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Concept
Comité de données pour la science et la technologie
Résumé
The Committee on Data of the International Science Council (CODATA) was established in 1966 as the Committee on Data for Science and Technology, originally part of the International Council of Scientific Unions, now part of the International Science Council (ISC).
CODATA exists to promote global collaboration to advance open science and to improve the availability and usability of data for all areas of research. CODATA supports the principle that data produced by research and susceptible to being used for research should be as open as possible and as closed as necessary. CODATA works also to advance the interoperability and the usability of such data; research data should be FAIR (findable, accessible, interoperable and reusable). By promoting the policy, technological, and cultural changes that are essential to promote open science, CODATA helps advance ISC's vision and mission of advancing science as a global public good.
The CODATA Strategic Plan 2015 and Prospectus of Strategy and Achievement 2016 identify three priority areas:
promoting principles, policies and practices for open data and open science;
advancing the frontiers of data science;
building capacity for open science by improving data skills and the functions of national science systems needed to support open data.
CODATA achieves these objectives through a number of standing committees and strategic executive led initiatives, and through its task groups and working groups. CODATA also works closely with member unions and associations of ISC to promote the efforts on open data and open science.
CODATA supports the Data Science Journal and collaborates on major data conferences like SciDataCon and International Data Week.
In October 2020 CODATA is co-organising an International FAIR Symposium together with the GO FAIR initiative to provide a forum for advancing international and cross-domain convergence around FAIR. The event will bring together a global data community with an interest in combining data across domains for a host of research issues – including major global challenges, such as those relating to the Sustainable Development Goals.
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