“Open Science” reflects a fundamental paradigm shift in making scientific research more accessible and reusable. The Open Science movement has recently gained a strong momentum worldwide with an increasing demand for reliable and sustainable research data infrastructures that enable researchers to cooperate on data and share results. On the European level, for example, the European Open Science Cloud is being developed. In this context the so-called FAIR principles seem to become a common and widely accepted conceptual basis for future research data infrastructures.

These principles describe the core characteristics of data use, but they do not define or suggest any technological implementations. Thus, there is still a great lack of models, infrastructures and services available showing how FAIR research data infrastructures can be implemented. Computer science can greatly contribute to this important field.

The interdisciplinary Dagstuhl Perspectives Workshop “Implementing FAIR Data Infrastructures” aims at bringing together computer scientists with digital infrastructure experts from different domains. The central goal is to discuss the key elements required for the transition of scientific e-infrastructures and services to Open Science from the perspective of computer science as well as from different stakeholder perspectives. The workshop will discuss requirements, common mechanisms, and best practices for FAIR data management platforms and services, with a particular focus on innovative tools and methods for sharing research data and on principles of how research data can be represented in an interoperable way to foster linking and reusing data across community borders.

The Workshop will publish a manifesto of recommendations and an inventory of tools & services for implementing FAIR data principles and other targeted aspects of Open Science in future research data infrastructures and data management services. It will further shape the role that the field of computer science has to play in advancing Open Science practices.

Creative Commons BY 3.0 DE

Peter Mutschke, and Guido Scherp

• Marcel R. Ackermann (LZI Schloss Dagstuhl & dblp Trier) [dblp]
• Luiz Dlavo Bonino da Silva Santos (GO FAIR - Leiden, NL)
• Timothy W. Clark (University of Virginia, US) [dblp]
• Ron Dekker (CESSDA ERIC, NO) [dblp]
• Kees den Heijer (TU Delft, NL)
• Michel Dumontier (Maastricht University, NL) [dblp]
• Marie Farge (ENS - Paris and CNRS, FR) [dblp]
• Sascha Friesike (VU University of Amsterdam, NL) [dblp]
• Carole Goble (University of Manchester, GB) [dblp]
• Kathleen Gregory (NL) [dblp]
• Gregor Hagedorn (Museum für Naturkunde - Berlin, DE) [dblp]
• Wilhelm Hasselbring (Universität Kiel, DE) [dblp]
• Oliver Kohlbacher (Universität Tübingen, DE) [dblp]
• Paolo Manghi (ISTI-CNR - Pisa, IT) [dblp]
• Natalia Manola (University of Athens, GR) [dblp]
• Daniel Mietchen (University of Virginia, US) [dblp]
• Peter Mutschke (GESIS - Köln, DE) [dblp]
• Heike Neuroth (FH Potsdam, DE) [dblp]
• Andreas Rauber (TU Wien, AT) [dblp]
• Marc Rittberger (DIPF - Frankfurt am Main, DE) [dblp]
• Raphael Ritz (Max Planck Computing and Data Facility - Garching, DE) [dblp]
• Guido Scherp (ZBW-Leibniz-Informationszentrum Wirtschaft - Kiel, DE) [dblp]
• Birgit Schmidt (SuB - Göttingen, DE) [dblp]
• Achim Streit (KIT - Karlsruher Institut für Technologie, DE) [dblp]
• Klaus Tochtermann (ZBW-Leibniz-Informationszentrum Wirtschaft - Kiel, DE) [dblp]
• Dieter Van Uytvanck (CLARIN ERIC - Utrecht, NL) [dblp]
• Tobias Weigel (DKRZ Hamburg, DE) [dblp]
• Mark D. Wilkinson (Polytechnic University of Madrid, ES) [dblp]
• Peter Wittenburg (Max Planck Computing and Data Facility - Garching, DE) [dblp]