Text (Instruction Step Text)
From The Embassy of Good Science
Describe the actions the user should take to experience the material (including preparation and follow up if any). Write in an active way.
- ⧼SA Foundation Data Type⧽: Text
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<span lang="EN-US">The aim of this activity is to invite participants to '''reflect''' on their '''expectations'''. This is useful both for trainers and participants.</span>
<span lang="EN-US">'''Trainers can pick between two possible activities:'''</span>
<span lang="EN-US">'''OPTION 1:'''</span>
<span lang="EN-US">''Mind map activity → small group activity: in sub-groups participants create a mind map of their current knowledge on the topic.''</span>
<span lang="EN-US">The following steps can support trainers in organizing this activity:</span><div>
*<span lang="EN-US">Divide participants into subgroups.</span>
*<span lang="EN-US">Provide each group with a digital (or physical) board.</span>
*<span lang="EN-US">Ask them to brainstorm and write down the words that come to mind when they think of "gene editing."</span>
*<span lang="EN-US">Ask them to divide the terms into:</span>
-Topics they want to learn more about.
<span lang="EN-US">-Topics they are already familiar with.</span>
</div>
*<span lang="EN-US">After 6-7 minutes of discussion in sub-groups, ask all groups share their maps with the group. Together with the group select the most common unknown topics.</span>
<span lang="EN-US">'''OPTION 2:'''</span>
<span lang="EN-US">''Learning goals with Mentimeter''</span>
<div>
*<span lang="EN-US">Prepare and share a Mentimeter (or similar tool) with the following question: ''after this session I expect to be able to…''</span>
*<span lang="EN-US">Ask participants to submit two goals, project the results and discuss them with the group.</span> </div><div></div> +
This clip explains the basics of benefit sharing, which is an instrument to increase justice in international research and cross-border access to resources. In the context of the UN Convention on Biological Diversity, benefit sharing is contribution-based, i.e. those who contribute to a project or research should benefit from its outcomes. In the context of the UNESCO Universal Declaration on Bioethics and Human Rights, the benefits of research should be shared with all of society, independent of contribution. +
In times of crisis, policy-makers urgently need advice from researchers. Can such advice take ethical values into consideration? [https://prepared-project.eu/ PREPARED] developed an ethics brief format around fairness, respect, care and honesty and launched a first brief with [https://www.nature.com/articles/d41586-023-01014-z NATURE coverage] in April 2023. The PREPARED team met at the UNESCO headquarters in Paris in early June. Watch this annotated video and learn more about bringing ethics into policy making.
Click below to watch the annotated video. +
[[File:Donating Samples.png|center|frameless|600x600px]]
Alison, a 42-year-old woman in robust health, was invited to contribute to scientific advancement by donating biological material along with health-related information (data) to a biobank. Alison explained to her friends and family that she wanted to contribute to medical research ‘to give something back’ after seeing her father’s successful treatment for cancer.
The biobank provided Alison with detailed information about the purpose of the biobank, the types of samples and data needed, risks and potential benefits related to the donation to biobanking and the right to withdraw consent.
Alison then gave her consent to the donation process, acknowledging her understanding and agreement to participate.
Before donating the samples, Alison underwent a thorough screening process which included a review of her medical history and a physical examination.
The samples were carefully labelled, processed, and stored in secure, controlled environments. Storage conditions also comply with stringent ethical and privacy protocols, ensuring the preservation of Alison’s privacy and confidentiality.
Alison was told that her personal information would be de-identified or pseudonymized to protect her identity. As part of the consent process, Alison also gave permission for the biobank to contact her in the future to follow up on her health as she ages and potentially invite her to participate in further studies beyond the scope of her original donation. Maintaining contact with donors is crucial for biobanks when samples are used for longitudinal studies or when follow-up health information is needed.
Alison's donation is now part of a valuable resource for researchers studying various health conditions, including genetic predispositions and disease markers. Her contribution will allow scientists to conduct longitudinal studies, advancing the understanding of health and potential breakthroughs in personalized medicine. Alison's decision exemplifies the vital role individuals can play in shaping the future of medical research through biobank donations.
[[File:Mexican town hall.jpg|alt=mexican town hall|center|frameless|600x600px|mexican town hall]]
What ethics issues can you identify in the cases mentioned in this short video? You can download the text if you wish to help you formulate your thoughts. +
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In November 2018, an international news story broke about a scientist in China who had genetically altered a gene in human embryos that had resulted in the birth of IVF twins, Lulu and Nana. The gene editing involved the use of CRISPR-Cas9 technology to disable the CCR5 gene with the aim that this would lead to HIV resistance. The scientist, He Jiankui, introduced the CRISPR technology very soon after the embryos were created when they were formed of only one cell each. He Jiankui’s actions were widely condemned as unethical, and the news sparked intense debate about the potential impacts upon the children.
How might this genetic modification affect the development, the health and the wellbeing of Lulu and Nana? In the years since their birth there have been many rumours and suggestions about the impacts, including that the twins have enhanced memories and learning abilities, and others that their lives will be shortened. We don’t yet know what attributes can be attributed to the gene editing. +
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VR and AR are used in a very wide range of applications across various industries. +
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What is Hunter syndrome?
Hunter syndrome is a rare genetic disorder that primarily affects males. It is part of a group of diseases known as mucopolysaccharidoses or MPS, which are caused by the body's inability to break down certain complex sugars called glycosaminoglycans or GAGs. For people with Hunter syndrome, a lack of the enzyme iduronate-2-sulfatase or IDS, means that GAGs build up inside the body leading to a wide variety of symptoms including developmental issues, physical problems and mental decline. For example:
*Physical development impacts like coarse facial features, thickened skin, enlarged tongue, and joint stiffness.
*Developmental delays in children affecting motor skills, speech, and learning.
*Respiratory problems with frequent respiratory infections, sleep apnoea, and other breathing difficulties.
*Hearing loss.
*Enlarged liver and spleen, leading to abdominal distension.
*Heart problems with heart valve abnormalities and other cardiac issues.
*Skeletal abnormalities like joint stiffness, short stature, and abnormal bone development.
The onset of the disease is usually between the ages of 2 and 4 years and developmental decline is usually evident between the ages of 18 and 36 months.
There is currently no cure for Hunter syndrome, but treatments can help to manage the symptoms and improve quality of life. Options include:
#Enzyme replacement therapy (ERT). Regular, often weekly, infusions of a synthetic version of the missing enzyme can help reduce the buildup of GAGs. However, the enzyme is not able to pass the blood-brain-barrier, so this form of treatment does not help to protect against brain damage.
*Symptomatic treatments for specific issues including physical therapy for joint problems, medications for respiratory and heart problems, and surgical interventions for specific complications.
Despite treatment, those with severe disease usually die in their teens. Those with a milder form of Hunter syndrome might live with more gradual deterioration in health until middle age.
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Malaria remains one of the leading causes of morbidity and mortality in Sub-Saharan Africa, particularly in rural regions. Despite significant efforts to curb transmission, the disease persists, with complex transmission patterns that vary based on environmental, social, and biological factors. With the recent rise of artificial intelligence (AI) and big data analytics, new tools are now available to understand and predict disease outbreaks more precisely.
'''Principal Investigators'''
Professor Smith (based in the US) and Dr Jones (based in the EU).
'''Aims'''
This project proposes to use AI and machine learning (ML) algorithms to analyse large datasets of malaria transmission in rural regions of Sub-Saharan Africa. Data will be collected on environmental variables, human behaviour, and mosquito population dynamics to build predictive models. The goal is to use AI to identify hotspots of malaria transmission, optimise intervention strategies, and contribute to global malaria eradication efforts.
'''Research Objectives'''
#To develop AI-driven predictive models of malaria transmission in rural regions of Sub-Saharan Africa based on environmental, behavioural, and biological factors.
#To collect and analyse large datasets on malaria incidence, mosquito populations, and environmental variables (e.g., temperature, humidity, rainfall).
#To provide recommendations to international health organisations on optimal malaria intervention strategies based on AI-predicted transmission patterns.
'''Research Questions'''
#How can AI and machine learning be used to predict malaria transmission patterns in rural Sub-Saharan Africa?
#What environmental, social, and biological factors are most strongly correlated with malaria transmission in these regions?
#How can AI models optimise intervention strategies for malaria control in low-resource settings?
'''Methodology'''
This study will employ AI and machine learning techniques to analyse large-scale data on malaria transmission. Data will be collected from remote rural areas in Sub-Saharan Africa, specifically focusing on regions in Tanzania, Uganda, and Mozambique, where malaria prevalence is high.
'''Ethics'''
Ethics approval is being sought from both Professor Smith’s and Dr Jones’ home institutions in the US and in the EU.
'''Phase 1: Data Collection'''
*Environmental Data: Remote sensing and satellite data will be used to gather information on environmental variables such as temperature, rainfall, and vegetation patterns.
*Human Behaviour Data: Survey data on human behaviour related to malaria prevention (e.g., use of bed nets, travel patterns) will be collected through short field visits conducted by external researchers.
*Biological Data: Data on mosquito populations and malaria incidence will be collected through partnerships with local healthcare facilities and mosquito trapping activities.
'''Phase 2: AI Model Development'''
*Machine Learning Algorithms: AI algorithms, including neural networks and decision trees, will be used to analyse the datasets and identify the key factors driving malaria transmission.
*Predictive Modelling: AI models will be trained to predict malaria outbreaks based on the environmental, social, and biological data collected.
'''Phase 3: Reporting and Recommendations'''
*The AI models will be used to provide recommendations for optimising malaria interventions (e.g., bed net distribution, insecticide spraying) in the study regions.
*Results will be published in high-impact international journals and shared with international health organisations.
'''Expected Outcomes'''
#Publication of Results: The research team expects to publish multiple papers in high-impact journals on the application of AI for malaria control, potentially advancing careers in academia and international research.
#Recommendations to International Organisations: AI-driven recommendations on malaria interventions will be shared with global health organisations like the WHO and major NGOs working in malaria control, without direct engagement with local policymakers or healthcare systems.
'''Timeline'''
*Months 1-3: Initial literature review, AI model development, and planning for data collection trips.
*Months 4-9: Data collection in Tanzania, Uganda, and Mozambique.
*Months 10-15: AI model training, data analysis, and predictive model development.
*Months 16-18: Reporting, writing, and submission of research papers.
'''Budget'''
The total estimated budget for this project is $1.2 million, covering:
*Travel expenses for international researchers conducting field visits.
*Equipment for data collection, including satellite imagery access, mosquito traps, and environmental sensors.
*AI development and data analysis software.
*Compensation for local healthcare workers and logistical support in the field.
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Let’s find out more about the proposed study. While working through the presentation, make a note of any points or questions that arise for you about the potential benefits and risks associated with this study. +
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The primary issues related to Extended Reality data processing concern privacy and confidentiality, data security and breaches, the volume of data extracted, and the lack of clarity around the sharing of information.
'''Feedback'''
XR platforms and applications can collect many different types of personal data from users. This includes biometric information (such as facial expressions or eye movements), location data and device identifiers, as well as potentially sensitive content from personal conversations, or confidential information that is shared within virtual environments.
As the technology develops, so new types of data are being processed. For instance, eye tracking technology has the potential to gather highly sensitive data about individuals, including their gaze patterns, attentional focus, and emotional responses. This can be used to reveal personal preferences (including sensitive areas like sexual preferences), and certain health conditions, like autism and attention-deficit/hyperactivity disorder (ADHD). +
<span lang="EN-GB">Define the broader (socio-economic, political) and narrower (institutional) context of the problem to be solved. Consider all background issues that can have a direct or indirect influence on the successful implementation of the recommendation. List general assumptions that you can make about the recommendation, i.e. list all those educated premises that you consider as a starting point for an effective application scenario. These assumptions are the starting points on which further reasoning and development of the scenario can be built. These assumptions can vary in nature and might relate to specific contexts like economics or social interactions.</span>
<span lang="EN-GB">· What is the core problem that needs to be solved to foster trust in science? What are the basic assumptions on which the application scenario can be built on?</span>
<span lang="EN-GB">· What are the socio-economic, political, and cultural aspects that fundamentally shape the implementation of the recommendation?</span>
<span lang="EN-GB">· What are the main organisational or institutional settings that potentially affect the implementation of the recommendation?</span> +
Research coordination and cooperation are essential to avoid the unnecessary duplication of studies, which could place unfair burdens on participants and waste time and resources. +
This step explores the environmental impacts of generative AI across its lifecycle: from training, deployment, and inference to hardware and infrastructure. +
Doing research with communities affected by climate change: Climate-conscious methodologies matrix (for researchers and ethics reviewers) +
Please complete the multiple answers mini quiz +
What if innovation projects were designed with nature in mind? Multispecies Thinking broadens our perspective, recognizing the interconnectedness of all life forms and the need to include non-human beings in our ethical and research considerations. Designer Liina Lember explores how light pollution might be tackled from the perspective of another species. View the slideshow on “In-Visible Moth Spells” and notice how it makes you feel. +
===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. ]] +
In this lecture, Rosemarie Barnabe discusses how different stakeholders – researchers, the broader research community, and the general public – can benefit from Open Science. The lecture introduces components of Open Science and explains how these components benefit different stakeholders.
'''Watch the lecture and then answer the questions.'''
'''Further reading:'''
UNESCO Recommendation on Open Science. (2021) https://doi.org/10.54677/MNMH8546
Tennant, J. P., Waldner, F., Jacques, D. C., Masuzzo, P., Collister, L. B., & Hartgerink, C. H. J. (2016). The academic, economic and societal impacts of Open Access: An evidence-based review (5:632). F1000Research. https://doi.org/10.12688/f1000research.8460.3
Catalano, G., Delugas, E., & Vignetti, S. (2025). Costs and Benefits of Open Science: Contributing to the Development of a Rigorous Assessment Framework. In J. Gutleber & P. Charitos (Eds.), The Economics of Big Science 2.0: Essays by Leading Scientists and Policymakers (pp. 127–135). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-60931-2_10
Arza, V., & Fressoli, M. (2017). Systematizing benefits of open science practices. Information Services and Use, 37(4), 463–474. https://doi.org/10.3233/ISU-170861
Meskus, M., Marelli, L., & D’Agostino, G. (2017). Research Misconduct in the Age of Open Science: The Case of STAP Stem Cells. Science as Culture, 27(1), 1–23. https://doi.org/10.1080/09505431.2017.1316975 <div></div> +
Introduction to the evaluation of the effectiveness of Research Ethics and Integrity (REI) training +
Challenges in assessing training effectiveness are that results are limited through extensive missing data, heterogeneity of trainings and evaluation tools, short interventions not allowing sufficient time to induce change or development, and small sample sizes. As the goals of trainings differ, different tests are used to measure those goals, making comparisons difficult. In addition, measurements take a lot of time and labour to assess and analyse, especially if the data are qualitative and learners receive feedback on their learning and development. +
