18. – 21. November 2018, Dagstuhl-Perspektive-Workshop 18472

Implementing FAIR Data Infrastructures


Natalia Manola (University of Athens, GR)
Andrea Scharnhorst (Royal Netherlands Acad. of Arts & Sci. – Amsterdam, NL)
Klaus Tochtermann (ZBW-Leibniz-Informationszentrum Wirtschaft – Kiel, DE)
Peter Wittenburg (Max Planck Computing and Data Facility – Garching, DE)


Peter Mutschke (GESIS – Köln, DE)
Guido Scherp (ZBW-Leibniz-Informationszentrum Wirtschaft – Kiel, DE)

Auskunft zu diesem Dagstuhl-Perspektive-Workshop erteilt

Dagstuhl Service Team


Dagstuhl Report, Volume 8, Issue 11 Dagstuhl Report
Dagstuhl Manifesto, Volume 8, Issue 1 Dagstuhl Manifesto
Programm des Dagstuhl-Perspektive-Workshops [pdf]


The Dagstuhl Perspectives Workshop on "Implementing FAIR Data Infrastructure" aimed at bringing together computer scientists and digital infrastructure experts from different domains to discuss challenges, open issues, and technical approaches for implementing the so-called FAIR Data Principles in research data infrastructures. Moreover, the workshop aimed to shape the role of and to develop a vision for computer science for the next years in this field, and to work out the potentials of computer science in advancing Open Science practices.

In the context of Open Science, and the European Open Science Cloud (EOSC) in particular, the FAIR principles seem to become a common and widely accepted conceptual basis for future research data infrastructures. The principles consist of the four core facets that data must be Findable, Accessible, Interoperable, and Reusable in order to advance the discoverability, reuse and reproducibility of research results. However, the FAIR principles are neither a specific standard nor do they suggest specific technologies or implementations. They describe the core characteristics of data use. Thus, the FAIR principles cover a broad range of implementation solutions. This certainly incorporates the risk of having a highly fragmented set of solutions at the end of the day.

Given this, and in view of the "need for a fast track implementation initiative [of the EOSC]", it is strongly needed to turn the principles into practice. Therefore, the workshop took the recommendations of the European Commission Expert Group on FAIR Data "Turning FAIR into reality" as a starting point and discussed what can be done next from the perspective of computer science to enable data providers to make their data FAIR.

The workshop started with three ignition talks on the wider background and context of the FAIR principles (given by Peter Wittenburg), the relationship of FAIR to Open Data (given by Natalia Manola) and the role of the principles within the EOSC (given by Klaus Tochtermann). Based on these talks as well as inputs from all participants in the forefront of the workshop, we have split the discussion into three working groups addressing, for each of the four principles, the main key challenges for implementing FAIR and the question what and how computer science can contribute to these key challenges. Based on the results of these three initial working groups we furthermore split into more focused groups addressing the problem of licenses w.r.t. data use, (self)improvement of FAIRification, and the relation of FAIR and data intensive science.

Finally, we identified three major areas to be addressed in the manifesto which we discussed in three further working groups:

  • Infrastructures & Services Aspects: This group focused on the question by which technical means research data infrastructures and data services can be advanced to better address and fulfil the FAIR principles.
  • Computer Science Research Topics: The working group discussed the relationship of research areas in computer science and topics relevant to implement FAIR data infrastructures.
  • FAIR Computer Science Research: While the other two groups mainly focused on the contribution of computer science to implement FAIR, this working group addressed the question how the FAIR principles are currently adopted by computer science research itself and what should be improved.

The participants will continue their work in the aforementioned issues, and a manifesto is foreseen to be ready by mid May 2019.

Summary text license
  Creative Commons BY 3.0 Unported license
  Natalia Manola, Peter Mutschke, Guido Scherp, Klaus Tochtermann, and Peter Wittenburg


  • Data Bases / Information Retrieval
  • Semantics / Formal Methods


  • Open Science
  • Open Data
  • FAIR principles
  • Research Data Infrastructures


In der Reihe Dagstuhl Reports werden alle Dagstuhl-Seminare und Dagstuhl-Perspektiven-Workshops dokumentiert. Die Organisatoren stellen zusammen mit dem Collector des Seminars einen Bericht zusammen, der die Beiträge der Autoren zusammenfasst und um eine Zusammenfassung ergänzt.


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