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dc.contributor.authorJeffery, Keith Geng
dc.contributor.authorAsserson, Anneeng
dc.contributor.authorHoussos, Nikoseng
dc.contributor.authorBrasse, Valerieeng
dc.contributor.authorJörg, Brigitteeng
dc.date.accessioned2015-06-29T07:48:07Z
dc.date.available2015-06-29T07:48:07Z
dc.date.issued2014
dc.identifier.issn1877-0509
dc.identifier.urihttps://hdl.handle.net/1956/10096
dc.description.abstractOGD (Open Government Data) is provided from government departments for transparency and to stimulate a market in ICT services for industry and citizens. Research datasets from publicly funded research commonly are associated with the open scholarly publications movement. However, the former world commonly is derived from the latter with generalisation and summarisation. There is advantage in a user of OGD being able to ‘drill down’ to the underlying research datasets. OGD encourages cross-domain research because the summarized data from different domains is more easily relatable. Bridging across the two worlds requires rich metadata; CERIF (Common European research Information Format) has proved itself to be ideally suited to this requirement. Utilising the research datasets is data-intensive science, a component of e-Research. Data-intensive science also requires access to an e-infrastructure. Virtualisation of this e-infrastructure optimizes this.en_US
dc.language.isoengeng
dc.publisherElseviereng
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/eng
dc.subjectrich contextual metadataeng
dc.subjectCERIFeng
dc.subjecte-Scienceeng
dc.subjectopen dataeng
dc.subjecte-infrastructureeng
dc.subjectresearch dataeng
dc.titleFrom Open Data to Data-intensive Science through CERIFeng
dc.typePeer reviewed
dc.typeJournal article
dc.date.updated2015-06-29T07:44:23Z
dc.description.versionpublishedVersion
dc.identifier.doihttps://doi.org/10.1016/j.procs.2014.06.032
dc.identifier.cristin1236851
dc.source.journalProcedia Computer Science
dc.source.4033
dc.source.pagenumber191-198


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