CO-OPERAS IN – Winner of the ANR open science call for projects on research data
The CO-OPERAS IN (Implementation Network) collaboration network, of which OpenEdition is one of the French coordinators alongside Huma-Num, has won the ANR open science call for projects on research practices and open data. Funded to the tune of €100,000 over two years, CO-OPERAS IN aims to organize and supervise the implementation of research data in the humanities and social sciences according to the principles of the GO FAIR initiative (Findable, Accessible, Interoperable and Reusable). This forms part of the development of the European infrastructure OPERAS (Open Scholarly Communication in the European Research Area for Social Sciences and Humanities).
Easy to find, accessible, interoperable and reusable data for research in the humanities and social sciences (HSS): this is the challenge that CO-OPERAS IN seeks to rise to, with the aim of federating existing services and platforms for scholarly communication and, more broadly, involving the HSS community at the international level.
Bringing together 45 members from 27 European and international research institutions and organizations, this network will work in close collaboration with the other GO FAIR international networks involved in the construction of the European Open Science Cloud (EOSC). Various working groups within CO-OPERAS IN have been defined as part of the network roadmap validated by GO FAIR.
Six strands have been foreseen: strategy, definition of FAIR data in the HSS, surveys and mapping, framework of application, future prospects of the FAIR ecosystem, communication and training.
The CO-OPERAS IN kick-off meetingon 1st July was used to structure the activities and begin thinking about the definition of data on the basis of the HSS disciplines.
The next step is a workshop titled “Defining FAIR in the HSS: Issues, cultures and practical implementations” at the Open Science Fair in Porto in September, which will enable HSS communities to define their own roadmap for the “FAIRification” of their data.