Please use this identifier to cite or link to this item: http://hdl.handle.net/11366/606
Title: FAIR Data: principles, implementation, implications
Authors: Hodson, Simon 
Keywords: research data management;FAIR data principles;open science;data repositories;EC H2020 Open Data Policy;CODATA;research data curation
Issue Date: 21-Nov-2017
Publisher: euroCRIS
Series/Report no.: euroCRIS Strategic Membership Meeting Autumn 2017 (CVTI SR, Bratislava, Slovakia, Nov 20-22, 2017)
Conference: Strategic Membership Meeting 2017 – Autumn (Bratislava) 
Abstract: 
The presentation provides an overview on the area of Open Research Data as a key part of Open Science implementation in which CODATA plays a very relevant role. The history of the policy push towards Open Data is explored in parallel with the gradual arising of the discourse on Open Science. The rationale behind the FAIR Data principles for findability, accessibility, interoperability and reusability and the challenges posed specially by the two last ones are described. Since these FAIR Data principles lie at the core of initiatives like the European Open Science Cloud, a roadmap is suggested for their implementation including -- among others -- areas like defining indicators for measuring progress on each of the four features, clarifying the boundaries of openness, investing in sustainable data infrastructure or addressing the skills needs for data scientists and researchers.
Description: 
46 slides.-- Presentation delivered within the session "Open Science and FAIR Data"
URI: http://hdl.handle.net/11366/606
Appears in Collections:Conference

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