-US">They advocate for integrating these principles into education, establishing incentive systems, and fostering collaboration:</span>

<span lang="EN-US">''“We should integrate reproducibility and Open Science practices into university curricula and professional development programs to equip researchers with the necessary skills and knowledge to conduct reproducible research.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

=== Resources to set up a Reproducibility Network ===

* [https://osf.io/ndwsj Application template]
* [https://osf.io/tsmxh Reviewer guidelines]

==='''<span lang="EN-GB">Call to action – what could you do?</span>'''===
<div>
*'''<span lang="EN-GB">Are you a researcher?</span>''' <span lang="EN-GB">Join an existing RN in your country or, if none exist, identify supporters and form your own network.</span>
</div><div>
*'''<span lang="EN-GB">Are you a funder?</span>''' <span lang="EN-GB">Offer your support by providing (additional) funding for personnel costs, events on reproducibility practices and Open Science, or training opportunities. Further, establish your own award calls to support the establishment of more RNs.</span>
</div><div>
*'''<span lang="EN-GB">Are you a publisher?</span>''' <span lang="EN-GB">Support the wide range of outputs generated by RNs, for example via special issues or journals, to help them increase their reach.</span>
</div>

===Not sure, if your country has an established Reproducibility Network?===

<span lang="EN-GB">Visit the Global Networks page hosted by the UKRN to find out if a Reproducibility Network already exists in your country: https://www.ukrn.org/global-networks/.</span> <div></div>
}}
{{Instruction Step Trainee
|Instruction Step Title=Stakeholder communities
|Instruction Step Text===Why build communities and engage stakeholders?==
<div>
<span lang="EN-GB">TIER2 actively engages with researchers from different research areas (social, life, and computer sciences) and two cross-disciplinary stakeholder groups (funders and publishers) to enhance reproducibility across contexts.</span>
</div><div>
<span lang="EN-GB">Through our co-creation and engagement activities, we are actively fostering communication within and across stakeholder groups creating communities of practices. Opportunities for knowledge exchange and sharing of perspectives further enhances our TIER2 community building efforts</span>
</div><div>
<span lang="EN-GB">We are emphasizing our stakeholder engagement and collaboration especially during the selection, prioritization, development, implementation, and evaluation phases of our new reproducibility-related tools and practices, designed within out eight pilot activities. Through co-creation activities, we explore opportunities for closer collaboration within and across stakeholder communities and facilitate the sharing of resources and expertise. By fostering a sense of ownership and involvement, we ensure that the new tools and practices, created within the project, are valuable and useful to the communities as well as beneficial to all parties involved.</span>

[[:File:TIER2 Stakeholder Communities.jpg|TIER2 Stakeholder Communities.jpg]]
</div>

=== <span lang="EN-US">Resources to plan and conduct open and inclusive co-creation activities:</span> ===

* [https://osf.io/7zpyd/files/hyf9z Types of co-creation events]
* [https://osf.io/7zpyd/files/sy3za DEIA resources for virtual co-creation events]

[[File:TIER2 Stakeholder Communities.jpg|thumb|Infographic illustrating the stakeholder communities and the activities they are involved with within TIER2.]]
[[File:WCRI Co-creation Poster.jpg|thumb|Strategies for fostering research integrity through community co-creation. ]]
}}
{{Instruction Step Trainee
|Instruction Step Title=Primers Inititative
|Instruction Step Text=<span lang="EN-US">The primer initiative from the United Kingdom Reproducibility Network was designed introduce a broad audience to important topics and aspects of open and reproducible scholarship. Each primer is a 3-to-4-page summary document which describes the open or reproducible research practice, why one might be interested in it, and how they can be applied or adopted with thorough guidance.</span>

More information on the Primers Initative can be found here: <u>[https://www.ukrn.org/primers/ <span lang="EN-US">https://www.ukrn.org/primers/</span>]</u> .
}}
{{Instruction Step Trainee
|Instruction Step Title=Consortia Partners
|Instruction Step Text=<span lang="EN-US">TIER2 brings a unique combination of skills and perspectives, consisting of eleven partners from seven countries, well spread across Europe. The partner organisations all bring a wealth of expertise and experience regarding the target communities (computer science, life science, social science), research culture reform, technical aspects of infrastructure and services, as well as expertise in social sciences and humanities, and gender aspects of R&I. </span>

==[https://irise-project.eu/ iRise]==
[[File:IRISE .png|thumb]]
iRise aims to deepen understanding of reproducibility drivers, evaluate their effectiveness and provide concrete solutions to enhance scientific evidence.

Their direct objectives are:

- Develop working definitions and a general framework for diagnosing and addressing reproducibility problems, define costs, benefits and opportunities, and assess the utility of theoretical evidence in forecasting the success of interventions.

- Perform scoping and systematic reviews to identify and evaluate existing interventions to improve reproducibility.

- Explore the interface between reproducibility and research culture, and in particular considerations and mainstreaming of equity, diversity, and inclusion (EDI).

- Consult and engage key stakeholder groups in prioritising practices and practical tool development for adoption to increase reproducibility.

- Test efficacy and feasibility of specific interventions to increase reproducibility.

==[https://osiris4r.eu/ OSIRIS]==
[[File:OSIRIS .png|thumb]]
Open Science to Increase Reproducibility in Science (OSIRIS) aims to facilitate the shift by systematically gathering knowledge on the underlying drivers, testing effective evidence-based solutions, identifying incentives for reproducibility by stakeholders, and embedding reproducibility in research design.
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File:WCRI Co-creation Poster.jpg

2025-10-22T11:38:09Z

0009-0002-1788-6517:

Strategies for fostering research integrity through community co-creation.

Instruction:4bc3edc0-d493-4f35-a742-e4cee5569562

2025-10-21T12:19:30Z

0009-0002-1788-6517:

{{Instruction
|Title=New Tools and Services for Reproducibility
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=TIER2 aims to better understand the causes, consequences and possible solutions of perceived poor levels of reproductivity of research across research contexts. With a focus on social, life, and computer sciences, as well as research publishers and funders, the project aims to increase awareness, build capacity, and propose innovative solutions sensitive to varied research cultures. Central to its approach are eight Pilot activities designed to develop, implement, and evaluate new reproducibility-related tools and practices.
|Has Duration=1
|Important For=All stakeholders in research
}}
{{Custom TabContent Trainee Open}}
{{Instruction Steps Foldout Trainee}}
{{Instruction Perspective Trainee}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 1 - Decision Aid
|Instruction Step Text=<span lang="EN-US">TIER2's Decision Aid provides clarity on the meaning, relevance, and feasibility of ‘reproducibility’ for researchers to aid them in identifying what type of reproducibility is relevant for their research and indicate what they must consider regarding how feasible such ‘reproducibility’ would be for them.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 2 - Reproducibility Management Plan (RMP)
|Instruction Step Text=<span lang="EN-US">The [https://osf.io/pn27g Reproducibility Management Plan (RMP) Pilot] aims to create a prototype of key thematic subjects and questions that will serve as the starting point to support reproducibility at the planning stage of research. Work involves defining what an RMP is, integrating it into the ARGOS service, and testing its effectiveness with feedback from the community. The pilot addresses researchers, beneficiaries and funders for its adoption.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 3 - Reproducible Workflows
|Instruction Step Text=<span lang="EN-US">In this pilot, [https://schema-lab.hypatia-comp.athenarc.gr/ SCHEMA] was developed as an open-source framework, comprising SCHEMA api for programmatic execution and SCHEMA lab for a user-friendly web interface to support reproducible computational research through containerized execution, metadata capturing and experiment management. It provides a scalable environment that enables researchers to design and run reproducible computational workflows and experiments.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 4 - The Reproducibility Checklist
|Instruction Step Text=<span lang="EN-US"><span lang="EN-GB">The <span lang="DE">[https://eur04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FGESIS-Methods-Hub%2Fguidelines-for-methods%2Fblob%2Fmain%2FREADME-template.md&data=05%7C02%7Cb.leitner%40amsterdamumc.nl%7C98306bdc1d14436a474308de062e488a%7C68dfab1a11bb4cc6beb528d756984fb6%7C0%7C0%7C638954993173754302%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=8wKJxWZb4qfVKLG%2F%2Bgn4HWuQCxrkIvrUyENg%2FEEwiWM%3D&reserved=0 Reproducibility Checklist for Computational Social Science Research]</span> provides a simple, structured framework to enhance the reproducibility of computational methods shared on [https://eur04.safelinks.protection.outlook.com/?url=http%3A%2F%2Fmethodshub.gesis.org%2F&data=05%7C02%7Cb.leitner%40amsterdamumc.nl%7C98306bdc1d14436a474308de062e488a%7C68dfab1a11bb4cc6beb528d756984fb6%7C0%7C0%7C638954993173788095%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=fZvqBgWjUcBuH%2FNJKGAl8WYPcNRsRQujUc8k%2FbPcG3Q%3D&reserved=0 Methods Hub]. Designed for minimal effort and maximum usability, the checklist helps researchers document and share their data and code in a consistent, verifiable way that fosters trust and collaboration within the social science community. This pilot contributes to more efficient, transparent, and reproducible computational social science by integrating practical usability with clear documentation standards.</span></span>

<span lang="EN-US">The [https://github.com/GESIS-Methods-Hub/guidelines-for-methods/blob/main/README-template.md <u>checklist tempelate</u>] is publicly available through GitHub [https://github.com/GESIS-Methods-Hub/guidelines-for-methods <u>project repositoriy</u>] and is accompanied by [https://github.com/GESIS-Methods-Hub/guidelines-for-methods/blob/main/guidelines.md <u>user guidance</u>] for researchers who want to submit a method. These resources explain how to apply the checklist in practice, both independently and in connection with [https://methodshub.gesis.org/ <u>Methods Hub</u>].</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 5 - The Reproducibility Promotion Plan for Funders (RPP)
|Instruction Step Text=<span lang="EN-US">The Reproducibility Promotion Plan for Funders (RPP) has developed a policy template with recommendations for funders to foster reproducible practices both in the research they fund across three key areas of funding work: evaluation and monitoring, policy and definitions, and incentives. The RPP provides actionable recommendations and best practice examples that funders and funding institutions can adapt to meet their specific needs.</span>

All drafts of the RPP can be found on [https://osf.io/3fpbj/ OSF].

[[File:RPP4F One Pager.jpg|center|thumb]]
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 6 - The Reproducibility Monitoring Dashboard
|Instruction Step Text=<span lang="EN-US">The Reproducibility Monitoring Dashboard hosts tools that enable funding agencies to track and monitor the reusability of research artifacts across various projects, programs, topics, and disciplines. This auto-generated dashboard assesses the impacts of policies related to data and code sharing.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 7 - Editorial Workflows to Increase Data Sharing
|Instruction Step Text=<span lang="EN-GB">A key aspect of (computational) reproducibility is availability of data. However, sharing of research data is still not the norm across disciplines. Developed co-creatively with stakeholders from major publishers, the workflow and email template provide a low-effort approach for publishers to nudge researchers towards sharing their data for journals operating under a “share upon request” policy. Documentation on the workflow and email template can be found in [https://doi.org/10.17605/OSF.IO/S7GJV TIER2 D5.2].</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 8- An Editorial Reference Handbook for Reproducibility and FAIRness
|Instruction Step Text=<div>
<span lang="EN-US">The [https://publishers.fairassist.org/ <u>Editorial Reference Handbook</u>] informs and assists journals to operationalise a set of checks necessary to make the data underlying published research findings more findable, accessible, interoperable and reusable (FAIR) to underpin reproducibility. The Handbook targets in-house staff managing the manuscripts primarily, but it will also benefit reviewers, authors and even those providing services to publishers by making the fundamental checks and requirements transparent and understandable.</span>
</div><div>
<span lang="EN-US">The Handbook includes three interlinked components: a checklist of 12 elements, a flowchart that outlines the ideal internal manuscript submission workflow (who should perform the checks and when), and a guidance to help users to implement the checks effectively, with definitions and tips.</span>
</div><div>
<span lang="EN-US">The Handbook fills a gap, because no common guidance existed on the practical implementation of these checks across a complex publishing workflow and the variety of individuals and teams involved. This pilot saw the participation of more than 30 individuals, from more than 20 journals of major publishers: CUP, Cell Press, EMBO Press, Taylor & Francis, GigaScience Press, OUP, PLOS, Springer Nature.</span>
</div>
}}
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Instruction:4bc3edc0-d493-4f35-a742-e4cee5569562

2025-10-16T07:47:01Z

0009-0002-1788-6517:

{{Instruction
|Title=New Tools and Services for Reproducibility
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=TIER2 aims to better understand the causes, consequences and possible solutions of perceived poor levels of reproductivity of research across research contexts. With a focus on social, life, and computer sciences, as well as research publishers and funders, the project aims to increase awareness, build capacity, and propose innovative solutions sensitive to varied research cultures. Central to its approach are eight Pilot activities designed to develop, implement, and evaluate new reproducibility-related tools and practices.
|Has Duration=1
|Important For=All stakeholders in research
}}
{{Custom TabContent Trainee Open}}
{{Instruction Steps Foldout Trainee}}
{{Instruction Perspective Trainee}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 1 - Decision Aid
|Instruction Step Text=<span lang="EN-US">TIER2's Decision Aid provides clarity on the meaning, relevance, and feasibility of ‘reproducibility’ for researchers to aid them in identifying what type of reproducibility is relevant for their research and indicate what they must consider regarding how feasible such ‘reproducibility’ would be for them.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 2 - Reproducibility Management Plan (RMP)
|Instruction Step Text=<span lang="EN-US">The [https://osf.io/pn27g Reproducibility Management Plan (RMP) Pilot] aims to create a prototype of key thematic subjects and questions that will serve as the starting point to support reproducibility at the planning stage of research. Work involves defining what an RMP is, integrating it into the ARGOS service, and testing its effectiveness with feedback from the community. The pilot addresses researchers, beneficiaries and funders for its adoption.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 3 - Reproducible Workflows
|Instruction Step Text=<span lang="EN-US">Reproducible Workflows has adapted the SCHEMA open-source platform for reproducible workflows in life and computer sciences by leveraging software containerisation, workflow description languages (CWL, Snakemake), and experiment packaging specifications (RO-crate), particularly emphasising machine learning in computer science.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 4 - The Reproducibility Checklist
|Instruction Step Text=<span lang="EN-US"><span lang="EN-GB">The <span lang="DE">[https://eur04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FGESIS-Methods-Hub%2Fguidelines-for-methods%2Fblob%2Fmain%2FREADME-template.md&data=05%7C02%7Cb.leitner%40amsterdamumc.nl%7C98306bdc1d14436a474308de062e488a%7C68dfab1a11bb4cc6beb528d756984fb6%7C0%7C0%7C638954993173754302%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=8wKJxWZb4qfVKLG%2F%2Bgn4HWuQCxrkIvrUyENg%2FEEwiWM%3D&reserved=0 Reproducibility Checklist for Computational Social Science Research]</span> provides a simple, structured framework to enhance the reproducibility of computational methods shared on [https://eur04.safelinks.protection.outlook.com/?url=http%3A%2F%2Fmethodshub.gesis.org%2F&data=05%7C02%7Cb.leitner%40amsterdamumc.nl%7C98306bdc1d14436a474308de062e488a%7C68dfab1a11bb4cc6beb528d756984fb6%7C0%7C0%7C638954993173788095%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=fZvqBgWjUcBuH%2FNJKGAl8WYPcNRsRQujUc8k%2FbPcG3Q%3D&reserved=0 Methods Hub]. Designed for minimal effort and maximum usability, the checklist helps researchers document and share their data and code in a consistent, verifiable way that fosters trust and collaboration within the social science community. This pilot contributes to more efficient, transparent, and reproducible computational social science by integrating practical usability with clear documentation standards.</span></span>

<span lang="EN-US">The [https://github.com/GESIS-Methods-Hub/guidelines-for-methods/blob/main/README-template.md <u>checklist tempelate</u>] is publicly available through GitHub [https://github.com/GESIS-Methods-Hub/guidelines-for-methods <u>project repositoriy</u>] and is accompanied by [https://github.com/GESIS-Methods-Hub/guidelines-for-methods/blob/main/guidelines.md <u>user guidance</u>] for researchers who want to submit a method. These resources explain how to apply the checklist in practice, both independently and in connection with [https://methodshub.gesis.org/ <u>Methods Hub</u>].</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 5 - The Reproducibility Promotion Plan for Funders (RPP)
|Instruction Step Text=<span lang="EN-US">The Reproducibility Promotion Plan for Funders (RPP) has developed a policy template with recommendations for funders to foster reproducible practices both in the research they fund across three key areas of funding work: evaluation and monitoring, policy and definitions, and incentives. The RPP provides actionable recommendations and best practice examples that funders and funding institutions can adapt to meet their specific needs.</span>

All drafts of the RPP can be found on [https://osf.io/3fpbj/ OSF].

[[File:RPP4F One Pager.jpg|center|thumb]]
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 6 - The Reproducibility Monitoring Dashboard
|Instruction Step Text=<span lang="EN-US">The Reproducibility Monitoring Dashboard hosts tools that enable funding agencies to track and monitor the reusability of research artifacts across various projects, programs, topics, and disciplines. This auto-generated dashboard assesses the impacts of policies related to data and code sharing.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 7 - Editorial Workflows to Increase Data Sharing
|Instruction Step Text=<span lang="EN-GB">A key aspect of (computational) reproducibility is availability of data. However, sharing of research data is still not the norm across disciplines. Developed co-creatively with stakeholders from major publishers, the workflow and email template provide a low-effort approach for publishers to nudge researchers towards sharing their data for journals operating under a “share upon request” policy. Documentation on the workflow and email template can be found in [https://doi.org/10.17605/OSF.IO/S7GJV TIER2 D5.2].</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 8- An Editorial Reference Handbook for Reproducibility and FAIRness
|Instruction Step Text=<div>
<span lang="EN-US">The [https://publishers.fairassist.org/ <u>Editorial Reference Handbook</u>] informs and assists journals to operationalise a set of checks necessary to make the data underlying published research findings more findable, accessible, interoperable and reusable (FAIR) to underpin reproducibility. The Handbook targets in-house staff managing the manuscripts primarily, but it will also benefit reviewers, authors and even those providing services to publishers by making the fundamental checks and requirements transparent and understandable.</span>
</div><div>
<span lang="EN-US">The Handbook includes three interlinked components: a checklist of 12 elements, a flowchart that outlines the ideal internal manuscript submission workflow (who should perform the checks and when), and a guidance to help users to implement the checks effectively, with definitions and tips.</span>
</div><div>
<span lang="EN-US">The Handbook fills a gap, because no common guidance existed on the practical implementation of these checks across a complex publishing workflow and the variety of individuals and teams involved. This pilot saw the participation of more than 30 individuals, from more than 20 journals of major publishers: CUP, Cell Press, EMBO Press, Taylor & Francis, GigaScience Press, OUP, PLOS, Springer Nature.</span>
</div>
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Instruction:4bc3edc0-d493-4f35-a742-e4cee5569562

2025-10-13T11:09:45Z

0009-0002-1788-6517:

{{Instruction
|Title=New Tools and Services for Reproducibility
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=TIER2 aims to better understand the causes, consequences and possible solutions of perceived poor levels of reproductivity of research across research contexts. With a focus on social, life, and computer sciences, as well as research publishers and funders, the project aims to increase awareness, build capacity, and propose innovative solutions sensitive to varied research cultures. Central to its approach are eight Pilot activities designed to develop, implement, and evaluate new reproducibility-related tools and practices.
|Has Duration=1
|Important For=All stakeholders in research
}}
{{Custom TabContent Trainee Open}}
{{Instruction Steps Foldout Trainee}}
{{Instruction Perspective Trainee}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 1 - Decision Aid
|Instruction Step Text=<span lang="EN-US">TIER2's Decision Aid provides clarity on the meaning, relevance, and feasibility of ‘reproducibility’ for researchers to aid them in identifying what type of reproducibility is relevant for their research and indicate what they must consider regarding how feasible such ‘reproducibility’ would be for them.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 2 - Reproducibility Management Plan (RMP)
|Instruction Step Text=<span lang="EN-US">The [https://osf.io/pn27g Reproducibility Management Plan (RMP) Pilot] aims to create a prototype of key thematic subjects and questions that will serve as the starting point to support reproducibility at the planning stage of research. Work involves defining what an RMP is, integrating it into the ARGOS service, and testing its effectiveness with feedback from the community. The pilot addresses researchers, beneficiaries and funders for its adoption.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 3 - Reproducible Workflows
|Instruction Step Text=<span lang="EN-US">Reproducible Workflows has adapted the SCHEMA open-source platform for reproducible workflows in life and computer sciences by leveraging software containerisation, workflow description languages (CWL, Snakemake), and experiment packaging specifications (RO-crate), particularly emphasising machine learning in computer science.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 4 - The Reproducibility Checklist
|Instruction Step Text=<span lang="EN-US"><span lang="EN-GB">The <span lang="DE">[https://eur04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FGESIS-Methods-Hub%2Fguidelines-for-methods%2Fblob%2Fmain%2FREADME-template.md&data=05%7C02%7Cb.leitner%40amsterdamumc.nl%7C98306bdc1d14436a474308de062e488a%7C68dfab1a11bb4cc6beb528d756984fb6%7C0%7C0%7C638954993173754302%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=8wKJxWZb4qfVKLG%2F%2Bgn4HWuQCxrkIvrUyENg%2FEEwiWM%3D&reserved=0 Reproducibility Checklist for Computational Social Science Research]</span> provides a simple, structured framework to enhance the reproducibility of computational methods shared on [https://eur04.safelinks.protection.outlook.com/?url=http%3A%2F%2Fmethodshub.gesis.org%2F&data=05%7C02%7Cb.leitner%40amsterdamumc.nl%7C98306bdc1d14436a474308de062e488a%7C68dfab1a11bb4cc6beb528d756984fb6%7C0%7C0%7C638954993173788095%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=fZvqBgWjUcBuH%2FNJKGAl8WYPcNRsRQujUc8k%2FbPcG3Q%3D&reserved=0 Methods Hub]. Designed for minimal effort and maximum usability, the checklist helps researchers document and share their data and code in a consistent, verifiable way that fosters trust and collaboration within the social science community. This pilot contributes to more efficient, transparent, and reproducible computational social science by integrating practical usability with clear documentation standards.</span></span>

<span lang="EN-US">The [https://github.com/GESIS-Methods-Hub/guidelines-for-methods/blob/main/README-template.md <u>checklist tempelate</u>] is publicly available through GitHub [https://github.com/GESIS-Methods-Hub/guidelines-for-methods <u>project repositoriy</u>] and is accompanied by [https://github.com/GESIS-Methods-Hub/guidelines-for-methods/blob/main/guidelines.md <u>user guidance</u>] for researchers who want to submit a method. These resources explain how to apply the checklist in practice, both independently and in connection with [https://methodshub.gesis.org/ <u>Methods Hub</u>].</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 5 - The Reproducibility Promotion Plan for Funders (RPP)
|Instruction Step Text=<span lang="EN-US">The Reproducibility Promotion Plan for Funders (RPP) has developed a policy template with recommendations for funders to foster reproducible practices both in the research they fund across three key areas of funding work: evaluation and monitoring, policy and definitions, and incentives. The RPP provides actionable recommendations and best practice examples that funders and funding institutions can adapt to meet their specific needs.</span>

All drafts of the RPP can be found on [https://osf.io/3fpbj/ OSF].

[[File:RPP4F One Pager.jpg|center|thumb]]
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 6 - The Reproducibility Monitoring Dashboard
|Instruction Step Text=<span lang="EN-US">The Reproducibility Monitoring Dashboard hosts tools that enable funding agencies to track and monitor the reusability of research artifacts across various projects, programs, topics, and disciplines. This auto-generated dashboard assesses the impacts of policies related to data and code sharing.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 7 - Editorial Workflows to Increase Data Sharing
|Instruction Step Text=This tool is aimed at increasing data sharing in published work. Data sharing is an important building block for increased reproducibility & transparency, but current rates of sharing are low.
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 8- An Editorial Reference Handbook for Reproducibility and FAIRness
|Instruction Step Text=<div>
<span lang="EN-US">The [https://publishers.fairassist.org/ <u>Editorial Reference Handbook</u>] informs and assists journals to operationalise a set of checks necessary to make the data underlying published research findings more findable, accessible, interoperable and reusable (FAIR) to underpin reproducibility. The Handbook targets in-house staff managing the manuscripts primarily, but it will also benefit reviewers, authors and even those providing services to publishers by making the fundamental checks and requirements transparent and understandable.</span>
</div><div>
<span lang="EN-US">The Handbook includes three interlinked components: a checklist of 12 elements, a flowchart that outlines the ideal internal manuscript submission workflow (who should perform the checks and when), and a guidance to help users to implement the checks effectively, with definitions and tips.</span>
</div><div>
<span lang="EN-US">The Handbook fills a gap, because no common guidance existed on the practical implementation of these checks across a complex publishing workflow and the variety of individuals and teams involved. This pilot saw the participation of more than 30 individuals, from more than 20 journals of major publishers: CUP, Cell Press, EMBO Press, Taylor & Francis, GigaScience Press, OUP, PLOS, Springer Nature.</span>
</div>
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Instruction:4bc3edc0-d493-4f35-a742-e4cee5569562

2025-10-09T07:40:51Z

0009-0002-1788-6517:

{{Instruction
|Title=New Tools and Services for Reproducibility
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=TIER2 aims to better understand the causes, consequences and possible solutions of perceived poor levels of reproductivity of research across research contexts. With a focus on social, life, and computer sciences, as well as research publishers and funders, the project aims to increase awareness, build capacity, and propose innovative solutions sensitive to varied research cultures. Central to its approach are eight Pilot activities designed to develop, implement, and evaluate new reproducibility-related tools and practices.
|Has Duration=1
|Important For=All stakeholders in research
}}
{{Custom TabContent Trainee Open}}
{{Instruction Steps Foldout Trainee}}
{{Instruction Perspective Trainee}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 1 - Decision Aid
|Instruction Step Text=<span lang="EN-US">TIER2's Decision Aid provides clarity on the meaning, relevance, and feasibility of ‘reproducibility’ for researchers to aid them in identifying what type of reproducibility is relevant for their research and indicate what they must consider regarding how feasible such ‘reproducibility’ would be for them.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 2 - Reproducibility Management Plan (RMP)
|Instruction Step Text=<span lang="EN-US">The [https://osf.io/pn27g Reproducibility Management Plan (RMP) Pilot] aims to create a prototype of key thematic subjects and questions that will serve as the starting point to support reproducibility at the planning stage of research. Work involves defining what an RMP is, integrating it into the ARGOS service, and testing its effectiveness with feedback from the community. The pilot addresses researchers, beneficiaries and funders for its adoption.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 3 - Reproducible Workflows
|Instruction Step Text=<span lang="EN-US">Reproducible Workflows has adapted the SCHEMA open-source platform for reproducible workflows in life and computer sciences by leveraging software containerisation, workflow description languages (CWL, Snakemake), and experiment packaging specifications (RO-crate), particularly emphasising machine learning in computer science.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 4 - The Reproducibility Checklist
|Instruction Step Text=<span lang="EN-US"><span lang="EN-GB">The <span lang="DE">[https://eur04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FGESIS-Methods-Hub%2Fguidelines-for-methods%2Fblob%2Fmain%2FREADME-template.md&data=05%7C02%7Cb.leitner%40amsterdamumc.nl%7C98306bdc1d14436a474308de062e488a%7C68dfab1a11bb4cc6beb528d756984fb6%7C0%7C0%7C638954993173754302%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=8wKJxWZb4qfVKLG%2F%2Bgn4HWuQCxrkIvrUyENg%2FEEwiWM%3D&reserved=0 Reproducibility Checklist for Computational Social Science Research]</span> provides a simple, structured framework to enhance the reproducibility of computational methods shared on [https://eur04.safelinks.protection.outlook.com/?url=http%3A%2F%2Fmethodshub.gesis.org%2F&data=05%7C02%7Cb.leitner%40amsterdamumc.nl%7C98306bdc1d14436a474308de062e488a%7C68dfab1a11bb4cc6beb528d756984fb6%7C0%7C0%7C638954993173788095%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=fZvqBgWjUcBuH%2FNJKGAl8WYPcNRsRQujUc8k%2FbPcG3Q%3D&reserved=0 Methods Hub]. Designed for minimal effort and maximum usability, the checklist helps researchers document and share their data and code in a consistent, verifiable way that fosters trust and collaboration within the social science community. This pilot contributes to more efficient, transparent, and reproducible computational social science by integrating practical usability with clear documentation standards.</span></span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 5 - The Reproducibility Promotion Plan for Funders (RPP)
|Instruction Step Text=<span lang="EN-US">The Reproducibility Promotion Plan for Funders (RPP) has developed a policy template with recommendations for funders to foster reproducible practices both in the research they fund across three key areas of funding work: evaluation and monitoring, policy and definitions, and incentives. The RPP provides actionable recommendations and best practice examples that funders and funding institutions can adapt to meet their specific needs.</span>

All drafts of the RPP can be found on [https://osf.io/3fpbj/ OSF].

[[File:RPP4F One Pager.jpg|center|thumb]]
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 6 - The Reproducibility Monitoring Dashboard
|Instruction Step Text=<span lang="EN-US">The Reproducibility Monitoring Dashboard hosts tools that enable funding agencies to track and monitor the reusability of research artifacts across various projects, programs, topics, and disciplines. This auto-generated dashboard assesses the impacts of policies related to data and code sharing.</span>
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 7 - Editorial Workflows to Increase Data Sharing
|Instruction Step Text=This tool is aimed at increasing data sharing in published work. Data sharing is an important building block for increased reproducibility & transparency, but current rates of sharing are low.
}}
{{Instruction Step Trainee
|Instruction Step Title=Pilot 8- An Editorial Reference Handbook for Reproducibility and FAIRness
|Instruction Step Text=<div>
<span lang="EN-US">The [https://publishers.fairassist.org/ <u>Editorial Reference Handbook</u>] informs and assists journals to operationalise a set of checks necessary to make the data underlying published research findings more findable, accessible, interoperable and reusable (FAIR) to underpin reproducibility. The Handbook targets in-house staff managing the manuscripts primarily, but it will also benefit reviewers, authors and even those providing services to publishers by making the fundamental checks and requirements transparent and understandable.</span>
</div><div>
<span lang="EN-US">The Handbook includes three interlinked components: a checklist of 12 elements, a flowchart that outlines the ideal internal manuscript submission workflow (who should perform the checks and when), and a guidance to help users to implement the checks effectively, with definitions and tips.</span>
</div><div>
<span lang="EN-US">The Handbook fills a gap, because no common guidance existed on the practical implementation of these checks across a complex publishing workflow and the variety of individuals and teams involved. This pilot saw the participation of more than 30 individuals, from more than 20 journals of major publishers: CUP, Cell Press, EMBO Press, Taylor & Francis, GigaScience Press, OUP, PLOS, Springer Nature.</span>
</div>
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Instruction:1354bf06-e258-4d40-bfa0-b6bcc6a68dea

2025-10-03T13:45:09Z

0009-0002-1788-6517:

{{Instruction
|Title=Future of Reproducibility
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=<span lang="EN-US">Policy briefs and recommendations</span>
|Has Duration=1
|Important For=All stakeholders in research
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|Instruction Step Title=Policy Brief 1: Reproducibility and Epistemic Diversity
|Instruction Step Text=<div>Reproducibility and Epistemic Diversity
Reproducibility is emerging as a key priority for research stakeholders. In this policy brief, targeted at research policy - makers (e.g., funders, institutions and publishers), the team built on findings from the first year of the TIER2 project to deliver advice on creating policy that is sensitive to differences in basic conditions for knowledge production within and across fields (epistemic diversity) that crucially affect the relevance and feasibility of reproducibility.

The full policy brief on the connection between reproducbility and epistemic diversity can be found here: [https://osf.io/hxa24 OSF -TIER2_D2.5_Policy_Brief_1_Reproducibility_and_Epistemic_Diversity.pdf]

</div>
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Instruction:62bee3f2-de7c-4bc6-ae88-fe8b93f5d1f6

2025-10-03T13:39:58Z

0009-0002-1788-6517:

{{Instruction
|Title=What is reproducibility?
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=This module provides an in-depth introduction to reproducibility through the work of TIER2 and iRise. The purpose and concept of reproducibility is introduced, working definitions are provided for important concepts in relation to reproducibility and replicability, and the futures of reproducibility and illustrated from the perspective of different stakeholders.
|Has Duration=2
|Important For=All stakeholders in research; Funders; Publishers; Researchers
}}
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|Instruction Step Title=Enabling and Redoing
|Instruction Step Text=The research team within TIER2 present an analytical framework that supports epistemic diversity by examining the potential relevance and degree of feasibility of reproducibility for different modes of knowledge production. The research team find current general typologies with the same aim wanting. They propose top-down derived enumerative lists of kinds of reproducibility organised according to vaguely defined fields, disciplines, methods or so-called research types. Current typologies cannot sufficiently characterise different kinds of research and their varying research context at the granularity needed to deal with how epistemic diversity and reproducibility relate. They also do not clarify the prevailing conceptual confusion surrounding reproducibility and replication. To clarify matters, they propose ''redoing'' to commonly describe the acts of reproducing and replicating and ''enabling'' to describe the acts of making something reproducible and replicable. They suggest mapping practices and epistemic functions to characterise what parts of a study should be redone or enabled and for what intended purposes. The research team propose knowledge production modes (KPM) as an organising construct to situate redoing and enabling within knowledge production’s epistemic, social, and contextual conditions. Epistemologies determine epistemic norms and criteria. Social conditions influence how research is organised, practised, rewarded, reported, and discussed. Contextual conditions put boundaries and restrictions on research, for example, due to subject matter, environment, availability of resources, and technologies, which are the ‘local’ conditions. Their framework clarifies the potential ''relevance'' of redoing and the degree of ''feasibility'' of redoing and enabling for a specific knowledge production mode. Relevance comprises research goals and epistemology. Epistemology is the basic assumption behind knowledge production modes. It determines how knowledge claims are produced and justified with systems of justification, the criteria for good/trustworthy research, and, thus, the epistemic norms. Different ways of knowing have different epistemic norms, practices, and criteria. Feasibility comprises the nature and complexity of the subject under investigation, the necessary investment for redoing or enabling, and the degree of theoretical and methodological uncertainty associated with the actual research. The proposed framework works bottom-up in that knowledge production modes are not defined a priori but derived from the analytical framework. The framework, therefore, supports epistemic diversity by being open and non-hierarchical and working at a sufficient level of granularity to discern the diverse conditions of knowledge production. The research team propose a framework that can clarify, not a cookbook. Enabling in some form always seems relevant in empirical work irrespective of ways of knowing—the same is not true for redoing.

For the full paper click here: [https://osf.io/preprints/metaarxiv/ujnd9_v1 MetaArXiv Preprints - Knowledge Production Modes: The Relevance and Feasibility of Reproducibility]

'''Reference'''

Ulpts, S., & Schneider, J. W. (2023, September 25). Knowledge Production Modes: The Relevance and Feasibility of Reproducibility. <nowiki>https://doi.org/10.31222/osf.io/ujnd9</nowiki>
}}
{{Instruction Step Trainee
|Instruction Step Title=Defining Reproducibility
|Instruction Step Text=Defining reproducibility and replicability, has been a challenge in the research community, as different interpretations and even contradicting definitions are often used. Defining these terms has proven to be challenging as their use and understanding differs between fields of research. However, the European funded iRise consortium developed a reproducibility glossary by critically reviewing existing scientific literature. The glossary provides working definitions for the use of terms reproducibility, replicability and replication, as well as related concepts.

'''References'''

Voelkl, B., Heyard, R., Fanelli, D., Wever, K., Held, L., Würbel, H., Zellers, S., & Maniadis, Z. (2024). Glossary of common terminology resulting from scoping reviews. https://osf.io/ewybt.
}}
{{Instruction Step Trainee
|Instruction Step Title=Futures of Reproducibility
|Instruction Step Text=<div>
<span lang="EN-GB">Improving reproducibility is a multifaceted challenge requiring both behavioural and cultural change.</span> <span lang="EN-US">The adoption of reproducibility practices has been sparked and embraced by the Open Science movement. However, a lot of researchers are not fully aware of the implications of reproducibility and how Open Science and reproducibility are connected and intertwined (Haven et al., 2022). To increase awareness and change research practices several steps should be taken (Nosek, 2019). First, the infrastructure for the desired behaviour should be provided to make it possible. Second, the user interface and experience of the infrastructure should be improved to make the behaviour easy. Third, communities of practice should be fostered to make the behaviour visible and so increasingly normative. Fourth, incentives to enact the behaviour should be provided to make it rewarding. Last, policies should be enacted to make the behaviour required (Nosek, 2019). To further this work, we sought to explore the future of reproducibility for different stakeholders and question what should be the next steps for reproducibility and how diverse epistemic contexts can adopt reproducibility in different forms. In this deliverable, we aim to add nuance to the reproducibility debate through flexible investigation of diverse epistemic contexts (researchers from the field of machine learning and researchers working with qualitative methods), exploring the future of reproducibility through the lens of diverse research stakeholders – researchers, funders, and publishers.</span>
</div><div>
<span lang="EN-US">In this context, we look to the future of reproducibility by exploring the preferred scenarios for multiple stakeholders, including how these scenarios can be realized. We reflect on the steps that are necessary for adherence to reproducibility-enabling practices and what different epistemic contexts need to make reproducibility a priority. Lastly, we reflect on what are the new problems that we may face when aiming to improve reproducibility. We believe exploring the possible futures for reproducibility is essential to discover the next steps for different members of the scientific community to take to realize the preferred future and the actions to avoid steering away from the dystopian futures.</span>
</div><div>
<span lang="EN-US">We aim to highlight the essential role of institutions, funders and publishers in this endeavor to make reproducibility a priority by recognizing, rewarding, evaluating and monitoring reproducibility. Ultimately, we hope to steer and move forward the debate on reproducibility in the research community by</span> <span lang="EN-GB">addressing a set of core research questions related to how key stakeholders in the academic community envision the way in which matters of reproducibility should be addressed in the future. More specifically, it asks representatives from research funders, scholarly publishers, and researchers from diverse disciplinary backgrounds:</span>
</div><div>
<span lang="EN-GB">1. What are the preferred futures of reproducibility?</span>
</div><div>
<span lang="EN-GB">2. What are the enablers and barriers on the way to the preferred future or reproducibility more generally?</span>
</div><div>
Below we present the results of our study below.
</div>

For more information, please refer to the full paper: [https://osf.io/preprints/metaarxiv/gx9jq_v1 MetaArXiv Preprints - How to get there from here? Barriers and enablers on the road towards reproducibility in research].
|Instruction Step Interactive Content=Resource:H5P-116
}}
{{Instruction Step Trainee
|Instruction Step Title=Open Science interventions to improve reproducibility and replicability of research
|Instruction Step Text=<div>Various interventions – especially those related to open science – have been proposed to improve the reproducibility and replicability of scientific research. To assess whether and which interventions have been formally tested for their effectiveness in improving reproducibility and replicability, the research team from TIER2 and OSIRIS conducted a scoping review of the literature on interventions to improve reproducibility. They systematically searched Medline, Embase, Web of Science, PsycINFO, Scopus and Eric, on August 18, 2023. Grey literature was requested from experts in the fields of reproducibility and open science. Any study empirically evaluating the effectiveness of interventions aimed at improving the reproducibility or replicability of scientific methods and findings wasincluded. An intervention could be any action taken by either individual researchers or scientific institutions (e.g., research institutes, publishers and funders). We summarized the retrieved evidence narratively and in an evidence gap map. Of the 104 distinct studies we included, 15 directly measured the effect of an intervention on reproducibility or replicability, while the other research questions addressed a proxy outcome that might be expected to increase reproducibility or replicability, such as data sharing, methods transparency or preregistration. Thirty research questions within included studies were non-comparative and 27 were comparative but cross-sectional, precluding any causal inference. Possible limitations of our review may be the search and selection strategy, which was done by a large team including researchers from different disciplines and different expertise levels. Despite studies investigating a range of interventions and addressing various outcomes, our findings indicate that in general the evidence-base for which various interventions to improve reproducibility of research remains remarkably limited in many respects.
The full pre-print is available here: [https://osf.io/preprints/metaarxiv/a8rmu_v1 MetaArXiv Preprints - Open Science interventions to improve reproducibility and replicability of research: a scoping review preprint]

Dudda, L., Kormann, E., Kozula, M., DeVito, N. J., Klebel, T., Dewi, A. P. M., … Leeflang, M. (2024, June 17). Open Science interventions to improve reproducibility and replicability of research: a scoping review preprint. <nowiki>https://doi.org/10.31222/osf.io/a8rmu</nowiki>
</div>
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{{Tags
|Involves=TIER2
|Has Good Practice And Misconduct=Reproducibility
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Instruction:4bc3edc0-d493-4f35-a742-e4cee5569562

2025-05-26T15:19:05Z

0009-0002-1788-6517:

Instruction:7c159fc9-db27-4623-9432-9c37b8889f89

2025-05-26T15:05:03Z

0009-0002-1788-6517:

{{Instruction
|Title=Communities and collaborators
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=On this page we present the TIER2 Reproducibility Network Award, the stakeholder community building activities and efforts of TIER2, our consortia partners (iRise and OSIRIS), and finally the UKRN Primers initative.
|Has Duration=1
|Important For=All stakeholders in research
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{{Instruction Step Trainee
|Instruction Step Title=Reproducibility Network Award
|Instruction Step Text=<div>
==='''<span lang="EN-GB">What is a Reproducibility Network?</span>''' ===
</div><div><div>
<span lang="EN-GB">A national Reproducibility Network <u>(RN)</u> is a countrywide peer-led consortium that aims to improve research practices by promoting, supporting, and investigating factors contributing to robust research including, but not limited to, reproducibility, replicability, and Open Science. Activities may include promoting training activities, disseminating best practices, supporting research on reproducible research practices, and advocacy for reproducible and open research. </span>
</div><div>
<span lang="EN-GB">An RN typically serves as a hub to connect researchers to exchange ideas and good practices, promoting collaboration among researchers from a range of scientific disciplines. These networks provide infrastructure, facilitate opportunities for researchers and initiatives to support and amplify each other’s efforts, and foster community building as well as shared problem solving. </span>
</div><div>
<span lang="EN-GB">RNs can serve as connectors to other stakeholder groups such as universities, funders, or academic publishers.</span>
</div></div>

===Benefits for setting up an Reproducibility Network?===

<span lang="EN-GB">By providing seed funding for the establishment of a new RN, you actively contribute to the strengthening of reproducibility and Open Science in your local ecosystem. The widespread presence of RNs is crucial, as they function as points of contact for scientific communities who, across e.g., disciplinary, demographic, and geographic contexts, face different challenges and barriers. RNs can provide local and tailored support and keep in mind the different stages of readiness of their local communities for implementing reproducible research practices.</span>

==="Lessons learned" from the TIER2 award===
1. '''<span lang="EN-GB">Build strong community links.</span>''' <span lang="EN-GB">Involve already existing and successful RNs in the establishment of new RNs. This ensures that new RNs receive valuable guidance, input and support early in the establishment process.</span>

2. '''<span lang="EN-GB">Expand connections and broaden the reach.</span>''' <span lang="EN-GB">Reach out to researchers and other relevant stakeholders, such as universities, as this is important for local support and the sustainability of the RN. However, identifying and connecting with researchers in Horizon Europe Widening Participation countries (WIDERA countries) who are active in reproducible research and Open Science practices can be challenging.</span>

3. '''<span lang="EN-GB">Facilitate international support.</span>''' <span lang="EN-GB">Several RNs across the globe exist and more are being established. Build strong international connections amongst them to facilitate the sharing of resources and best practices, this will help to coordinate and amplify efforts.</span>

4. '''<span lang="EN-GB">Focus on the local ecosystem.</span>''' <span lang="EN-GB">RNs are national networks that promote transparent and trustworthy practices in their local research ecosystems. Recognize local needs, geopolitical conditions as well as barriers and available resources.</span>

===How has TIER2 supported the awarded networks?===

1. TIER2 members and award organizers have facilitated connections between awardees and existing international Reproducibility and Open Science networks. via email contacts as well as through virtual and in-person meetings.

2. <span lang="EN-GB">TIER2 award organizers, have added awardees, with their consent, to various mailing lists and newsletters from different international RNs.</span>

3.<span lang="EN-GB">Further, TIER2 award organizers have invited awardees to attend and speak at several Open Science and reproducibility events to meet (steering group) members from other RNs and (inter-)national initiatives.</span>

<span lang="EN-GB">4. TIER2 project members as well as award organizers have provided the awardees with resources and information on relevant topics, including different RN structures, website layout and structure, as well as language.</span>

===Awardess of the TIER2 Reproducibility Network Award===

TIER2 is proud to announce the two awarded consortia based in Ukraine and Georgia who will receive the monetary awards from the Reproducibility Network open call this summer. Multiple scientific consortia from Horizon Europe “[https://www.era-learn.eu/support-for-partnerships/additional-activities/openness-inclusivness-transparency/widening-and-inclusiveness Widening Participation]” countries submitted applications describing their plans and motivations for establishing a Reproducibility Network in their home country which TIER2 would support with a €5000 prize.

[[File:Ukraine and Georgia RN.png|center|thumb]]

====Ukrainian Consortium====
The Ukrainian consortium, from the Institute for Open Science and Innovation ([https://www.facebook.com/inosi.org/ INOSI]), [https://twitter.com/optima_open OPTIMA] Project Consortium & [https://lpnu.ua/en Lviv Polytechnic National University], comprises researchers with a broad scientific background, ranging from informatics to chemistry and ecology. The core of the consortium has already experience working together in promoting Open Science in Ukraine, particularly within the OPTIMA project and within the Working Group on the [https://www.kmu.gov.ua/en/news/ukraina-pryiednalas-do-krain-ies-shcho-maiut-zatverdzhenyi-plan-realizatsii-pryntsypiv-vidkrytoi-nauky National Plan for Open Science development] in Ukraine. In response to what motivated them in participating in the open call, they state that: ''“Ukraine needs good science to make good decisions in all spheres. This is particularly relevant during the war and will be needed for the post-war recovery. Reproducibility (as a part of the Open Science concept) can boost the value of academic research in Ukraine making science a real game-changer for progress''”. Regarding their future plans for the Ukrainian Reproducibility Network, they share: “''In the short term, the ambition is to kickstart the network of experts, able to lead the discussion on reproducibility and become a role model on the national level. In the long term, the ambition is, of course, to make reproducibility in research a standard by default. This has to be supported by co-creation and sharing best practices, research on research, and making an impact on national policy. We hope that the network will be viable and ambitious enough to compete for international grant funding to achieve this''”. With regard to the global state of reproducibility & scientific integrity, they say: “''The progress on the global level is visible, but it's only the beginning of a long way forward. The key to achieving the goal is a strong research culture that is often missing in many academic communities. Openness and transparency in performing and communicating research are the basic things to be established''.”

====Georgian Consortium====
The consortium from Georgia, comprises three researchers from different institutions: the Department of Human Anatomy at Tbilisi State Medical University ([https://tsmu.edu/ts/home TSMU]), the Faculty of Medicine at Tbilisi State University ([https://www.tsu.ge/en TSU]), the Institute of Morphology, and the Scientific Department at Caucasus International University ([https://ciu.edu.ge/?lang=en CIU]). Brought together as team members of a research group, they were drafting a proposal for a Horizon Europe (HE) project when their HE grant coordinator alerted them about the TIER2 open call announcement. The team was immediately drawn to it, sharing that:

“''During our individual and collective research endeavors, we frequently encountered challenges in reproducing experiment results, a phenomenon that was not isolated to our work but across the global research landscape. [...] a consolidated effort was needed to elevate the state of research in our nation. [...] Moreover, the opportunity to foster a Reproducibility Network (RN) in Georgia provided a platform to unite our nation's fragmented research endeavors, drive standards in research methodologies, and integrate with the global scientific community''”. Regarding their short-term plans after receiving the award, they list the following: “''Organize the foundational meeting, bringing together stakeholders from various Georgian research institutions, to lay down the operational blueprint for the RN; Launch training sessions that cover core skills in reproducibility, data management, and research design; Conduct sessions in universities and community centers to educate and foster trust in scientific research: Set up an official RN website and leverage social media for real-time updates and engagements”. In the long term, the team envisions to “Establish partnerships with International Reproducibility Networks, facilitating knowledge exchange and joint research projects and collaborate with Georgian institutions to advocate for policies emphasizing reproducibility and transparency''”. Their global vision for the state of reproducibility and scientific integrity “''is one where every piece of research, irrespective of its domain or geography, stands the test of time and validation. We envision a scientific landscape where collaboration, transparency, and inclusivity aren't just ideals but are deeply integrated into research methodologies''.”

They share that the way forward is to prioritize

“''1)Education & Training: Equip researchers, especially the younger generation, with the necessary tools and knowledge to ensure reproducibility.''

''2)Open Science: Promote Open Access publications, making research universally accessible and subject to broader scrutiny.''

''3)Interdisciplinary Collaborations: Foster collaborations across disciplines, pooling expertise and resources to tackle complex research challenges.''

''4)Technological Integration: Leverage technology, especially AI and data analytics, to aid in ensuring research consistency and integrity.''

''If we could change one thing, it would be the isolated nature of scientific endeavors prevalent in many regions, like Georgia. We would foster a globally interconnected research network where findings, methodologies, and tools are shared seamlessly, accelerating scientific progress and ensuring its robustness''”.

Lastly, the Georgian consortium highlights what they would change in the global reproducibility landscape if they could: “''1)Revise Academic Incentives: The current "publish or perish" culture sometimes prioritizes quantity over quality. We'd advocate for a system where researchers are rewarded for the reproducibility and integrity of their work, not just the volume. 2)Enhanced Training: Incorporate reproducibility and Open Science training at early academic stages, ensuring that upcoming researchers are well-equipped with the necessary skills and ethos. 3)Global Collaboration Platforms: Creation of digital platforms that facilitate global collaboration, data sharing, and mutual validation of research findings, breaking down silos and fostering a truly global scientific community''.”

====Serbian Consortium====
[[File:Serbian RN.png|center|thumb]]

<span lang="EN-US">[https://tier2-project.eu/ TIER2] is excited to announce the winner of the 2024 Open Call aimed at fostering the establishment of a third Reproducibility Network (RN) in “Widening Participation” countries - Serbia. The goal of Reproducibility Networks is to promote rigorous research practices, facilitate interdisciplinary collaborations and discussions, and enhance the trustworthiness of scientific work. The Serbian consortium will thus receive a €5,000 grant to organise an initial meeting, laying the groundwork for establishing an RN in their country.</span>

<span lang="EN-US">The Serbian consortium, consisting of nine organisations – six institutes and three faculties –, brings together diverse academic backgrounds with a shared commitment to improving research culture in Serbia. They focus on integrating Open Science, reproducibility, and inclusive policies into institutions and education. The consortium has previously collaborated on initiatives like the [https://nitra.gov.rs/en/ Team for Open Science in Serbia] and [https://nitra.gov.rs/en/inovacije/projekat-saige the Saige project], organising workshops and training to promote open science practices.</span>

<span lang="EN-US">Motivated by challenges such as low research investment and a scientific system that prioritises quantity over quality, they believe establishing a Reproducibility Network will enhance collaboration and help to address these issues. In the short term, they plan to promote the network through conferences, a kick-off event, and online platforms. Long-term, they aim to integrate Open Science into curricula, incentivise reproducibility, support initiatives beyond major centers, advocate for policy changes, and build international collaborations.</span>

<span lang="EN-US">Their vision for global reproducibility is one where research is transparent, ethical, and rigorous:</span>

<span lang="EN-US">''“In this ideal state, researchers across all disciplines adhere to principles of Open Science, ensuring that their methods, data, and results are accessible and reproducible.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

<span lang="EN-US">They advocate for integrating these principles into education, establishing incentive systems, and fostering collaboration:</span>

<span lang="EN-US">''“We should integrate reproducibility and Open Science practices into university curricula and professional development programs to equip researchers with the necessary skills and knowledge to conduct reproducible research.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

=== Resources to set up a Reproducibility Network ===

* [https://osf.io/ndwsj Application template]
* [https://osf.io/tsmxh Reviewer guidelines]

==='''<span lang="EN-GB">Call to action – what could you do?</span>'''===
<div>
*'''<span lang="EN-GB">Are you a researcher?</span>''' <span lang="EN-GB">Join an existing RN in your country or, if none exist, identify supporters and form your own network.</span>
</div><div>
*'''<span lang="EN-GB">Are you a funder?</span>''' <span lang="EN-GB">Offer your support by providing (additional) funding for personnel costs, events on reproducibility practices and Open Science, or training opportunities. Further, establish your own award calls to support the establishment of more RNs.</span>
</div><div>
*'''<span lang="EN-GB">Are you a publisher?</span>''' <span lang="EN-GB">Support the wide range of outputs generated by RNs, for example via special issues or journals, to help them increase their reach.</span>
</div>

===Not sure, if your country has an established Reproducibility Network?===

<span lang="EN-GB">Visit the Global Networks page hosted by the UKRN to find out if a Reproducibility Network already exists in your country: https://www.ukrn.org/global-networks/.</span> <div></div>
}}
{{Instruction Step Trainee
|Instruction Step Title=Stakeholder communities
|Instruction Step Text=== Why build communities and engage stakeholders? ==
<div>
<span lang="EN-GB">TIER2 actively engages with researchers from different research areas (social, life, and computer sciences) and two cross-disciplinary stakeholder groups (funders and publishers) to enhance reproducibility across contexts.</span>
</div><div>
<span lang="EN-GB">Through our co-creation and engagement activities, we are actively fostering communication within and across stakeholder groups creating communities of practices. Opportunities for knowledge exchange and sharing of perspectives further enhances our TIER2 community building efforts</span>
</div><div>
<span lang="EN-GB">We are emphasizing our stakeholder engagement and collaboration especially during the selection, prioritization, development, implementation, and evaluation phases of our new reproducibility-related tools and practices, designed within out eight pilot activities. Through co-creation activities, we explore opportunities for closer collaboration within and across stakeholder communities and facilitate the sharing of resources and expertise. By fostering a sense of ownership and involvement, we ensure that the new tools and practices, created within the project, are valuable and useful to the communities as well as beneficial to all parties involved.</span>
</div>
[[File:TIER2 Stakeholder Communities.jpg|thumb|Infographic illustrating the stakeholder communities and the activities they are involved with within TIER2.]]
}}
{{Instruction Step Trainee
|Instruction Step Title=Primers Inititative
|Instruction Step Text=<span lang="EN-US">The primer initiative from the United Kingdom Reproducibility Network was designed introduce a broad audience to important topics and aspects of open and reproducible scholarship. Each primer is a 3-to-4-page summary document which describes the open or reproducible research practice, why one might be interested in it, and how they can be applied or adopted with thorough guidance.</span>

More information on the Primers Initative can be found here: <u>[https://www.ukrn.org/primers/ <span lang="EN-US">https://www.ukrn.org/primers/</span>]</u> .
}}
{{Instruction Step Trainee
|Instruction Step Title=Consortia Partners
|Instruction Step Text=<span lang="EN-US">TIER2 brings a unique combination of skills and perspectives, consisting of eleven partners from seven countries, well spread across Europe. The partner organisations all bring a wealth of expertise and experience regarding the target communities (computer science, life science, social science), research culture reform, technical aspects of infrastructure and services, as well as expertise in social sciences and humanities, and gender aspects of R&I. </span>

==[https://irise-project.eu/ iRise]==
[[File:IRISE .png|thumb]]
iRise aims to deepen understanding of reproducibility drivers, evaluate their effectiveness and provide concrete solutions to enhance scientific evidence.

Their direct objectives are:

- Develop working definitions and a general framework for diagnosing and addressing reproducibility problems, define costs, benefits and opportunities, and assess the utility of theoretical evidence in forecasting the success of interventions.

- Perform scoping and systematic reviews to identify and evaluate existing interventions to improve reproducibility.

- Explore the interface between reproducibility and research culture, and in particular considerations and mainstreaming of equity, diversity, and inclusion (EDI).

- Consult and engage key stakeholder groups in prioritising practices and practical tool development for adoption to increase reproducibility.

- Test efficacy and feasibility of specific interventions to increase reproducibility.

==[https://osiris4r.eu/ OSIRIS]==
[[File:OSIRIS .png|thumb]]
Open Science to Increase Reproducibility in Science (OSIRIS) aims to facilitate the shift by systematically gathering knowledge on the underlying drivers, testing effective evidence-based solutions, identifying incentives for reproducibility by stakeholders, and embedding reproducibility in research design.
}}
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Instruction:7c159fc9-db27-4623-9432-9c37b8889f89

2025-05-26T14:56:38Z

0009-0002-1788-6517:

{{Instruction
|Title=Communities and collaborators
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=x
|Has Duration=1
|Important For=All stakeholders in research
}}
{{Custom TabContent Trainee Open}}
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{{Instruction Step Trainee
|Instruction Step Title=Reproducibility Network Award
|Instruction Step Text=<div>
==='''<span lang="EN-GB">What is a Reproducibility Network?</span>''' ===
</div><div><div>
<span lang="EN-GB">A national Reproducibility Network <u>(RN)</u> is a countrywide peer-led consortium that aims to improve research practices by promoting, supporting, and investigating factors contributing to robust research including, but not limited to, reproducibility, replicability, and Open Science. Activities may include promoting training activities, disseminating best practices, supporting research on reproducible research practices, and advocacy for reproducible and open research. </span>
</div><div>
<span lang="EN-GB">An RN typically serves as a hub to connect researchers to exchange ideas and good practices, promoting collaboration among researchers from a range of scientific disciplines. These networks provide infrastructure, facilitate opportunities for researchers and initiatives to support and amplify each other’s efforts, and foster community building as well as shared problem solving. </span>
</div><div>
<span lang="EN-GB">RNs can serve as connectors to other stakeholder groups such as universities, funders, or academic publishers.</span>
</div></div>

===Benefits for setting up an Reproducibility Network?===

<span lang="EN-GB">By providing seed funding for the establishment of a new RN, you actively contribute to the strengthening of reproducibility and Open Science in your local ecosystem. The widespread presence of RNs is crucial, as they function as points of contact for scientific communities who, across e.g., disciplinary, demographic, and geographic contexts, face different challenges and barriers. RNs can provide local and tailored support and keep in mind the different stages of readiness of their local communities for implementing reproducible research practices.</span>

==="Lessons learned" from the TIER2 award===
1. '''<span lang="EN-GB">Build strong community links.</span>''' <span lang="EN-GB">Involve already existing and successful RNs in the establishment of new RNs. This ensures that new RNs receive valuable guidance, input and support early in the establishment process.</span>

2. '''<span lang="EN-GB">Expand connections and broaden the reach.</span>''' <span lang="EN-GB">Reach out to researchers and other relevant stakeholders, such as universities, as this is important for local support and the sustainability of the RN. However, identifying and connecting with researchers in Horizon Europe Widening Participation countries (WIDERA countries) who are active in reproducible research and Open Science practices can be challenging.</span>

3. '''<span lang="EN-GB">Facilitate international support.</span>''' <span lang="EN-GB">Several RNs across the globe exist and more are being established. Build strong international connections amongst them to facilitate the sharing of resources and best practices, this will help to coordinate and amplify efforts.</span>

4. '''<span lang="EN-GB">Focus on the local ecosystem.</span>''' <span lang="EN-GB">RNs are national networks that promote transparent and trustworthy practices in their local research ecosystems. Recognize local needs, geopolitical conditions as well as barriers and available resources.</span>

===How has TIER2 supported the awarded networks?===

1. TIER2 members and award organizers have facilitated connections between awardees and existing international Reproducibility and Open Science networks. via email contacts as well as through virtual and in-person meetings.

2. <span lang="EN-GB">TIER2 award organizers, have added awardees, with their consent, to various mailing lists and newsletters from different international RNs.</span>

3.<span lang="EN-GB">Further, TIER2 award organizers have invited awardees to attend and speak at several Open Science and reproducibility events to meet (steering group) members from other RNs and (inter-)national initiatives.</span>

<span lang="EN-GB">4. TIER2 project members as well as award organizers have provided the awardees with resources and information on relevant topics, including different RN structures, website layout and structure, as well as language.</span>

===Awardess of the TIER2 Reproducibility Network Award===

TIER2 is proud to announce the two awarded consortia based in Ukraine and Georgia who will receive the monetary awards from the Reproducibility Network open call this summer. Multiple scientific consortia from Horizon Europe “[https://www.era-learn.eu/support-for-partnerships/additional-activities/openness-inclusivness-transparency/widening-and-inclusiveness Widening Participation]” countries submitted applications describing their plans and motivations for establishing a Reproducibility Network in their home country which TIER2 would support with a €5000 prize.

[[File:Ukraine and Georgia RN.png|center|thumb]]

====Ukrainian Consortium====
The Ukrainian consortium, from the Institute for Open Science and Innovation ([https://www.facebook.com/inosi.org/ INOSI]), [https://twitter.com/optima_open OPTIMA] Project Consortium & [https://lpnu.ua/en Lviv Polytechnic National University], comprises researchers with a broad scientific background, ranging from informatics to chemistry and ecology. The core of the consortium has already experience working together in promoting Open Science in Ukraine, particularly within the OPTIMA project and within the Working Group on the [https://www.kmu.gov.ua/en/news/ukraina-pryiednalas-do-krain-ies-shcho-maiut-zatverdzhenyi-plan-realizatsii-pryntsypiv-vidkrytoi-nauky National Plan for Open Science development] in Ukraine. In response to what motivated them in participating in the open call, they state that: ''“Ukraine needs good science to make good decisions in all spheres. This is particularly relevant during the war and will be needed for the post-war recovery. Reproducibility (as a part of the Open Science concept) can boost the value of academic research in Ukraine making science a real game-changer for progress''”. Regarding their future plans for the Ukrainian Reproducibility Network, they share: “''In the short term, the ambition is to kickstart the network of experts, able to lead the discussion on reproducibility and become a role model on the national level. In the long term, the ambition is, of course, to make reproducibility in research a standard by default. This has to be supported by co-creation and sharing best practices, research on research, and making an impact on national policy. We hope that the network will be viable and ambitious enough to compete for international grant funding to achieve this''”. With regard to the global state of reproducibility & scientific integrity, they say: “''The progress on the global level is visible, but it's only the beginning of a long way forward. The key to achieving the goal is a strong research culture that is often missing in many academic communities. Openness and transparency in performing and communicating research are the basic things to be established''.”

====Georgian Consortium====
The consortium from Georgia, comprises three researchers from different institutions: the Department of Human Anatomy at Tbilisi State Medical University ([https://tsmu.edu/ts/home TSMU]), the Faculty of Medicine at Tbilisi State University ([https://www.tsu.ge/en TSU]), the Institute of Morphology, and the Scientific Department at Caucasus International University ([https://ciu.edu.ge/?lang=en CIU]). Brought together as team members of a research group, they were drafting a proposal for a Horizon Europe (HE) project when their HE grant coordinator alerted them about the TIER2 open call announcement. The team was immediately drawn to it, sharing that:

“''During our individual and collective research endeavors, we frequently encountered challenges in reproducing experiment results, a phenomenon that was not isolated to our work but across the global research landscape. [...] a consolidated effort was needed to elevate the state of research in our nation. [...] Moreover, the opportunity to foster a Reproducibility Network (RN) in Georgia provided a platform to unite our nation's fragmented research endeavors, drive standards in research methodologies, and integrate with the global scientific community''”. Regarding their short-term plans after receiving the award, they list the following: “''Organize the foundational meeting, bringing together stakeholders from various Georgian research institutions, to lay down the operational blueprint for the RN; Launch training sessions that cover core skills in reproducibility, data management, and research design; Conduct sessions in universities and community centers to educate and foster trust in scientific research: Set up an official RN website and leverage social media for real-time updates and engagements”. In the long term, the team envisions to “Establish partnerships with International Reproducibility Networks, facilitating knowledge exchange and joint research projects and collaborate with Georgian institutions to advocate for policies emphasizing reproducibility and transparency''”. Their global vision for the state of reproducibility and scientific integrity “''is one where every piece of research, irrespective of its domain or geography, stands the test of time and validation. We envision a scientific landscape where collaboration, transparency, and inclusivity aren't just ideals but are deeply integrated into research methodologies''.”

They share that the way forward is to prioritize

“''1)Education & Training: Equip researchers, especially the younger generation, with the necessary tools and knowledge to ensure reproducibility.''

''2)Open Science: Promote Open Access publications, making research universally accessible and subject to broader scrutiny.''

''3)Interdisciplinary Collaborations: Foster collaborations across disciplines, pooling expertise and resources to tackle complex research challenges.''

''4)Technological Integration: Leverage technology, especially AI and data analytics, to aid in ensuring research consistency and integrity.''

''If we could change one thing, it would be the isolated nature of scientific endeavors prevalent in many regions, like Georgia. We would foster a globally interconnected research network where findings, methodologies, and tools are shared seamlessly, accelerating scientific progress and ensuring its robustness''”.

Lastly, the Georgian consortium highlights what they would change in the global reproducibility landscape if they could: “''1)Revise Academic Incentives: The current "publish or perish" culture sometimes prioritizes quantity over quality. We'd advocate for a system where researchers are rewarded for the reproducibility and integrity of their work, not just the volume. 2)Enhanced Training: Incorporate reproducibility and Open Science training at early academic stages, ensuring that upcoming researchers are well-equipped with the necessary skills and ethos. 3)Global Collaboration Platforms: Creation of digital platforms that facilitate global collaboration, data sharing, and mutual validation of research findings, breaking down silos and fostering a truly global scientific community''.”

====Serbian Consortium====
[[File:Serbian RN.png|center|thumb]]

<span lang="EN-US">[https://tier2-project.eu/ TIER2] is excited to announce the winner of the 2024 Open Call aimed at fostering the establishment of a third Reproducibility Network (RN) in “Widening Participation” countries - Serbia. The goal of Reproducibility Networks is to promote rigorous research practices, facilitate interdisciplinary collaborations and discussions, and enhance the trustworthiness of scientific work. The Serbian consortium will thus receive a €5,000 grant to organise an initial meeting, laying the groundwork for establishing an RN in their country.</span>

<span lang="EN-US">The Serbian consortium, consisting of nine organisations – six institutes and three faculties –, brings together diverse academic backgrounds with a shared commitment to improving research culture in Serbia. They focus on integrating Open Science, reproducibility, and inclusive policies into institutions and education. The consortium has previously collaborated on initiatives like the [https://nitra.gov.rs/en/ Team for Open Science in Serbia] and [https://nitra.gov.rs/en/inovacije/projekat-saige the Saige project], organising workshops and training to promote open science practices.</span>

<span lang="EN-US">Motivated by challenges such as low research investment and a scientific system that prioritises quantity over quality, they believe establishing a Reproducibility Network will enhance collaboration and help to address these issues. In the short term, they plan to promote the network through conferences, a kick-off event, and online platforms. Long-term, they aim to integrate Open Science into curricula, incentivise reproducibility, support initiatives beyond major centers, advocate for policy changes, and build international collaborations.</span>

<span lang="EN-US">Their vision for global reproducibility is one where research is transparent, ethical, and rigorous:</span>

<span lang="EN-US">''“In this ideal state, researchers across all disciplines adhere to principles of Open Science, ensuring that their methods, data, and results are accessible and reproducible.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

<span lang="EN-US">They advocate for integrating these principles into education, establishing incentive systems, and fostering collaboration:</span>

<span lang="EN-US">''“We should integrate reproducibility and Open Science practices into university curricula and professional development programs to equip researchers with the necessary skills and knowledge to conduct reproducible research.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

==='''<span lang="EN-GB">Call to action – what could you do?</span>'''===
<div>
*'''<span lang="EN-GB">Are you a researcher?</span>''' <span lang="EN-GB">Join an existing RN in your country or, if none exist, identify supporters and form your own network.</span>
</div><div>
*'''<span lang="EN-GB">Are you a funder?</span>''' <span lang="EN-GB">Offer your support by providing (additional) funding for personnel costs, events on reproducibility practices and Open Science, or training opportunities. Further, establish your own award calls to support the establishment of more RNs.</span>
</div><div>
*'''<span lang="EN-GB">Are you a publisher?</span>''' <span lang="EN-GB">Support the wide range of outputs generated by RNs, for example via special issues or journals, to help them increase their reach.</span>
</div>

===Not sure, if your country has an established Reproducibility Network?===

<span lang="EN-GB">Visit the Global Networks page hosted by the UKRN to find out if a Reproducibility Network already exists in your country: https://www.ukrn.org/global-networks/.</span> <div></div>
}}
{{Instruction Step Trainee
|Instruction Step Title=Stakeholder communities
|Instruction Step Text=== Why build communities and engage stakeholders? ==
<div>
<span lang="EN-GB">TIER2 actively engages with researchers from different research areas (social, life, and computer sciences) and two cross-disciplinary stakeholder groups (funders and publishers) to enhance reproducibility across contexts.</span>
</div><div>
<span lang="EN-GB">Through our co-creation and engagement activities, we are actively fostering communication within and across stakeholder groups creating communities of practices. Opportunities for knowledge exchange and sharing of perspectives further enhances our TIER2 community building efforts</span>
</div><div>
<span lang="EN-GB">We are emphasizing our stakeholder engagement and collaboration especially during the selection, prioritization, development, implementation, and evaluation phases of our new reproducibility-related tools and practices, designed within out eight pilot activities. Through co-creation activities, we explore opportunities for closer collaboration within and across stakeholder communities and facilitate the sharing of resources and expertise. By fostering a sense of ownership and involvement, we ensure that the new tools and practices, created within the project, are valuable and useful to the communities as well as beneficial to all parties involved.</span>
</div>
[[File:TIER2 Stakeholder Communities.jpg|thumb|Infographic illustrating the stakeholder communities and the activities they are involved with within TIER2.]]
}}
{{Instruction Step Trainee
|Instruction Step Title=Primers Inititative
|Instruction Step Text=<span lang="EN-US">The primer initiative from the United Kingdom Reproducibility Network was designed introduce a broad audience to important topics and aspects of open and reproducible scholarship. Each primer is a 3-to-4-page summary document which describes the open or reproducible research practice, why one might be interested in it, and how they can be applied or adopted with thorough guidance.</span>

More information on the Primers Initative can be found here: <u>[https://www.ukrn.org/primers/ <span lang="EN-US">https://www.ukrn.org/primers/</span>]</u> .
}}
{{Instruction Step Trainee
|Instruction Step Title=Consortia Partners
|Instruction Step Text=<span lang="EN-US">TIER2 brings a unique combination of skills and perspectives, consisting of eleven partners from seven countries, well spread across Europe. The partner organisations all bring a wealth of expertise and experience regarding the target communities (computer science, life science, social science), research culture reform, technical aspects of infrastructure and services, as well as expertise in social sciences and humanities, and gender aspects of R&I. </span>

==[https://irise-project.eu/ iRise]==
[[File:IRISE .png|thumb]]
iRise aims to deepen understanding of reproducibility drivers, evaluate their effectiveness and provide concrete solutions to enhance scientific evidence.

Their direct objectives are:

- Develop working definitions and a general framework for diagnosing and addressing reproducibility problems, define costs, benefits and opportunities, and assess the utility of theoretical evidence in forecasting the success of interventions.

- Perform scoping and systematic reviews to identify and evaluate existing interventions to improve reproducibility.

- Explore the interface between reproducibility and research culture, and in particular considerations and mainstreaming of equity, diversity, and inclusion (EDI).

- Consult and engage key stakeholder groups in prioritising practices and practical tool development for adoption to increase reproducibility.

- Test efficacy and feasibility of specific interventions to increase reproducibility.

==[https://osiris4r.eu/ OSIRIS]==
[[File:OSIRIS .png|thumb]]
Open Science to Increase Reproducibility in Science (OSIRIS) aims to facilitate the shift by systematically gathering knowledge on the underlying drivers, testing effective evidence-based solutions, identifying incentives for reproducibility by stakeholders, and embedding reproducibility in research design.
}}
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File:TIER2 Stakeholder Communities.jpg

2025-05-26T14:55:48Z

0009-0002-1788-6517:

TIER2 stakeholder communities infographic

Instruction:7c159fc9-db27-4623-9432-9c37b8889f89

2025-05-26T14:44:05Z

0009-0002-1788-6517:

{{Instruction
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|Instruction Step Title=Reproducibility Network Award
|Instruction Step Text=<div>
==='''<span lang="EN-GB">What is a Reproducibility Network?</span>''' ===
</div><div><div>
<span lang="EN-GB">A national Reproducibility Network <u>(RN)</u> is a countrywide peer-led consortium that aims to improve research practices by promoting, supporting, and investigating factors contributing to robust research including, but not limited to, reproducibility, replicability, and Open Science. Activities may include promoting training activities, disseminating best practices, supporting research on reproducible research practices, and advocacy for reproducible and open research. </span>
</div><div>
<span lang="EN-GB">An RN typically serves as a hub to connect researchers to exchange ideas and good practices, promoting collaboration among researchers from a range of scientific disciplines. These networks provide infrastructure, facilitate opportunities for researchers and initiatives to support and amplify each other’s efforts, and foster community building as well as shared problem solving. </span>
</div><div>
<span lang="EN-GB">RNs can serve as connectors to other stakeholder groups such as universities, funders, or academic publishers.</span>
</div></div>

=== Benefits for setting up an Reproducibility Network? ===

<span lang="EN-GB">By providing seed funding for the establishment of a new RN, you actively contribute to the strengthening of reproducibility and Open Science in your local ecosystem. The widespread presence of RNs is crucial, as they function as points of contact for scientific communities who, across e.g., disciplinary, demographic, and geographic contexts, face different challenges and barriers. RNs can provide local and tailored support and keep in mind the different stages of readiness of their local communities for implementing reproducible research practices.</span>

=== "Lessons learned" from the TIER2 award ===
1. '''<span lang="EN-GB">Build strong community links.</span>''' <span lang="EN-GB">Involve already existing and successful RNs in the establishment of new RNs. This ensures that new RNs receive valuable guidance, input and support early in the establishment process.</span>

2. '''<span lang="EN-GB">Expand connections and broaden the reach.</span>''' <span lang="EN-GB">Reach out to researchers and other relevant stakeholders, such as universities, as this is important for local support and the sustainability of the RN. However, identifying and connecting with researchers in Horizon Europe Widening Participation countries (WIDERA countries) who are active in reproducible research and Open Science practices can be challenging.</span>

3. '''<span lang="EN-GB">Facilitate international support.</span>''' <span lang="EN-GB">Several RNs across the globe exist and more are being established. Build strong international connections amongst them to facilitate the sharing of resources and best practices, this will help to coordinate and amplify efforts.</span>

4. '''<span lang="EN-GB">Focus on the local ecosystem.</span>''' <span lang="EN-GB">RNs are national networks that promote transparent and trustworthy practices in their local research ecosystems. Recognize local needs, geopolitical conditions as well as barriers and available resources.</span>

=== How has TIER2 supported the awarded networks? ===
1.TIER2 members and award organizers have facilitated connections between awardees and existing international Reproducibility and Open Science networks. via email contacts as well as through virtual and in-person meetings.

2. <span lang="EN-GB">TIER2 award organizers, have added awardees, with their consent, to various mailing lists and newsletters from different international RNs.</span>

3.<span lang="EN-GB">Further, TIER2 award organizers have invited awardees to attend and speak at several Open Science and reproducibility events to meet (steering group) members from other RNs and (inter-)national initiatives.</span>

<span lang="EN-GB">4. TIER2 project members as well as award organizers have provided the awardees with resources and information on relevant topics, including different RN structures, website layout and structure, as well as language.</span>

===Awardess of the TIER2 Reproducibility Network Award===
TIER2 is proud to announce the two awarded consortia based in Ukraine and Georgia who will receive the monetary awards from the Reproducibility Network open call this summer. Multiple scientific consortia from Horizon Europe “[https://www.era-learn.eu/support-for-partnerships/additional-activities/openness-inclusivness-transparency/widening-and-inclusiveness Widening Participation]” countries submitted applications describing their plans and motivations for establishing a Reproducibility Network in their home country which TIER2 would support with a €5000 prize.
[[File:Ukraine and Georgia RN.png|center|thumb]]

====Ukrainian Consortium====
The Ukrainian consortium, from the Institute for Open Science and Innovation ([https://www.facebook.com/inosi.org/ INOSI]), [https://twitter.com/optima_open OPTIMA] Project Consortium & [https://lpnu.ua/en Lviv Polytechnic National University], comprises researchers with a broad scientific background, ranging from informatics to chemistry and ecology. The core of the consortium has already experience working together in promoting Open Science in Ukraine, particularly within the OPTIMA project and within the Working Group on the [https://www.kmu.gov.ua/en/news/ukraina-pryiednalas-do-krain-ies-shcho-maiut-zatverdzhenyi-plan-realizatsii-pryntsypiv-vidkrytoi-nauky National Plan for Open Science development] in Ukraine. In response to what motivated them in participating in the open call, they state that: ''“Ukraine needs good science to make good decisions in all spheres. This is particularly relevant during the war and will be needed for the post-war recovery. Reproducibility (as a part of the Open Science concept) can boost the value of academic research in Ukraine making science a real game-changer for progress''”. Regarding their future plans for the Ukrainian Reproducibility Network, they share: “''In the short term, the ambition is to kickstart the network of experts, able to lead the discussion on reproducibility and become a role model on the national level. In the long term, the ambition is, of course, to make reproducibility in research a standard by default. This has to be supported by co-creation and sharing best practices, research on research, and making an impact on national policy. We hope that the network will be viable and ambitious enough to compete for international grant funding to achieve this''”. With regard to the global state of reproducibility & scientific integrity, they say: “''The progress on the global level is visible, but it's only the beginning of a long way forward. The key to achieving the goal is a strong research culture that is often missing in many academic communities. Openness and transparency in performing and communicating research are the basic things to be established''.”

====Georgian Consortium====
The consortium from Georgia, comprises three researchers from different institutions: the Department of Human Anatomy at Tbilisi State Medical University ([https://tsmu.edu/ts/home TSMU]), the Faculty of Medicine at Tbilisi State University ([https://www.tsu.ge/en TSU]), the Institute of Morphology, and the Scientific Department at Caucasus International University ([https://ciu.edu.ge/?lang=en CIU]). Brought together as team members of a research group, they were drafting a proposal for a Horizon Europe (HE) project when their HE grant coordinator alerted them about the TIER2 open call announcement. The team was immediately drawn to it, sharing that:

“''During our individual and collective research endeavors, we frequently encountered challenges in reproducing experiment results, a phenomenon that was not isolated to our work but across the global research landscape. [...] a consolidated effort was needed to elevate the state of research in our nation. [...] Moreover, the opportunity to foster a Reproducibility Network (RN) in Georgia provided a platform to unite our nation's fragmented research endeavors, drive standards in research methodologies, and integrate with the global scientific community''”. Regarding their short-term plans after receiving the award, they list the following: “''Organize the foundational meeting, bringing together stakeholders from various Georgian research institutions, to lay down the operational blueprint for the RN; Launch training sessions that cover core skills in reproducibility, data management, and research design; Conduct sessions in universities and community centers to educate and foster trust in scientific research: Set up an official RN website and leverage social media for real-time updates and engagements”. In the long term, the team envisions to “Establish partnerships with International Reproducibility Networks, facilitating knowledge exchange and joint research projects and collaborate with Georgian institutions to advocate for policies emphasizing reproducibility and transparency''”. Their global vision for the state of reproducibility and scientific integrity “''is one where every piece of research, irrespective of its domain or geography, stands the test of time and validation. We envision a scientific landscape where collaboration, transparency, and inclusivity aren't just ideals but are deeply integrated into research methodologies''.”

They share that the way forward is to prioritize

“''1)Education & Training: Equip researchers, especially the younger generation, with the necessary tools and knowledge to ensure reproducibility.''

''2)Open Science: Promote Open Access publications, making research universally accessible and subject to broader scrutiny.''

''3)Interdisciplinary Collaborations: Foster collaborations across disciplines, pooling expertise and resources to tackle complex research challenges.''

''4)Technological Integration: Leverage technology, especially AI and data analytics, to aid in ensuring research consistency and integrity.''

''If we could change one thing, it would be the isolated nature of scientific endeavors prevalent in many regions, like Georgia. We would foster a globally interconnected research network where findings, methodologies, and tools are shared seamlessly, accelerating scientific progress and ensuring its robustness''”.

Lastly, the Georgian consortium highlights what they would change in the global reproducibility landscape if they could: “''1)Revise Academic Incentives: The current "publish or perish" culture sometimes prioritizes quantity over quality. We'd advocate for a system where researchers are rewarded for the reproducibility and integrity of their work, not just the volume. 2)Enhanced Training: Incorporate reproducibility and Open Science training at early academic stages, ensuring that upcoming researchers are well-equipped with the necessary skills and ethos. 3)Global Collaboration Platforms: Creation of digital platforms that facilitate global collaboration, data sharing, and mutual validation of research findings, breaking down silos and fostering a truly global scientific community''.”

====Serbian Consortium====
[[File:Serbian RN.png|center|thumb]]
<span lang="EN-US">[https://tier2-project.eu/ TIER2] is excited to announce the winner of the 2024 Open Call aimed at fostering the establishment of a third Reproducibility Network (RN) in “Widening Participation” countries - Serbia. The goal of Reproducibility Networks is to promote rigorous research practices, facilitate interdisciplinary collaborations and discussions, and enhance the trustworthiness of scientific work. The Serbian consortium will thus receive a €5,000 grant to organise an initial meeting, laying the groundwork for establishing an RN in their country.</span>

<span lang="EN-US">The Serbian consortium, consisting of nine organisations – six institutes and three faculties –, brings together diverse academic backgrounds with a shared commitment to improving research culture in Serbia. They focus on integrating Open Science, reproducibility, and inclusive policies into institutions and education. The consortium has previously collaborated on initiatives like the [https://nitra.gov.rs/en/ Team for Open Science in Serbia] and [https://nitra.gov.rs/en/inovacije/projekat-saige the Saige project], organising workshops and training to promote open science practices.</span>

<span lang="EN-US">Motivated by challenges such as low research investment and a scientific system that prioritises quantity over quality, they believe establishing a Reproducibility Network will enhance collaboration and help to address these issues. In the short term, they plan to promote the network through conferences, a kick-off event, and online platforms. Long-term, they aim to integrate Open Science into curricula, incentivise reproducibility, support initiatives beyond major centers, advocate for policy changes, and build international collaborations.</span>

<span lang="EN-US">Their vision for global reproducibility is one where research is transparent, ethical, and rigorous:</span>

<span lang="EN-US">''“In this ideal state, researchers across all disciplines adhere to principles of Open Science, ensuring that their methods, data, and results are accessible and reproducible.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

<span lang="EN-US">They advocate for integrating these principles into education, establishing incentive systems, and fostering collaboration:</span>

<span lang="EN-US">''“We should integrate reproducibility and Open Science practices into university curricula and professional development programs to equip researchers with the necessary skills and knowledge to conduct reproducible research.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

=== '''<span lang="EN-GB">Call to action – what could you do?</span>''' ===
<div>
* '''<span lang="EN-GB">Are you a researcher?</span>''' <span lang="EN-GB">Join an existing RN in your country or, if none exist, identify supporters and form your own network.</span>
</div><div>
* '''<span lang="EN-GB">Are you a funder?</span>''' <span lang="EN-GB">Offer your support by providing (additional) funding for personnel costs, events on reproducibility practices and Open Science, or training opportunities. Further, establish your own award calls to support the establishment of more RNs.</span>
</div><div>
* '''<span lang="EN-GB">Are you a publisher?</span>''' <span lang="EN-GB">Support the wide range of outputs generated by RNs, for example via special issues or journals, to help them increase their reach.</span>
</div>

===Not sure, if your country has an established Reproducibility Network?===
<span lang="EN-GB">Visit the Global Networks page hosted by the UKRN to find out if a Reproducibility Network already exists in your country: https://www.ukrn.org/global-networks/.</span> <div></div>
}}
{{Instruction Step Trainee
|Instruction Step Title=Stakeholder communities
|Instruction Step Text=x
}}
{{Instruction Step Trainee
|Instruction Step Title=Primers Inititative
|Instruction Step Text=<span lang="EN-US">The primer initiative from the United Kingdom Reproducibility Network was designed introduce a broad audience to important topics and aspects of open and reproducible scholarship. Each primer is a 3-to-4-page summary document which describes the open or reproducible research practice, why one might be interested in it, and how they can be applied or adopted with thorough guidance.</span>

More information on the Primers Initative can be found here: <u>[https://www.ukrn.org/primers/ <span lang="EN-US">https://www.ukrn.org/primers/</span>]</u> .
}}
{{Instruction Step Trainee
|Instruction Step Title=Consortia Partners
|Instruction Step Text=<span lang="EN-US">TIER2 brings a unique combination of skills and perspectives, consisting of eleven partners from seven countries, well spread across Europe. The partner organisations all bring a wealth of expertise and experience regarding the target communities (computer science, life science, social science), research culture reform, technical aspects of infrastructure and services, as well as expertise in social sciences and humanities, and gender aspects of R&I. </span>

==[https://irise-project.eu/ iRise]==
[[File:IRISE .png|thumb]]
iRise aims to deepen understanding of reproducibility drivers, evaluate their effectiveness and provide concrete solutions to enhance scientific evidence.

Their direct objectives are:

- Develop working definitions and a general framework for diagnosing and addressing reproducibility problems, define costs, benefits and opportunities, and assess the utility of theoretical evidence in forecasting the success of interventions.

- Perform scoping and systematic reviews to identify and evaluate existing interventions to improve reproducibility.

- Explore the interface between reproducibility and research culture, and in particular considerations and mainstreaming of equity, diversity, and inclusion (EDI).

- Consult and engage key stakeholder groups in prioritising practices and practical tool development for adoption to increase reproducibility.

- Test efficacy and feasibility of specific interventions to increase reproducibility.

==[https://osiris4r.eu/ OSIRIS]==
[[File:OSIRIS .png|thumb]]
Open Science to Increase Reproducibility in Science (OSIRIS) aims to facilitate the shift by systematically gathering knowledge on the underlying drivers, testing effective evidence-based solutions, identifying incentives for reproducibility by stakeholders, and embedding reproducibility in research design.
}}
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Instruction:4bc3edc0-d493-4f35-a742-e4cee5569562

2025-04-08T16:11:10Z

0009-0002-1788-6517:

File:RPP4F One Pager.jpg

2025-04-08T16:10:51Z

0009-0002-1788-6517:

One pager of the recommendations from RPP4F

Instruction:7c159fc9-db27-4623-9432-9c37b8889f89

2025-04-08T15:40:16Z

0009-0002-1788-6517:

{{Instruction
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{{Instruction Step Trainee
|Instruction Step Title=Reproducibility Network Award
|Instruction Step Text=<div>
==='''<span lang="EN-GB">What is a Reproducibility Network?</span>''' ===
</div><div>
<span lang="EN-GB">A national Reproducibility Network is a countrywide peer-led consortium that aims to improve research practices by promoting, supporting, and investigating factors contributing to robust research including, but not limited to, reproducibility, replicability, and Open Science. Activities may include promoting training activities, disseminating best practices, supporting research on reproducible research practices, and advocacy for reproducible and open research. </span>
</div><div>
<span lang="EN-GB">A Reproducibility Network typically serves as a hub to connect researchers to exchange ideas and good practices, promoting collaboration among researchers from a range of scientific disciplines. These networks provide infrastructure, facilitate opportunities for researchers and initiatives to support and amplify each other’s efforts, and foster community building as well as shared problem solving. </span>
</div><div>
<span lang="EN-GB">Reproducibility Networks can serve as connectors to other stakeholder groups such as universities, funders, or academic publishers. </span>

</div>

===Why an organizations should consider setting up their own seed funding award for new Reproducibility Networks?===

*Benefits for setting up an Reproducibility Network?
*Reflections on the TIER2 Reproducibility Network Award

*Resources to set up a Reproducibility Network

===Awardess of the TIER2 Reproducibility Network Award===
TIER2 is proud to announce the two awarded consortia based in Ukraine and Georgia who will receive the monetary awards from the Reproducibility Network open call this summer. Multiple scientific consortia from Horizon Europe “[https://www.era-learn.eu/support-for-partnerships/additional-activities/openness-inclusivness-transparency/widening-and-inclusiveness Widening Participation]” countries submitted applications describing their plans and motivations for establishing a Reproducibility Network in their home country which TIER2 would support with a €5000 prize.
[[File:Ukraine and Georgia RN.png|center|thumb]]

====Ukrainian Consortium====
The Ukrainian consortium, from the Institute for Open Science and Innovation ([https://www.facebook.com/inosi.org/ INOSI]), [https://twitter.com/optima_open OPTIMA] Project Consortium & [https://lpnu.ua/en Lviv Polytechnic National University], comprises researchers with a broad scientific background, ranging from informatics to chemistry and ecology. The core of the consortium has already experience working together in promoting Open Science in Ukraine, particularly within the OPTIMA project and within the Working Group on the [https://www.kmu.gov.ua/en/news/ukraina-pryiednalas-do-krain-ies-shcho-maiut-zatverdzhenyi-plan-realizatsii-pryntsypiv-vidkrytoi-nauky National Plan for Open Science development] in Ukraine. In response to what motivated them in participating in the open call, they state that: ''“Ukraine needs good science to make good decisions in all spheres. This is particularly relevant during the war and will be needed for the post-war recovery. Reproducibility (as a part of the Open Science concept) can boost the value of academic research in Ukraine making science a real game-changer for progress''”. Regarding their future plans for the Ukrainian Reproducibility Network, they share: “''In the short term, the ambition is to kickstart the network of experts, able to lead the discussion on reproducibility and become a role model on the national level. In the long term, the ambition is, of course, to make reproducibility in research a standard by default. This has to be supported by co-creation and sharing best practices, research on research, and making an impact on national policy. We hope that the network will be viable and ambitious enough to compete for international grant funding to achieve this''”. With regard to the global state of reproducibility & scientific integrity, they say: “''The progress on the global level is visible, but it's only the beginning of a long way forward. The key to achieving the goal is a strong research culture that is often missing in many academic communities. Openness and transparency in performing and communicating research are the basic things to be established''.”

====Georgian Consortium====
The consortium from Georgia, comprises three researchers from different institutions: the Department of Human Anatomy at Tbilisi State Medical University ([https://tsmu.edu/ts/home TSMU]), the Faculty of Medicine at Tbilisi State University ([https://www.tsu.ge/en TSU]), the Institute of Morphology, and the Scientific Department at Caucasus International University ([https://ciu.edu.ge/?lang=en CIU]). Brought together as team members of a research group, they were drafting a proposal for a Horizon Europe (HE) project when their HE grant coordinator alerted them about the TIER2 open call announcement. The team was immediately drawn to it, sharing that:

“''During our individual and collective research endeavors, we frequently encountered challenges in reproducing experiment results, a phenomenon that was not isolated to our work but across the global research landscape. [...] a consolidated effort was needed to elevate the state of research in our nation. [...] Moreover, the opportunity to foster a Reproducibility Network (RN) in Georgia provided a platform to unite our nation's fragmented research endeavors, drive standards in research methodologies, and integrate with the global scientific community''”. Regarding their short-term plans after receiving the award, they list the following: “''Organize the foundational meeting, bringing together stakeholders from various Georgian research institutions, to lay down the operational blueprint for the RN; Launch training sessions that cover core skills in reproducibility, data management, and research design; Conduct sessions in universities and community centers to educate and foster trust in scientific research: Set up an official RN website and leverage social media for real-time updates and engagements”. In the long term, the team envisions to “Establish partnerships with International Reproducibility Networks, facilitating knowledge exchange and joint research projects and collaborate with Georgian institutions to advocate for policies emphasizing reproducibility and transparency''”. Their global vision for the state of reproducibility and scientific integrity “''is one where every piece of research, irrespective of its domain or geography, stands the test of time and validation. We envision a scientific landscape where collaboration, transparency, and inclusivity aren't just ideals but are deeply integrated into research methodologies''.”

They share that the way forward is to prioritize

“''1)Education & Training: Equip researchers, especially the younger generation, with the necessary tools and knowledge to ensure reproducibility.''

''2)Open Science: Promote Open Access publications, making research universally accessible and subject to broader scrutiny.''

''3)Interdisciplinary Collaborations: Foster collaborations across disciplines, pooling expertise and resources to tackle complex research challenges.''

''4)Technological Integration: Leverage technology, especially AI and data analytics, to aid in ensuring research consistency and integrity.''

''If we could change one thing, it would be the isolated nature of scientific endeavors prevalent in many regions, like Georgia. We would foster a globally interconnected research network where findings, methodologies, and tools are shared seamlessly, accelerating scientific progress and ensuring its robustness''”.

Lastly, the Georgian consortium highlights what they would change in the global reproducibility landscape if they could: “''1)Revise Academic Incentives: The current "publish or perish" culture sometimes prioritizes quantity over quality. We'd advocate for a system where researchers are rewarded for the reproducibility and integrity of their work, not just the volume. 2)Enhanced Training: Incorporate reproducibility and Open Science training at early academic stages, ensuring that upcoming researchers are well-equipped with the necessary skills and ethos. 3)Global Collaboration Platforms: Creation of digital platforms that facilitate global collaboration, data sharing, and mutual validation of research findings, breaking down silos and fostering a truly global scientific community''.”

====Serbian Consortium====
[[File:Serbian RN.png|center|thumb]]
<span lang="EN-US">[https://tier2-project.eu/ TIER2] is excited to announce the winner of the 2024 Open Call aimed at fostering the establishment of a third Reproducibility Network (RN) in “Widening Participation” countries - Serbia. The goal of Reproducibility Networks is to promote rigorous research practices, facilitate interdisciplinary collaborations and discussions, and enhance the trustworthiness of scientific work. The Serbian consortium will thus receive a €5,000 grant to organise an initial meeting, laying the groundwork for establishing an RN in their country.</span>

<span lang="EN-US">The Serbian consortium, consisting of nine organisations – six institutes and three faculties –, brings together diverse academic backgrounds with a shared commitment to improving research culture in Serbia. They focus on integrating Open Science, reproducibility, and inclusive policies into institutions and education. The consortium has previously collaborated on initiatives like the [https://nitra.gov.rs/en/ Team for Open Science in Serbia] and [https://nitra.gov.rs/en/inovacije/projekat-saige the Saige project], organising workshops and training to promote open science practices.</span>

<span lang="EN-US">Motivated by challenges such as low research investment and a scientific system that prioritises quantity over quality, they believe establishing a Reproducibility Network will enhance collaboration and help to address these issues. In the short term, they plan to promote the network through conferences, a kick-off event, and online platforms. Long-term, they aim to integrate Open Science into curricula, incentivise reproducibility, support initiatives beyond major centers, advocate for policy changes, and build international collaborations.</span>

<span lang="EN-US">Their vision for global reproducibility is one where research is transparent, ethical, and rigorous:</span>

<span lang="EN-US">''“In this ideal state, researchers across all disciplines adhere to principles of Open Science, ensuring that their methods, data, and results are accessible and reproducible.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

<span lang="EN-US">They advocate for integrating these principles into education, establishing incentive systems, and fostering collaboration:</span>

<span lang="EN-US">''“We should integrate reproducibility and Open Science practices into university curricula and professional development programs to equip researchers with the necessary skills and knowledge to conduct reproducible research.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

====Not sure, if your country has an established Reproducibility Network?====
<span lang="EN-GB">Visit the Global Networks page hosted by the UKRN to find out if a Reproducibility Network already exists in your country: https://www.ukrn.org/global-networks/.</span> <div></div>
}}
{{Instruction Step Trainee
|Instruction Step Title=Stakeholder communities
|Instruction Step Text=x
}}
{{Instruction Step Trainee
|Instruction Step Title=Primers Inititative
|Instruction Step Text=<span lang="EN-US">The primer initiative from the United Kingdom Reproducibility Network was designed introduce a broad audience to important topics and aspects of open and reproducible scholarship. Each primer is a 3-to-4-page summary document which describes the open or reproducible research practice, why one might be interested in it, and how they can be applied or adopted with thorough guidance.</span>

More information on the Primers Initative can be found here: <u>[https://www.ukrn.org/primers/ <span lang="EN-US">https://www.ukrn.org/primers/</span>]</u> .
}}
{{Instruction Step Trainee
|Instruction Step Title=Consortia Partners
|Instruction Step Text=<span lang="EN-US">TIER2 brings a unique combination of skills and perspectives, consisting of eleven partners from seven countries, well spread across Europe. The partner organisations all bring a wealth of expertise and experience regarding the target communities (computer science, life science, social science), research culture reform, technical aspects of infrastructure and services, as well as expertise in social sciences and humanities, and gender aspects of R&I. </span>

==[https://irise-project.eu/ iRise]==
[[File:IRISE .png|thumb]]
iRise aims to deepen understanding of reproducibility drivers, evaluate their effectiveness and provide concrete solutions to enhance scientific evidence.

Their direct objectives are:

- Develop working definitions and a general framework for diagnosing and addressing reproducibility problems, define costs, benefits and opportunities, and assess the utility of theoretical evidence in forecasting the success of interventions.

- Perform scoping and systematic reviews to identify and evaluate existing interventions to improve reproducibility.

- Explore the interface between reproducibility and research culture, and in particular considerations and mainstreaming of equity, diversity, and inclusion (EDI).

- Consult and engage key stakeholder groups in prioritising practices and practical tool development for adoption to increase reproducibility.

- Test efficacy and feasibility of specific interventions to increase reproducibility.

==[https://osiris4r.eu/ OSIRIS]==
[[File:OSIRIS .png|thumb]]
Open Science to Increase Reproducibility in Science (OSIRIS) aims to facilitate the shift by systematically gathering knowledge on the underlying drivers, testing effective evidence-based solutions, identifying incentives for reproducibility by stakeholders, and embedding reproducibility in research design.
}}
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Instruction:7c159fc9-db27-4623-9432-9c37b8889f89

2025-04-08T15:39:01Z

0009-0002-1788-6517:

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|Instruction Step Title=Reproducibility Network Award
|Instruction Step Text=<div>
==='''<span lang="EN-GB">What is a Reproducibility Network?</span>''' ===
</div><div>
<span lang="EN-GB">A national Reproducibility Network is a countrywide peer-led consortium that aims to improve research practices by promoting, supporting, and investigating factors contributing to robust research including, but not limited to, reproducibility, replicability, and Open Science. Activities may include promoting training activities, disseminating best practices, supporting research on reproducible research practices, and advocacy for reproducible and open research. </span>
</div><div>
<span lang="EN-GB">A Reproducibility Network typically serves as a hub to connect researchers to exchange ideas and good practices, promoting collaboration among researchers from a range of scientific disciplines. These networks provide infrastructure, facilitate opportunities for researchers and initiatives to support and amplify each other’s efforts, and foster community building as well as shared problem solving. </span>
</div><div>
<span lang="EN-GB">Reproducibility Networks can serve as connectors to other stakeholder groups such as universities, funders, or academic publishers. </span>

</div>

===Why an organizations should consider setting up their own seed funding award for new Reproducibility Networks?===

*Benefits for setting up an Reproducibility Network?
*Reflections on the TIER2 Reproducibility Network Award

*Resources to set up a Reproducibility Network

===Awardess of the TIER2 Reproducibility Network Award===
TIER2 is proud to announce the two awarded consortia based in Ukraine and Georgia who will receive the monetary awards from the Reproducibility Network open call this summer. Multiple scientific consortia from Horizon Europe “[https://www.era-learn.eu/support-for-partnerships/additional-activities/openness-inclusivness-transparency/widening-and-inclusiveness Widening Participation]” countries submitted applications describing their plans and motivations for establishing a Reproducibility Network in their home country which TIER2 would support with a €5000 prize.
[[File:Ukraine and Georgia RN.png|center|thumb]]

==== Ukrainian Consortium ====
The Ukrainian consortium, from the Institute for Open Science and Innovation ([https://www.facebook.com/inosi.org/ INOSI]), [https://twitter.com/optima_open OPTIMA] Project Consortium & [https://lpnu.ua/en Lviv Polytechnic National University], comprises researchers with a broad scientific background, ranging from informatics to chemistry and ecology. The core of the consortium has already experience working together in promoting Open Science in Ukraine, particularly within the OPTIMA project and within the Working Group on the [https://www.kmu.gov.ua/en/news/ukraina-pryiednalas-do-krain-ies-shcho-maiut-zatverdzhenyi-plan-realizatsii-pryntsypiv-vidkrytoi-nauky National Plan for Open Science development] in Ukraine. In response to what motivated them in participating in the open call, they state that: ''“Ukraine needs good science to make good decisions in all spheres. This is particularly relevant during the war and will be needed for the post-war recovery. Reproducibility (as a part of the Open Science concept) can boost the value of academic research in Ukraine making science a real game-changer for progress''”. Regarding their future plans for the Ukrainian Reproducibility Network, they share: “''In the short term, the ambition is to kickstart the network of experts, able to lead the discussion on reproducibility and become a role model on the national level. In the long term, the ambition is, of course, to make reproducibility in research a standard by default. This has to be supported by co-creation and sharing best practices, research on research, and making an impact on national policy. We hope that the network will be viable and ambitious enough to compete for international grant funding to achieve this''”. With regard to the global state of reproducibility & scientific integrity, they say: “''The progress on the global level is visible, but it's only the beginning of a long way forward. The key to achieving the goal is a strong research culture that is often missing in many academic communities. Openness and transparency in performing and communicating research are the basic things to be established''.”

==== Georgian Consortium ====
The consortium from Georgia, comprises three researchers from different institutions: the Department of Human Anatomy at Tbilisi State Medical University ([https://tsmu.edu/ts/home TSMU]), the Faculty of Medicine at Tbilisi State University ([https://www.tsu.ge/en TSU]), the Institute of Morphology, and the Scientific Department at Caucasus International University ([https://ciu.edu.ge/?lang=en CIU]). Brought together as team members of a research group, they were drafting a proposal for a Horizon Europe (HE) project when their HE grant coordinator alerted them about the TIER2 open call announcement. The team was immediately drawn to it, sharing that:

“''During our individual and collective research endeavors, we frequently encountered challenges in reproducing experiment results, a phenomenon that was not isolated to our work but across the global research landscape. [...] a consolidated effort was needed to elevate the state of research in our nation. [...] Moreover, the opportunity to foster a Reproducibility Network (RN) in Georgia provided a platform to unite our nation's fragmented research endeavors, drive standards in research methodologies, and integrate with the global scientific community''”. Regarding their short-term plans after receiving the award, they list the following: “''Organize the foundational meeting, bringing together stakeholders from various Georgian research institutions, to lay down the operational blueprint for the RN; Launch training sessions that cover core skills in reproducibility, data management, and research design; Conduct sessions in universities and community centers to educate and foster trust in scientific research: Set up an official RN website and leverage social media for real-time updates and engagements”. In the long term, the team envisions to “Establish partnerships with International Reproducibility Networks, facilitating knowledge exchange and joint research projects and collaborate with Georgian institutions to advocate for policies emphasizing reproducibility and transparency''”. Their global vision for the state of reproducibility and scientific integrity “''is one where every piece of research, irrespective of its domain or geography, stands the test of time and validation. We envision a scientific landscape where collaboration, transparency, and inclusivity aren't just ideals but are deeply integrated into research methodologies''.”

They share that the way forward is to prioritize

“''1)Education & Training: Equip researchers, especially the younger generation, with the necessary tools and knowledge to ensure reproducibility.''

''2)Open Science: Promote Open Access publications, making research universally accessible and subject to broader scrutiny.''

''3)Interdisciplinary Collaborations: Foster collaborations across disciplines, pooling expertise and resources to tackle complex research challenges.''

''4)Technological Integration: Leverage technology, especially AI and data analytics, to aid in ensuring research consistency and integrity.''

''If we could change one thing, it would be the isolated nature of scientific endeavors prevalent in many regions, like Georgia. We would foster a globally interconnected research network where findings, methodologies, and tools are shared seamlessly, accelerating scientific progress and ensuring its robustness''”.

Lastly, the Georgian consortium highlights what they would change in the global reproducibility landscape if they could: “''1)Revise Academic Incentives: The current "publish or perish" culture sometimes prioritizes quantity over quality. We'd advocate for a system where researchers are rewarded for the reproducibility and integrity of their work, not just the volume. 2)Enhanced Training: Incorporate reproducibility and Open Science training at early academic stages, ensuring that upcoming researchers are well-equipped with the necessary skills and ethos. 3)Global Collaboration Platforms: Creation of digital platforms that facilitate global collaboration, data sharing, and mutual validation of research findings, breaking down silos and fostering a truly global scientific community''.”

==== Serbian Consortium ====
[[File:Serbian RN.png|center|thumb]]
<span lang="EN-US">[https://tier2-project.eu/ TIER2] is excited to announce the winner of the 2024 Open Call aimed at fostering the establishment of a third Reproducibility Network (RN) in “Widening Participation” countries - Serbia. The goal of Reproducibility Networks is to promote rigorous research practices, facilitate interdisciplinary collaborations and discussions, and enhance the trustworthiness of scientific work. The Serbian consortium will thus receive a €5,000 grant to organise an initial meeting, laying the groundwork for establishing an RN in their country.</span>

<span lang="EN-US">The Serbian consortium, consisting of nine organisations – six institutes and three faculties –, brings together diverse academic backgrounds with a shared commitment to improving research culture in Serbia. They focus on integrating Open Science, reproducibility, and inclusive policies into institutions and education. The consortium has previously collaborated on initiatives like the [https://nitra.gov.rs/en/ Team for Open Science in Serbia] and [https://nitra.gov.rs/en/inovacije/projekat-saige the Saige project], organising workshops and training to promote open science practices.</span>

<span lang="EN-US">Motivated by challenges such as low research investment and a scientific system that prioritises quantity over quality, they believe establishing a Reproducibility Network will enhance collaboration and help to address these issues. In the short term, they plan to promote the network through conferences, a kick-off event, and online platforms. Long-term, they aim to integrate Open Science into curricula, incentivise reproducibility, support initiatives beyond major centers, advocate for policy changes, and build international collaborations.</span>

<span lang="EN-US">Their vision for global reproducibility is one where research is transparent, ethical, and rigorous:</span>

<span lang="EN-US">''“In this ideal state, researchers across all disciplines adhere to principles of Open Science, ensuring that their methods, data, and results are accessible and reproducible.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

<span lang="EN-US">They advocate for integrating these principles into education, establishing incentive systems, and fostering collaboration:</span>

<span lang="EN-US">''“We should integrate reproducibility and Open Science practices into university curricula and professional development programs to equip researchers with the necessary skills and knowledge to conduct reproducible research.”''</span>

<span lang="EN-US">– Matija Zlatar on behalf of the Serbian consortium</span>

====Not sure, if your country has an established Reproducibility Network?====
<span lang="EN-GB">Visit the Global Networks page hosted by the UKRN to find out if a Reproducibility Network already exists in your country: https://www.ukrn.org/global-networks/.</span> <div></div>
}}
{{Instruction Step Trainee
|Instruction Step Title=Stakeholder communities
|Instruction Step Text=x
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{{Instruction Step Trainee
|Instruction Step Title=Primers Inititative
|Instruction Step Text=<span lang="EN-US">The primer initiative from the United Kingdom Reproducibility Network was designed introduce a broad audience to important topics and aspects of open and reproducible scholarship. Each primer is a 3-to-4-page summary document which describes the open or reproducible research practice, why one might be interested in it, and how they can be applied or adopted with thorough guidance.</span>

More information on the Primers Initative can be found here: <u>[https://www.ukrn.org/primers/ <span lang="EN-US">https://www.ukrn.org/primers/</span>]</u> .
}}
{{Instruction Step Trainee
|Instruction Step Title=Consortia Partners
|Instruction Step Text=<span lang="EN-US">TIER2 brings a unique combination of skills and perspectives, consisting of eleven partners from seven countries, well spread across Europe. The partner organisations all bring a wealth of expertise and experience regarding the target communities (computer science, life science, social science), research culture reform, technical aspects of infrastructure and services, as well as expertise in social sciences and humanities, and gender aspects of R&I. </span>

==[https://irise-project.eu/ iRise]==
[[File:IRISE .png|thumb]]
iRise aims to deepen understanding of reproducibility drivers, evaluate their effectiveness and provide concrete solutions to enhance scientific evidence.

Their direct objectives are:

- Develop working definitions and a general framework for diagnosing and addressing reproducibility problems, define costs, benefits and opportunities, and assess the utility of theoretical evidence in forecasting the success of interventions.

- Perform scoping and systematic reviews to identify and evaluate existing interventions to improve reproducibility.

- Explore the interface between reproducibility and research culture, and in particular considerations and mainstreaming of equity, diversity, and inclusion (EDI).

- Consult and engage key stakeholder groups in prioritising practices and practical tool development for adoption to increase reproducibility.

- Test efficacy and feasibility of specific interventions to increase reproducibility.

==[https://osiris4r.eu/ OSIRIS]==
[[File:OSIRIS .png|thumb]]
Open Science to Increase Reproducibility in Science (OSIRIS) aims to facilitate the shift by systematically gathering knowledge on the underlying drivers, testing effective evidence-based solutions, identifying incentives for reproducibility by stakeholders, and embedding reproducibility in research design.
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Consortia of Ukraine and Georgia RNs

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Members of the Serbian RN

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{{Instruction
|Title=What is reproducibility?
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=This module provides an in-depth introduction to reproducibility through the work of TIER2 and iRise. The purpose and concept of reproducibility is introduced, working definitions are provided for important concepts in relation to reproducibility and replicability, and the futures of reproducibility and illustrated from the perspective of different stakeholders.
|Has Duration=2
|Important For=All stakeholders in research; Funders; Publishers; Researchers
}}
{{Custom TabContent Trainee Open}}
{{Instruction Steps Foldout Trainee}}
{{Instruction Perspective Trainee}}
{{Instruction Step Trainee
|Instruction Step Title=Enabling and Redoing
|Instruction Step Text=The research team within TIER2 present an analytical framework that supports epistemic diversity by examining the potential relevance and degree of feasibility of reproducibility for different modes of knowledge production. The research team find current general typologies with the same aim wanting. They propose top-down derived enumerative lists of kinds of reproducibility organised according to vaguely defined fields, disciplines, methods or so-called research types. Current typologies cannot sufficiently characterise different kinds of research and their varying research context at the granularity needed to deal with how epistemic diversity and reproducibility relate. They also do not clarify the prevailing conceptual confusion surrounding reproducibility and replication. To clarify matters, they propose ''redoing'' to commonly describe the acts of reproducing and replicating and ''enabling'' to describe the acts of making something reproducible and replicable. They suggest mapping practices and epistemic functions to characterise what parts of a study should be redone or enabled and for what intended purposes. The research team propose knowledge production modes (KPM) as an organising construct to situate redoing and enabling within knowledge production’s epistemic, social, and contextual conditions. Epistemologies determine epistemic norms and criteria. Social conditions influence how research is organised, practised, rewarded, reported, and discussed. Contextual conditions put boundaries and restrictions on research, for example, due to subject matter, environment, availability of resources, and technologies, which are the ‘local’ conditions. Their framework clarifies the potential ''relevance'' of redoing and the degree of ''feasibility'' of redoing and enabling for a specific knowledge production mode. Relevance comprises research goals and epistemology. Epistemology is the basic assumption behind knowledge production modes. It determines how knowledge claims are produced and justified with systems of justification, the criteria for good/trustworthy research, and, thus, the epistemic norms. Different ways of knowing have different epistemic norms, practices, and criteria. Feasibility comprises the nature and complexity of the subject under investigation, the necessary investment for redoing or enabling, and the degree of theoretical and methodological uncertainty associated with the actual research. The proposed framework works bottom-up in that knowledge production modes are not defined a priori but derived from the analytical framework. The framework, therefore, supports epistemic diversity by being open and non-hierarchical and working at a sufficient level of granularity to discern the diverse conditions of knowledge production. The research team propose a framework that can clarify, not a cookbook. Enabling in some form always seems relevant in empirical work irrespective of ways of knowing—the same is not true for redoing.

For the full paper click here: [https://osf.io/preprints/metaarxiv/ujnd9_v1 MetaArXiv Preprints - Knowledge Production Modes: The Relevance and Feasibility of Reproducibility]

'''Reference'''

Ulpts, S., & Schneider, J. W. (2023, September 25). Knowledge Production Modes: The Relevance and Feasibility of Reproducibility. <nowiki>https://doi.org/10.31222/osf.io/ujnd9</nowiki>
}}
{{Instruction Step Trainee
|Instruction Step Title=Defining Reproducibility
|Instruction Step Text=Defining reproducibility and replicability, has been a challenge in the research community, as different interpretations and even contradicting definitions are often used. Defining these terms has proven to be challenging as their use and understanding differs between fields of research. However, the European funded iRise consortium developed a reproducibility glossary by critically reviewing existing scientific literature. The glossary provides working definitions for the use of terms reproducibility, replicability and replication, as well as related concepts.

'''References'''

Voelkl, B., Heyard, R., Fanelli, D., Wever, K., Held, L., Würbel, H., Zellers, S., & Maniadis, Z. (2024). Glossary of common terminology resulting from scoping reviews. https://osf.io/ewybt.
}}
{{Instruction Step Trainee
|Instruction Step Title=Futures of Reproducibility
|Instruction Step Text=<div>
<span lang="EN-GB">Improving reproducibility is a multifaceted challenge requiring both behavioural and cultural change.</span> <span lang="EN-US">The adoption of reproducibility practices has been sparked and embraced by the Open Science movement. However, a lot of researchers are not fully aware of the implications of reproducibility and how Open Science and reproducibility are connected and intertwined (Haven et al., 2022). To increase awareness and change research practices several steps should be taken (Nosek, 2019). First, the infrastructure for the desired behaviour should be provided to make it possible. Second, the user interface and experience of the infrastructure should be improved to make the behaviour easy. Third, communities of practice should be fostered to make the behaviour visible and so increasingly normative. Fourth, incentives to enact the behaviour should be provided to make it rewarding. Last, policies should be enacted to make the behaviour required (Nosek, 2019). To further this work, we sought to explore the future of reproducibility for different stakeholders and question what should be the next steps for reproducibility and how diverse epistemic contexts can adopt reproducibility in different forms. In this deliverable, we aim to add nuance to the reproducibility debate through flexible investigation of diverse epistemic contexts (researchers from the field of machine learning and researchers working with qualitative methods), exploring the future of reproducibility through the lens of diverse research stakeholders – researchers, funders, and publishers.</span>
</div><div>
<span lang="EN-US">In this context, we look to the future of reproducibility by exploring the preferred scenarios for multiple stakeholders, including how these scenarios can be realized. We reflect on the steps that are necessary for adherence to reproducibility-enabling practices and what different epistemic contexts need to make reproducibility a priority. Lastly, we reflect on what are the new problems that we may face when aiming to improve reproducibility. We believe exploring the possible futures for reproducibility is essential to discover the next steps for different members of the scientific community to take to realize the preferred future and the actions to avoid steering away from the dystopian futures.</span>
</div><div>
<span lang="EN-US">We aim to highlight the essential role of institutions, funders and publishers in this endeavor to make reproducibility a priority by recognizing, rewarding, evaluating and monitoring reproducibility. Ultimately, we hope to steer and move forward the debate on reproducibility in the research community by</span> <span lang="EN-GB">addressing a set of core research questions related to how key stakeholders in the academic community envision the way in which matters of reproducibility should be addressed in the future. More specifically, it asks representatives from research funders, scholarly publishers, and researchers from diverse disciplinary backgrounds:</span>
</div><div>
<span lang="EN-GB">1. What are the preferred futures of reproducibility?</span>
</div><div>
<span lang="EN-GB">2. What are the enablers and barriers on the way to the preferred future or reproducibility more generally?</span>
</div><div>
Below we present the results of our study below.
</div>

For more information, please refer to the full paper: [https://osf.io/preprints/metaarxiv/gx9jq_v1 MetaArXiv Preprints - How to get there from here? Barriers and enablers on the road towards reproducibility in research].
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2025-04-08T10:03:35Z

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0009-0002-1788-6517:

{{Instruction
|Title=What is reproducibility?
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=This module provides an in-depth introduction to reproducibility through the work of TIER2 and iRise. The purpose and concept of reproducibility is introduced, working definitions are provided for important concepts in relation to reproducibility and replicability, and the futures of reproducibility and illustrated from the perspective of different stakeholders.
|Has Duration=2
|Important For=All stakeholders in research; Funders; Publishers; Researchers
}}
{{Custom TabContent Trainee Open}}
{{Instruction Steps Foldout Trainee}}
{{Instruction Perspective Trainee}}
{{Instruction Step Trainee
|Instruction Step Title=Enabling and Redoing
|Instruction Step Text=<span lang="EN-GB">The research team within TIER2 present an analytical framework that supports epistemic diversity by examining the potential relevance and degree of feasibility of reproducibility for different modes of knowledge production. The research team find current general typologies with the same aim wanting. They propose top-down derived enumerative lists of kinds of reproducibility organised according to vaguely defined fields, disciplines, methods or so-called research types. Current typologies cannot sufficiently characterise different kinds of research and their varying research context at the granularity needed to deal with how epistemic diversity and reproducibility relate. They also do not clarify the prevailing conceptual confusion surrounding reproducibility and replication. To clarify matters, they propose ''redoing'' to commonly describe the acts of reproducing and replicating and ''enabling'' to describe the acts of making something reproducible and replicable. They suggest mapping practices and epistemic functions to characterise what parts of a study should be redone or enabled and for what intended purposes. The research team propose knowledge production modes (KPM) as an organising construct to situate redoing and enabling within knowledge production’s epistemic, social, and contextual conditions. Epistemologies determine epistemic norms and criteria. Social conditions influence how research is organised, practised, rewarded, reported, and discussed. Contextual conditions put boundaries and restrictions on research, for example, due to subject matter, environment, availability of resources, and technologies, which are the ‘local’ conditions. Our framework clarifies the potential ''relevance'' of redoing and the degree of ''feasibility'' of redoing and enabling for a specific knowledge production mode. Relevance comprises research goals and epistemology. Epistemology is the basic assumption behind knowledge production modes. It determines how knowledge claims are produced and justified with systems of justification, the criteria for good/trustworthy research, and, thus, the epistemic norms. Different ways of knowing have different epistemic norms, practices, and criteria. Feasibility comprises the nature and complexity of the subject under investigation, the necessary investment for redoing or enabling, and the degree of theoretical and methodological uncertainty associated with the actual research. The proposed framework works bottom-up in that knowledge production modes are not defined a priori but derived from the analytical framework. The framework, therefore, supports epistemic diversity by being open and non-hierarchical and working at a sufficient level of granularity to discern the diverse conditions of knowledge production. The research team propose a framework that can clarify, not a cookbook. Enabling in some form always seems relevant in empirical work irrespective of ways of knowing—the same is not true for redoing.</span>

For the full paper click here: [https://osf.io/preprints/metaarxiv/ujnd9_v1 MetaArXiv Preprints - Knowledge Production Modes: The Relevance and Feasibility of Reproducibility]

'''Reference'''

Ulpts, S., & Schneider, J. W. (2023, September 25). Knowledge Production Modes: The Relevance and Feasibility of Reproducibility. <nowiki>https://doi.org/10.31222/osf.io/ujnd9</nowiki>
}}
{{Instruction Step Trainee
|Instruction Step Title=Defining Reproducibility
|Instruction Step Text=Defining reproducibility and replicability, has been a challenge in the research community, as different interpretations and even contradicting definitions are often used. Defining these terms has proven to be challenging as their use and understanding differs between fields of research. However, the European funded iRise consortium developed a reproducibility glossary by critically reviewing existing scientific literature. The glossary provides working definitions for the use of terms reproducibility, replicability and replication, as well as related concepts.

'''References'''

Voelkl, B., Heyard, R., Fanelli, D., Wever, K., Held, L., Würbel, H., Zellers, S., & Maniadis, Z. (2024). Glossary of common terminology resulting from scoping reviews. https://osf.io/ewybt.
}}
{{Instruction Step Trainee
|Instruction Step Title=Futures of Reproducibility
|Instruction Step Text=<div>
<span lang="EN-GB">Improving reproducibility is a multifaceted challenge requiring both behavioural and cultural change.</span> <span lang="EN-US">The adoption of reproducibility practices has been sparked and embraced by the Open Science movement. However, a lot of researchers are not fully aware of the implications of reproducibility and how Open Science and reproducibility are connected and intertwined (Haven et al., 2022). To increase awareness and change research practices several steps should be taken (Nosek, 2019). First, the infrastructure for the desired behaviour should be provided to make it possible. Second, the user interface and experience of the infrastructure should be improved to make the behaviour easy. Third, communities of practice should be fostered to make the behaviour visible and so increasingly normative. Fourth, incentives to enact the behaviour should be provided to make it rewarding. Last, policies should be enacted to make the behaviour required (Nosek, 2019). To further this work, we sought to explore the future of reproducibility for different stakeholders and question what should be the next steps for reproducibility and how diverse epistemic contexts can adopt reproducibility in different forms. In this deliverable, we aim to add nuance to the reproducibility debate through flexible investigation of diverse epistemic contexts (researchers from the field of machine learning and researchers working with qualitative methods), exploring the future of reproducibility through the lens of diverse research stakeholders – researchers, funders, and publishers.</span>
</div><div>
<span lang="EN-US">In this context, we look to the future of reproducibility by exploring the preferred scenarios for multiple stakeholders, including how these scenarios can be realized. We reflect on the steps that are necessary for adherence to reproducibility-enabling practices and what different epistemic contexts need to make reproducibility a priority. Lastly, we reflect on what are the new problems that we may face when aiming to improve reproducibility. We believe exploring the possible futures for reproducibility is essential to discover the next steps for different members of the scientific community to take to realize the preferred future and the actions to avoid steering away from the dystopian futures.</span>
</div><div>
<span lang="EN-US">We aim to highlight the essential role of institutions, funders and publishers in this endeavor to make reproducibility a priority by recognizing, rewarding, evaluating and monitoring reproducibility. Ultimately, we hope to steer and move forward the debate on reproducibility in the research community by</span> <span lang="EN-GB">addressing a set of core research questions related to how key stakeholders in the academic community envision the way in which matters of reproducibility should be addressed in the future. More specifically, it asks representatives from research funders, scholarly publishers, and researchers from diverse disciplinary backgrounds:</span>
</div><div>
<span lang="EN-GB">1. What are the preferred futures of reproducibility?</span>
</div><div>
<span lang="EN-GB">2. What are the enablers and barriers on the way to the preferred future or reproducibility more generally?</span>
</div><div>
Below we present the results of our study below.
</div>

For more information, please refer to the full paper: [https://osf.io/preprints/metaarxiv/gx9jq_v1 MetaArXiv Preprints - How to get there from here? Barriers and enablers on the road towards reproducibility in research].
}}
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|Has Good Practice And Misconduct=Reproducibility
}}

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{{Instruction
|Title=What is the evidence for reproducibility in different epistemic contexts?
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=Conceptions, roles & pertinence of reproducibility are closely linked to different principal modes of knowledge production within & across research fields, so-called ‘epistemic contexts’. TIER2 mapped the contextual factors to various dimensions of ‘reproducibility’, as well as pertinent framework conditions (e.g., political, ethical, social, legal) that may affect the uptake of reproducibility practices in qualitative and machine learning fields. The literature reviews enabled analyses of diverse conceptions, roles & barriers of reproducibility & permits identification of relevant & targeted tools.
|Has Duration=1
|Important For=Academic institutions; All stakeholders in research; Funders; Publishers; researchers; reserach integrity offices
}}
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{{Instruction Step Trainee
|Instruction Step Title=Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers
|Instruction Step Text="Many research fields are currently reckoning with issues of poor levels of reproducibility. Some label it a "crisis", and research employing or building Machine Learning (ML) models is no exception. Issues including lack of transparency, data or code, poor adherence to standards, and the sensitivity of ML training conditions mean that many papers are not even reproducible in principle. Where they are, though, reproducibility experiments have found worryingly low degrees of similarity with original results. Despite previous appeals from ML researchers on this topic and various initiatives from conference reproducibility tracks to the ACM's new Emerging Interest Group on Reproducibility and Replicability, we contend that the general community continues to take this issue too lightly. Poor reproducibility threatens trust in and integrity of research results. Therefore, in this article, we lay out a new perspective on the key barriers and drivers (both procedural and technical) to increased reproducibility at various levels (methods, code, data, and experiments). We then map the drivers to the barriers to give concrete advice for strategies for researchers to mitigate reproducibility issues in their own work, to lay out key areas where further research is needed in specific areas, and to further ignite discussion on the threat presented by these urgent issues."

Find the full paper here: [https://arxiv.org/abs/2406.14325 Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers]

References:

Semmelrock, H., Ross-Hellauer, T., Kopeinik, S., Theiler, D., Haberl, A., Thalmann, S., & Kowald, D. (2024). Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers. ''arXiv preprint arXiv:2406.14325''.
}}
{{Instruction Step Trainee
|Instruction Step Title=Reproducibility and replicability of qualitative research: an integrative review of concepts, barriers and enablers
|Instruction Step Text=<blockquote>"The integrative review presented here examines how reproducibility and replicability are conceptualized and discussed in relation to qualitative research, and which factors and practices enable or undermine them. Both peer-reviewed and grey English-language literature that address reproducibility and/or Open Science in relation to qualitative research were eligible for inclusion. Initial searches were conducted in Scopus, Web of Science, Dimensions, PubMed, APA PsychInfo, and JSTOR, and followed with snowball sampling from included literature. Studies were screened and both quantitative and qualitative data were extracted using the SyRF online platform, with 248 papers included. We found that conceptualizations that stem from quantitative standpoints are overwhelmingly framed as inappropriate practices and epistemic criteria for (most) qualitative research. When conceptualized in alternative ways that are adapted to the epistemic conditions, aims and practices of qualitative research, they can be both applicable and appropriate. Key barriers include the ontological and epistemological misalignment of reproducibility, replicability and Open Science and qualitative research, and ethical and practical concerns surrounding data sharing and reuse. Key enablers include practices that respond to ethical and practical concerns around data sharing and reuse (anonymization, ethical consent practices, context documentation, and ethical access management), adapting expectations and norms of openness, and established qualitative practices including documentation, reflexivity, and considering positionality. We conclude that reproducibility, replicability and Open Science practices must be adapted to the aims and epistemic conditions of qualitative research for them to be applicable and feasible, and that they will not always be both for all qualitative research."

Find the full paper here: [https://osf.io/preprints/metaarxiv/n5zkw_v1 MetaArXiv Preprints - Reproducibility and replicability of qualitative research: an integrative review of concepts, barriers and enablers].</blockquote>

Reference:

Cole, N. L., Ulpts, S., Bochynska, A., Kormann, E., Good, M., Leitner, B., & Ross-Hellauer, T. (2024, December 23). Reproducibility and replicability of qualitative research: an integrative review of concepts, barriers and enablers. <nowiki>https://doi.org/10.31222/osf.io/n5zkw_v1</nowiki>
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Instruction:26f898cb-a1e1-485c-b3d3-e7cc564d6dac

2025-04-03T11:27:55Z

0009-0002-1788-6517:

{{Instruction
|Title=What is the evidence for reproducibility in different epistemic contexts?
|Has Related Initiative=Initiative:286109fc-03cb-4a08-bd45-c0276eae3079
|Instruction Goal=Conceptions, roles & pertinence of reproducibility are closely linked to different principal modes of knowledge production within & across research fields, so-called ‘epistemic contexts’. TIER2 mapped the contextual factors to various dimensions of ‘reproducibility’, as well as pertinent framework conditions (e.g., political, ethical, social, legal) that may affect the uptake of reproducibility practices in qualitative and machine learning fields. The literature reviews enabled analyses of diverse conceptions, roles & barriers of reproducibility & permits identification of relevant & targeted tools.
|Has Duration=1
|Important For=Academic institutions; All stakeholders in research; Funders; Publishers; researchers; reserach integrity offices
}}
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{{Instruction Step Trainee
|Instruction Step Title=Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers
|Instruction Step Text="Many research fields are currently reckoning with issues of poor levels of reproducibility. Some label it a "crisis", and research employing or building Machine Learning (ML) models is no exception. Issues including lack of transparency, data or code, poor adherence to standards, and the sensitivity of ML training conditions mean that many papers are not even reproducible in principle. Where they are, though, reproducibility experiments have found worryingly low degrees of similarity with original results. Despite previous appeals from ML researchers on this topic and various initiatives from conference reproducibility tracks to the ACM's new Emerging Interest Group on Reproducibility and Replicability, we contend that the general community continues to take this issue too lightly. Poor reproducibility threatens trust in and integrity of research results. Therefore, in this article, we lay out a new perspective on the key barriers and drivers (both procedural and technical) to increased reproducibility at various levels (methods, code, data, and experiments). We then map the drivers to the barriers to give concrete advice for strategies for researchers to mitigate reproducibility issues in their own work, to lay out key areas where further research is needed in specific areas, and to further ignite discussion on the threat presented by these urgent issues."

Find the full paper here: [https://arxiv.org/abs/2406.14325 Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers]

References:

Semmelrock, H., Ross-Hellauer, T., Kopeinik, S., Theiler, D., Haberl, A., Thalmann, S., & Kowald, D. (2024). Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers. ''arXiv preprint arXiv:2406.14325''.
}}
{{Instruction Step Trainee
|Instruction Step Title=Reproducibility and replicability of qualitative research: an integrative review of concepts, barriers and enablers
|Instruction Step Text=<blockquote>"The integrative review presented here examines how reproducibility and replicability are conceptualized and discussed in relation to qualitative research, and which factors and practices enable or undermine them. Both peer-reviewed and grey English-language literature that address reproducibility and/or Open Science in relation to qualitative research were eligible for inclusion. Initial searches were conducted in Scopus, Web of Science, Dimensions, PubMed, APA PsychInfo, and JSTOR, and followed with snowball sampling from included literature. Studies were screened and both quantitative and qualitative data were extracted using the SyRF online platform, with 248 papers included. We found that conceptualizations that stem from quantitative standpoints are overwhelmingly framed as inappropriate practices and epistemic criteria for (most) qualitative research. When conceptualized in alternative ways that are adapted to the epistemic conditions, aims and practices of qualitative research, they can be both applicable and appropriate. Key barriers include the ontological and epistemological misalignment of reproducibility, replicability and Open Science and qualitative research, and ethical and practical concerns surrounding data sharing and reuse. Key enablers include practices that respond to ethical and practical concerns around data sharing and reuse (anonymization, ethical consent practices, context documentation, and ethical access management), adapting expectations and norms of openness, and established qualitative practices including documentation, reflexivity, and considering positionality. We conclude that reproducibility, replicability and Open Science practices must be adapted to the aims and epistemic conditions of qualitative research for them to be applicable and feasible, and that they will not always be both for all qualitative research."

Find the full paper here: [https://osf.io/preprints/metaarxiv/n5zkw_v1 MetaArXiv Preprints - Reproducibility and replicability of qualitative research: an integrative review of concepts, barriers and enablers].</blockquote>Reference:

Cole, N. L., Ulpts, S., Bochynska, A., Kormann, E., Good, M., Leitner, B., & Ross-Hellauer, T. (2024, December 23). Reproducibility and replicability of qualitative research: an integrative review of concepts, barriers and enablers. <nowiki>https://doi.org/10.31222/osf.io/n5zkw_v1</nowiki>
}}
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Instruction:7c159fc9-db27-4623-9432-9c37b8889f89

2025-04-02T14:43:02Z

0009-0002-1788-6517:

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2025-04-02T14:36:02Z

0009-0002-1788-6517:

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0009-0002-1788-6517:

Logo for the Horizon Project OSIRIS