Major steps forward taken in the building of a terminology for the skills required to make and keep data FAIR.
DANS headquarters, The Hague, October 16-18, 2019.

What did we do?

On 16-18 October 2019, representatives of the research data community met at the DANS headquarters in The Hague to continue to build a terminology to describe FAIR stewardship skills (the skills necessary to make data FAIR and to keep them FAIR): the tag #terms4FAIRskills was used on Twitter during the event.

The meeting was kindly supported by FAIRsFAIR. This meeting was a follow up to the first terms4FAIRskills meeting held at the CODATA headquarters in Paris in 19-20 May 2019.

Why is this important?

This effort is building a formalised terminology that describes the competencies, skills and knowledge associated with activities involved in making data FAIR and keeping it FAIR. We have focussed initially on two important use cases, namely:

• determining what FAIR-related skills are covered by a set of training materials;
• searching for relevant FAIR-related courses and learning paths.

These will be important in enabling the training of FAIR-related skills for researchers, data stewards and data managers.

Other possible use cases such as developing FAIR-related job descriptions and domain-related searches in topics such as the Life or Social Sciences could also be developed. At the end of the Paris workshop we had a spreadsheet developed with 245 rows of terms based on the FAIR4S table.

What did we achieve since Paris?

Definitions and relationships for each term were developed by our annotation teams. The FAIRsharing team then clarified and added further information to the spreadsheet to enable conversion into an OWL file, which is one of the standard formats for expressing knowledge engineering data sets such as this. Details of this process can be found at https://github.com/terms4fairskills/FAIRterminology

What did we achieve in The Hague?

At the meeting in DANS, the following was achieved:

• the terminology was remodelled to more precisely distinguish activities from pedagogical concepts such as Knowledge, Skills and Aptitudes.
• Talks were presented by the collaborations SSHOC, ELIXIR and FAIRsFAIR, which provided insights into how the terminology could be used and extended for their purposes.

What next?

We will continue to atomise and refine each class and build relationships collaboratively using the WebProtege web tool. The terminology will soon be tested against the initial use cases. We plan to make the terminology available in the near future for initial inspection and comment.

Read more. https://terms4fairskills.github.io/2ndWorkshopHagueAnnouncement.html

A Galleries, Libraries, Archives and Museums (GLAM) Lab is a place for experimenting with digital collections and data. It is where researchers, artists, entrepreneurs, educators and the interested public can collaborate with an engaged group of partners to create new collections, tools, and services that will help transform the future ways in which knowledge and culture are disseminated. These Labs play a significant role in the transformation of large digital collections into data.

So far there was no systematic guidance on establishing GLAM Labs. In September a team of 16 international experts wrote the book ‘Open a GLAM Lab’ in five days during a booksprint and now this book is available under a CC0 licence on https://qspace.qu.edu.qa/handle/10576/12115  and also accessible from the website of the International GLAM Labs community, https://glamlabs.io/.

We are sharing with the CODATA community where many colleagues may be interested in the collections as data aspects of this work.

This post was written by Rebecca Lawrence, Managing Director of F1000. She was a session organiser at the CODATA 2019 Conference in Beijing, China 

Scholarly research is a global enterprise, often requiring researchers to collaborate with relevant experts across the world. The data generated during research is a valuable commodity, and researchers are increasingly required to share the data created during their research endeavour. 

However, institutional and funder data sharing policies are typically developed at organisational or national level. Meanwhile, researchers are often funded by several research agencies, working as part of a collaboration and/or with a myriad of data-related outputs.  This makes adherence to the different data sharing policies complex, burdensome and time consuming.  Furthermore, the practical ability to share data – in reputable repositories, with adequate metadata, in usable formats, at economic cost – can be onerous and in some case prohibitive for researchers.  There also remain real cultural, social and economic barriers for many researchers to share their research data openly and in a timely manner.

The session at CODATA Beijing brought together experts representing many different parts of the world to discuss how we can work better together towards harmonisation of policies and incentives for researchers to share their data so that we can fully realise the benefits of making research data more available. Panelists were Jean-Claude Burgelman (European Commission), Rebecca Lawrence (F1000; chair), Xiaoxuan Li (Chinese Academy of Sciences), Erik Schultes (Dutch Techcentre for Life Sciences), Daisy Selematsela (University of South Africa (UNISA) Library and Information Services) and Nick Shockey (SPARC).

There was considerable discussion around making sure that we don’t repeat the mistakes of the road towards Open Access (OA) but rather that we learn from it. With data sharing, there was agreement that it is especially important that it is built on a Commons and not allowed to be built by a small number of commercial closed entities. This is especially important given that ownership of data can be far more powerful and restrictive than ownership/copyright of publications. There was also agreement that much of the slow progress towards OA has been caused by confusing and lenient policies. With data sharing we have the opportunity to ensure early on that clear and stringent policies are put in place to ensure that a middle-ground does not emerge along a similar vein to the ‘hybrid’ approach now prevalent in article publishing.

There was also much discussion about the significant, and growing, gap in data sharing practices between the global north and the global south. We need to not just talk about the positives that data sharing can bring but also (and maybe especially importantly in the global south) about the risks of doing nothing. We need to consider carefully the impact on equity and inclusion before we build data sharing systems, not after when it is too late to make a tangible difference. This is especially important when considering the business model for these infrastructures to ensure that approaches don’t develop that will cause further imbalance and inequity.

The importance of ensuring that researchers not only understand what data sharing is about but also why it is important and the potential positive impact it can have on them and their research should not be underestimated. We need to debunk the many myths about it and recognise that this process is going to take considerable time and effort to achieve. 

Having said this, a significant shift towards greater data sharing will only come about if the rewards and incentives system starts to fully recognise the value of such activities and shifts away from the traditional sole focus on publications in high-impact venues. However, during such a shift, we also need to be alert to potential unintended negative consequences of any new system or approach.

Such a shift in incentives can be achieved not only by dangling ‘carrots’ but also by reducing researcher burden.  For example, the increasing use of automated workflows and data capture was highlighted as potentially creating an incentive for researchers to share their data by removing the considerable time burden in capturing and curating the data and associated methods, whilst also increasing the likely level of FAIR-compliance of the resulting data.

There was a sense from the panel that like the early Internet, the current infrastructures being built globally to support data sharing are going to become another revolutionary global infrastructure that can ultimately be used by everyone. Like then, we don’t yet know what this infrastructure may become or what it may enable. But once we can demonstrate the possibilities and potential brought about by open data policies and implementation by working through a few pilots on a multinational scale, this will mobilise the international community very quickly, and help us to bring about the crucial alignment needed around core elements of data sharing policy and implementation. 

Francophone Open Data Conference

17 – 19 December – Abidjan, Ivory Coast

Conscious of the importance of data to build sustainable development, the Francophone African Community on Open Data (CAFDO) in collaboration with the Government of Côte d’Ivoire through the Ministry of Trade and Industry, Ministry host of the Open Government Partnership (OGP), organizes the second edition of the Francophone Open Data Conference (CAFDO 2019) from 17 to 19 December 2019 in Abidjan at the Palm Club Hotel.

The theme of this second edition is ” Open Data: From Principles to Action “. It is placed under the very high patronage of His Excellency the Prime Minister, Head of the Government of Côte d’Ivoire.

The objective of the conference is to promote the openness and reuse of data in French-speaking Africa. Specifically, it will:

• Advocate at the political level for more openness of data produced in ministries and public institutions;
• promote good practices on models of openness and exploitation of data;
• identify common challenges and propose actions for a better contribution of data in building a sustainable economy in member countries.

It is expected at this conference, actors from government, civil society, development organizations, research centers, universities, digital communities (Open Source, Open Data, Open Government, etc.).

Read more