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SCIence Data Infrastructure for Preservation – Earth Science (SCIDIP-ES)
Date du début: 1 sept. 2011, Date de fin: 31 déc. 2014 PROJET  TERMINÉ 

The aim of this initiative is to address priorities a) and c) of the call INFRA-2011-1.2.2: Data infrastructures for e-Science. It is about delivering long-term preservation services as part of the data infrastructure for e-Science.We aim to deliver generic infrastructure services for science data preservation that address the persistent storage, access and management required by the call and to build on the experience of the ESA Earth Observation Long Term Data Preservation (LTDP) programme to favour the set-up of a European Framework for the long term preservation of Earth Science (ES) data through the definition of common preservation policies, the harmonization of metadata and semantics and the deployment of the generic infrastructure services in the ES domain.The generic services will build on the already proven research prototype services from the CASPAR project. We will evaluate and tune these services in depth, using Earth Science as pathfinder, and broadly but less deeply across other disciplines linked to the Alliance for Permanent Access (APA) and ESFRI clusters. Earth Science presents an enormous challenge to the providers of data-infrastructure because it is inherently a very broad and scattered domain with completely different instruments operated by different entities, which at the moment apply different data preservation policies – or none at all. This work is important because it will allow our society to properly preserve the digitally encoded information on which we all depend, in particular Earth Science measurements which can never be repeated and yet on which a multitude of ecological, economic and political decisions must be based in the future. The generic services will allow all kinds of data to be usable by researchers from many different domains and will enable the cost for long-term usability across disciplines to be shared supporting the creation of strong business cases for the long term support of that data.



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