Open Science, Open Access, FAIR Data
ModulesOpen Science, Open Access, FAIR Data
After completing this session, you will:
- Understand the concept of open science and explain its importance in the context of modern research practices.
- Explain the principles of open access and the benefits of making research outputs freely available to the public.
- Develop a comprehensive research data management plan (DMP) that addresses the organization, storage, and sharing of research data.
- Apply the FAIR data principles (Findable, Accessible, Interoperable, Reusable) to ensure that research data is properly managed and shared.
- Critically evaluate the impact of open science practices on research integrity, collaboration, and innovation.
Open Science
Open Science represents a new approach to the scientific process based on cooperative work and new ways of diffusing knowledge by using digital technologies and new collaborative tools.
What is open science?
Open Science is the practice of science in such a way that others can collaborate and contribute, where research data, lab notes and other research processes are freely available, under terms that enable reuse, redistribution and reproduction of the research and its underlying data and methods (FOSTER Open Science Definition).
According to the FOSTER taxonomy, "Open science is the movement to make scientific research, data and dissemination accessible to all levels of an inquiring society." It can be defined as a grouping of principles and practices:
- Principles: Open Science is about increased transparency, re-use, participation, cooperation, accountability and reproducibility for research. It aims to improve the quality and reliability of research through principles like inclusion, fairness, equity, and sharing. Open Science can be viewed as research simply done properly, and it extends across the Life and Physical Sciences, Engineering, Mathematics, Social Sciences, and Humanities (Open Science MOOC).
- Practices: Open Science includes changes to the way science is done - including opening access to research publications, data-sharing, open notebooks, transparency in research evaluation, ensuring the reproducibility of research (where possible), transparency in research methods, open source code, software and infrastructure, citizen science and open educational resources.
What are the benefits?
Open Science is about increased rigour, accountability, and reproducibility for research. It is based on the principles of inclusion, fairness, equity, and sharing, and ultimately seeks to change the way research is done, who is involved and how it is valued. It aims to make research more open to participation, review/refutation, improvement and (re)use for the world to benefit.
What is it about?
Open Science is not different from traditional science and applies to all research disciplines. It just means to carry out the research in a more transparent and collaborative way. Open Science is about extending the principles of openness to the whole research cycle, fostering sharing and collaboration as early as possible, thus entailing a systemic change to the way science and research are done.
There are several definitions of "openness" with regards to various aspects of science; the Open Definition defines it thus: "Open data and content can be freely used, modified, and shared by anyone for any purpose". Open Science encompasses a variety of practices, usually including areas like open access to publications, open research data, open source software/tools, open workflows, citizen science, open educational resources, and alternative methods for research evaluation, including open peer review.
The Open Science Training Handbook
Want to learn more? FOSTER consortium created an open, living handbook on Open Science training – The Open Science Training Handbook. This book offers comprehensive guidance and resources for Open Science instructors and trainers, as well as anyone interested in improving levels of transparency and participation in research practices. The focus of the handbook is not only spreading the ideas of Open Science, but showing how to spread these ideas most effectively.
Further reading:
The best thing you can do now to understand this particular issue better is to read this paper by Jean-Claude Burgelman and his colleagues: Open Science, Open Data, and Open Scholarship: European Policies to Make Science Fit for the Twenty-First Century.
Just read. You don't have to do anything else.
[1] FOSTER consortium. (2018). What is open science? https://zenodo.org/records/2629946
[2] FOSTER consortium. (2018). The open science training handbook. https://doi.org/10.5281/zenodo.1212496Open Science in Horizon Europe
Open science is a legal requirement under Horizon Europe. Its objective is to enhance transparency and trust, ultimately benefiting scientific research and EU citizens. In the EU, Open Science means enhancing research quality to ensure transparency and reproducibility, facilitating their utilization by both industry and society as a catalyst for growth.
To learn about how to comply with open science principles when applying for EU funding and implementing the project, you can visit the European Research Executive Agency's Q&A webpage or check out this leaflet on "Horizon Europe: Open Science – Early Knowledge and Data Sharing" for a quick orientation.
Open Research Europe
Open Research Europe is an open-access publishing platform for the publication of research stemming from European Commission funding across all subject areas, with no author fees. The platform makes it easy for European Commission beneficiaries to comply with the open access terms of their funding and offers researchers a publishing venue to share their results and insights rapidly and facilitate open, constructive research discussion. Open Research Europe operates under a continuous publication schedule.
[1] European Research Executive Agency. (2024). Open science. Open science in Horizon Europe. https://rea.ec.europa.eu/open-science_enVideo: Open Research Europe: The new EU open access publishing platform
"Meet the open-access publishing venue set up for Horizon Europe and Horizon 2020 beneficiaries. Open Research Europe will give everyone, researchers and citizens alike, immediate open access to your latest scientific discoveries. And at no cost to you." Watch the video below
Introducing the Open Access
Open Access to scientific publications is one of several other policies that will accelerate the move towards Open Science.
Open Access to publications means that research publications like articles and books can be accessed online, free of charge by any user, with no technical obstacles (such as mandatory registration or login to specific platforms). At the very least, such publications can be read online, downloaded and printed. Ideally, additional rights such as the right to copy, distribute, search, link, crawl and mine should also be provided.
Two routes of open access
Open Access can be realised through two main non-exclusive routes:
- Green Open Access (self-archiving): The published work or the final peer-reviewed manuscript that has been accepted for publication is made freely and openly accessible by the author, or a representative, in an online repository. Some publishers request that Open Access be granted only after an embargo period has elapsed. This embargo period can last anywhere between several months and several years. For publications that have been deposited in a repository but are under embargo, usually at least the metadata are openly accessible.
- Gold Open Access (Open Access publishing): The published work is made available in Open Access mode by the publisher immediately upon publication. The most common business model is based on one-off payments by authors (commonly called APCs – article processing charges – or BPCs – book processing charges). Where Open Access content is combined with content that requires a subscription or purchase, in particular in the context of journals, conference proceedings and edited volumes, this is called hybrid Open Access.
The choice of a journal or a publishing platform may affect the availability and accessibility of the research results.
Preprints – a new method of publication dissemination
Preprints are widely used in physical sciences and now emerging in life sciences and other fields. Preprints are documents that have not been peer-reviewed but are considered complete scientific publication in the first stage. Some of the preprints servers include open peer review services and the availability to post new versions of the initial paper once reviewed by peers.
Further reading:
ALLEA. (2013). ALLEA statement on enhancement of open access to scientific publications in Europe.
Open Access Directory (OAD) – a wiki where the open access (OA) community can create and support simple factual lists about open access to science and scholarship.
[1] FOSTER consortium. (2018). The open science training handbook. https://doi.org/10.5281/zenodo.1212496An introduction to Open Access Publishing
"Gain an insight into open access and how it offers a further alternative for your research. Make your research freely available to everyone. Choose Open." Watch the video on An introduction to Open Access publishing from Taylor & Francis.
cOAlition S and Plan S
On 4 September 2018, a group of national research funding organisations, with the support of the European Commission and the European Research Council (ERC), announced the launch of cOAlition S, an initiative to make full and immediate Open Access to research publications a reality. It is built around Plan S, which consists of one target and 10 principles.
cOAlition S signals the commitment to implement the necessary measures to fulfill its main principle:
“With effect from 2021, all scholarly publications on the results from research funded by public or private grants provided by national, regional and international research councils and funding bodies, must be published in Open Access Journals, on Open Access Platforms, or made immediately available through Open Access Repositories without embargo.”
What is Plan S?
The main ambition of Plan S is to accelerate the transition to full and immediate OA. The guiding principle behind Plan S is that research that has been paid with public money should not be locked behind paywalls.
Plan S requires that, from 2021, recipients of research funding from cOAlition S organizations make the resulting publications available immediately (without embargoes) and under open licenses, either in quality OA platforms or journals or through immediate deposit in open repositories that fulfill the necessary conditions.
Plan S is applicable to research funded by organizations (incl. all beneficiaries of Horizon Europe) who have signed up to Plan S.
How to comply with Plan S?
cOAlition S released the Journal Checker Tool (JCT), a search engine that checks Plan S compliance. The JCT is a web-based tool which enables researchers to quickly identify journals or platforms that provide routes to compliance with Plan S.
Further reading:
Statement by the European Research Council on the support of the cOAlition S initiative.
[1] cOAlition S. (n.d.). What is cOAlition S? https://www.coalition-s.org/about/
[2] cOAlition S. (n.d.). Plan S principles. https://www.coalition-s.org/plan_s_principles/
[3] KU Leven. (n.d.). Plan S explained. https://www.kuleuven.be/open-science/what-is-open-science/scholarly-publishing-and-open-access/open-access-why-and-how/plan-s-explainedOpen Access in 60 Seconds
What does open access mean? This video summarizes the main points: No costs and technical barriers for readers and libraries, but permanent access and possibilities for subsequent use, as well as the generation of new knowledge. Click on Video: Open Access in 60 Seconds to open the resource.
Research data
Research data refers to the information collected, observed, or created for purposes of analysis to produce and validate original research results. Sharing and re-using data to reproduce research and build upon it, are a cornerstone of Open Science. The sustainability of research data refers to their long-term preservation, accessibility, and interoperability.
Proper management, preservation, and sharing of research data are crucial for ensuring the replicability of research results, advancing further studies, and enhancing collaboration among scholars.
Types of research data
Research data can come in various formats and types, depending on the field of study and the research methodology employed. Data can be quantitative (numerically based) or qualitative (non-numerical, such as words or images), and it may include, but is not limited to, numerical values, text, transcripts, images, video and audio recordings, software, algorithms, equations, and test responses.
Research data can be raw or primary data (collected directly from experiments, surveys, or observations), processed or secondary data (which has been analyzed or manipulated in some way), or metadata (data about data, which provides information necessary to understand other data).
ALLEA recommendations on good data management practices
The revised European Code of Conduct on Research Integrity outlines a number of recommendations on "Data Practices and Management":
- Researchers, research institutions, and organisations ensure appropriate stewardship, curation, and preservation of all data, metadata, protocols, code, software, and other research materials for a reasonable and clearly stated period.
- Researchers, research institutions, and organisations ensure that access to data is as open as possible, as closed as necessary, and where appropriate in line with the FAIR Principles (Findable, Accessible, Interoperable and Reusable) for data management.
- Researchers, research institutions, and organisations are transparent about how to access and gain permission to use data, metadata, protocols, code, software, and other research materials.
- Researchers inform research participants about how their data will be used, reused, accessed, stored, and deleted, in compliance with GDPR.
- Researchers, research institutions, and organizations acknowledge data, metadata, protocols, code, software, and other research materials as legitimate and citable products of research.
- Researchers, research institutions, and organisations ensure that any contracts or agreements relating to research results include equitable and fair provisions for the management of their use, ownership, and protection under intellectual property rights.
For the curious ones. There is a whole lot more to Data Management. Go ahead and check it out.
[1] ALLEA. (2023). The European Code of Conduct for Research Integrity. https://allea.org/code-of-conduct/Research Data Management
Data management plans (DMPs) are formal documents in which researchers describe how they plan to use data during and after the research. This helps researchers in sharing their data according to the FAIR principles (findable, accessible, interoperable, and re-useable), as recommended by the European Code of Conduct (ECoC).
DPMs are becoming integral parts of grant applications and research organisations. They are usually short, and state which data will be created and how. DMPs also define the plans for data sharing and presentation, prescribe how the data will be stored, who will have access to it, what documentation and metadata will be created with it, and how it will be preserved. Creating DMPs provides several benefits for researchers, such as reducing the loss of data, monitoring the research progress, and preparing data for future use. Apart from that, they are also time saving.
Creating DMPs - the 'How to' guides
- The Digital Curation Centre (DCC), a leading centre in digital information curation that gives advice and help on how to store, manage, protect and share digital research data, provides resources, such as online tools, guidance and training. One of them is DMP online, a free web-based tool that supports researchers in developing DMPs by providing them with templates and guidelines.
- California Digital Library has also developed DMPTool, an open and international source project, that helps researchers, institutions, and funders in the USA in creating DMPs.
- Science Europe, an association of Research Funding Organisations and Research Performing Organisations, has developed Practical Guide to the International Alignment or Research Data Management. The Guide provides a basis for development of data practices and management for organisations, disciplines, and individual researchers. Adaptable DMP templates are also available.
There are a number of other useful tools available for creating DMPs. Check those listed below:
- Data Stewardship Wizard. An open-source platform for collaborative and living data management plans.
- RDM kit. The Research Data Management toolkit for Life Sciences
[1] ELIXIR (2021) Research Data Management Kit. A deliverable from the EU-funded ELIXIR-CONVERGE project (grant agreement 871075). https://rdmkit.elixir-europe.org
[2] Embassy of Good Science. Data management plans. https://embassy.science/wiki/Theme:67a453dc-7fa0-4f58-a869-748fe
[3] Science Europe. Sustainable research data. https://scienceeurope.org/our-priorities/research-data/sustainable-research-data/FAIR Data
In 2016, the ‘FAIR Guiding Principles for scientific data management and stewardship’ were published in Scientific Data. The authors intended to provide guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets.
The principles emphasise machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention) because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity, and creation speed of data.
What is FAIR data?
The FAIR principles describe how research outputs should be organised so they can be more easily accessed, understood, exchanged and reused. Major funding bodies, including the European Commission, promote FAIR data to maximise the integrity and impact of their research investment.
The principles refer to three types of entities: data (or any digital object), metadata (information about that digital object), and infrastructure.
FAIR principles enable researchers to maximize the value of their data, accelerating scientific progress and innovation. FAIR data is an important aspect of the Open Science policy of the European Commission.
The FAIR guiding principles
Findable
The first step in (re)using data is to find them. Metadata and data should be easy to find for both humans and computers. Machine-readable metadata are essential for automatic discovery of datasets and services, so this is an essential component of the FAIRification process.
F1. (meta)data are assigned a globally unique and eternally persistent identifier.
F2. data are described with rich metadata.
F3. (meta)data are registered or indexed in a searchable resource.
F4. metadata specify the data identifier.
Accessible
Once the user finds the required data, she/he/they need to know how they can be accessed, possibly including authentication and authorisation.
A1. (meta)data are retrievable by their identifier using a standardized communications protocol.
- A1.1. the protocol is open, free, and universally implementable.
- A1.2. the protocol allows for an authentication and authorization procedure, where necessary.
A2. metadata are accessible, even when the data are no longer available.
Interoperable
The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing.
I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
I2. (meta)data use vocabularies that follow FAIR principles.
I3. (meta)data include qualified references to other (meta)data.
Reusable
The ultimate goal of FAIR is to optimise the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings.
R1. meta(data) have a plurality of accurate and relevant attributes.
- R1.1. (meta)data are released with a clear and accessible data usage license.
- R1.2. (meta)data are associated with their provenance.
- R1.3. (meta)data meet domain-relevant community standards.
[1] GO FAIR. FAIR principles. https://www.go-fair.org/fair-principles/
How to Make your Data FAIR
Are you at the start of your project and planning to create research data? Read on to find out how to make it more findable, accessible, interoperable and reusable via the FAIR principles.
How to GO FAIR – The Three-point FAIRification Framework
Since its beginning in early 2018, the GO FAIR community has been working towards implementations of the FAIR Guiding Principles. This collective effort has resulted in a three-point framework that formulates the essential steps towards the end goal, a global Internet of FAIR Data and Services where data are Findable, Accessible, Interoperable and Reusable (FAIR) for machines.
The Three-point FAIRification Framework developed by the GO FAIR Initiative provides practical “how to” guidance to stakeholders seeking to go FAIR. The framework helps a broad spectrum of stakeholders to see what “going FAIR” means to them in practice, and to immerse themselves in the emerging FAIR landscape.
FAIR self-assessment
In order to assess the FAIRness of a dataset and determine how to enhance its FAIRness, you can use this FAIR Data Self Assessment Tool developed by the ARDC - Australian Research Data Commons.
Further reading:
OpenAIRE – How to make your data FAIR. OpenAIRE Guide for Researchers.
[1] GO FAIR. How to GO FAIR. https://www.go-fair.org/how-to-go-fair/Discuss: Data Practices, Data Management and FAIR Principles
Members of The Embassy of Good Science have developed a set of scenarios for educational purposes and to stimulate strategic thinking about issues in research ethics and research integrity.
The scenarios are designed to help researchers and other entities to become better acquainted with The European Code of Conduct for Research Integrity as a regulatory document that articulates the standards of good research practice.
This scenario presents a hypothetical narrative concerning data practices and data management and their links with research ethics and research integrity.
It focuses on issues regarding:
- Data protection and consent;
- FAIR principles for data management and stewardship;
- Data copyright and data citation;
- Data for personal research use.
Your task is to:
- Read the narrative (Issue 1–3) and questions for researchers related to the presented issues
- Share your thoughts on research integrity issues raised by a narrative in a forum (at least one or two sentences per question; approx. 50 words)
- Discuss the best research practice with other participants (use 'Discuss this topic' button; optional)
Quiz
click and exercise the quiz.
Remarks
We are proud to have you, our world-class colleagues in the field, and we dedicate this course to you.
The course was developed within the ETHICS project and with the support of the European Education and Culture Executive Agency No. 101 101082546 — ETHICS — ERASMUS-EDU-2022-CBHE
