Welcome to my first blog for Jisc. You may know me (Bas Cordewener) in the role of Coordinator of the Knowledge Exchange initiative. As the responsible project manager I’d like to introduce a new piece of work Jisc is currently undertaking with the title FAIR in practice.
FAIR principles
To introduce what the FAIR principles are, let me quote the abstract of the article provided by Nature on their website ‘The FAIR Guiding Principles for scientific data management and stewardship’
There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals.
Where does Jisc fit in?
Jisc supports the research and higher education sector to realise the optimal infrastructure and policy framework. The challenges to be met are efficiency, effectiveness and transparency when using and reusing research data. One of the programmes to work on this is Research at Risk, enabling UK universities and their researchers to create, manage and share research data effectively. Within the shared services and infrastructure part of this programme, work is being done on Research Data Discovery, preservation, and storage services, as well as implementation of ORCID.
In order to make these services interoperable and ensure smooth data use and reuse, policies need to be in place to support Open Research and Open Data, and the reference to the FAIR principles that aim to guarantee Findability, Accessibility, Interoperability and Re-use/reproducibility of research data can be a big step forward. This can only be realised if the meaning and effect of the principles are fully understood. That is where the work on FAIR in Practice comes in.
FAIR in practice
Jisc wishes to establish a thorough insight in how FAIR principles are used within the research community in the UK and understand how FAIR can contribute optimally to the quality of research. That means knowing in what disciplines FAIR is a known concept that is acted upon in practice and/or acknowledged in policies; establishing a notion of what the perceived or experienced benefits and challenges are, as well as getting an idea of differences in awareness, adherence or applicability between various disciplines. At the same time we wish to explore what experts, researchers and research managers think about the future development and potential benefit of FAIR in the UK and internationally.
Jisc is not alone in its interest in FAIR. Its importance and potential is recognised by many other organisations. Examples are DANS in the Netherlands, exploring an approach to assess the FAIRness of datasets in Trustworthy Digital Repositories (presented at the iDCC conference by Peter Doorn and Ingrid Dillo), and the GoFAIR initiative, led by Barend Mons, former chair of the European High Level Expert Group for the European Open Science Cloud. The RDA (Research Data Alliance) also addresses aspects of FAIR within the Data Discovery Paradigm Interest Group.
Jisc FAIR in practice approach
We’ve invited a small group of Jisc experts, working in the field of research data and several external experts with various perspectives to provide their experience and views on FAIR as it is now, and can be in the future. We’ve also hired a consultant, Hapsis Innovation Ltd to interview these experts, as well as researchers and policy makers in different disciplines. They will bring representatives of these groups together in a dialogue to jointly explore and identify the value, hoped for development, and possible recommendations. Outcomes will inform the research community how to deal with and benefit from the FAIR principles. Around summer Jisc will issue a report with findings, expectations and considerations for joint interventions.
Your contributions are welcome
If you have questions or wish to contribute in whatever way to the FAIR in practice work, do not hesitate and get in touch with me. My email address can be found on the Jisc website, you may comment below, or you can send me a tweet @bascordewener
Thanks for your attention, happy to hear from you!
Bas Cordewener
10 replies on “FAIR in Practice”
This is great to hear, thanks for blogging Bas.
I’d encourage you to share results with the European Commission’s Expert Group on Turning FAIR data into reality. We have a public call for contributions out at the moment, see: https://ec.europa.eu/research/openscience/pdf/fair_eg.pdf#view=fit&pagemode=none
When is your work due to report? Is it Summer this year or next?
Thanks for your comments and suggestion, Sarah!
It is a bit hard to predict the exact moment of publication but will be after summer this year 🙂
Cheers, Bas
There will be a FAIR datafest at https://pidapalooza.org on 23/24th January, in Girona, Spain. One session in particular, the “PID stories”, is likely to contain some interesting FAIR examples. PIDs of course underpin FAIR, especially via interesting and innovative ways of deploying and utilising metadata.
I have documented a number of “FAIR in practice” stories on my blog: https://www.ch.imperial.ac.uk/rzepa/blog/?s=FAIR
Many, but not all, related to the molecular sciences.
There is a talk given to the Jisc “FAIR in practice” focus group for researchers (London), The British Library, 13 September, 2017 available (as a FAIR talk) via https://doi.org/ccwv
Dear Henry Rzepa,
Thanks for your contributions in reply to this blog. Unfortunately these ended up in the SPAM section. I did not notice until today – so they became public rather late. Best wishes, Bas
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The following link, https://losc.ligo.org/events/ contains examples of FAIR data relating to the (currently) six detections of gravitational waves. These are examples of FAIR enhanced by nice graphical presentation of the data, as well as the data itself.
This PID; http://doi.org/cfr9 charts the evolution of what is now called FAIR data over the period 1994-2015 from the perspective of one research group. Around 2008, the use of persistent identifiers started, albeit using Handles rather than the more common DOIs.
I have conducted a Scifinder search for the term FAIR data (Scifinder abstracts most of molecular and chemical science). Three articles which discuss the application of FAIR emerge;
https://doi.org/10.1016/j.jbiotec.2017.06.007 https://doi.org/10.3389/fpls.2016.00641 https://doi.org/10.1259/bjr.20160689
although there are many more which probably have not exalted the term FAIR data to the point it was captured in the abstracting. Thus Scifinder suggests 9357 references were found containing the concept “FAIR data” rather than the explicit term. Many of these are probably NOT the concept we are discussing here.
It will be interesting to see how these statistics evolve over the next few years.
Subject-domain standards bodies are increasingly promoting FAIR exchange (of data). Thus https://iupac.org/event/supporting-fair-exchange-chemical-data-standards-development/ where one of the objectives is to identify both good (and bad) examples of contemporary journals and their presentation of the data components.