Please use this identifier to cite or link to this item: http://hdl.handle.net/11366/229
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dc.contributor.authorNogales, Alberto-
dc.contributor.authorSicilia, Miguel Angel-
dc.contributor.authorJörg, Brigitte-
dc.date.accessioned2014-05-05T07:55:16Z-
dc.date.available2014-05-05T07:55:16Z-
dc.date.issued2014-05-14-
dc.identifier.citation"Managing Data-Intensive Science: the Role of Research Information Systems in Realising the Digital Agenda": Proceedings of the 12th International Conference on Current Research Information Systems (2014)en_US
dc.identifier.citationProcedia Computer Science 33: 266-271 (2014)-
dc.identifier.other10.1016/j.procs.2014.06.042-
dc.identifier.urihttp://hdl.handle.net/11366/229-
dc.descriptionDelivered at the CRIS2014 Conference in Rome; published in Procedia Computer Science 33 (Jul 2014).en_US
dc.descriptionContains conference paper (6 pages) and presentation (16 slides)-
dc.description.abstractThe needs of global science have fostered open access to the results and contextual information of research organizations at an international scale. This requires the use of standards or shared data models to exchange information preserving its semantics when transferred between systems. In that direction, standards as CERIF or projects as VIVO were developed to exchange or expose the scientific knowledge. Also, there are other sources of scientific information in the Web that are useful to complement institutional repositories and CRISes. The heterogeneity of data models behind each source in turn raises the need for mappings between them to ease interchange and aggregate information. In this paper, we present a tool that integrates three sources of research information and enables their aggregating and export into both VIVO and CERIF models. We present a case study in agriculture using OpenAGRIS, a bibliographic database linked to Web sources with more than 7 million records. Concretely, we describe the methods to combine Google Scholar data for the scholarly content indexed in OpenAGRIS and aggregating new information provided by the first one, using our tool. Finally the information is stored in a VIVO instance and then translated into CERIF using a conversion process mapping both data models. The case demonstrates the possibilities of mapping tools to aggregate and translate CRIS information.en_US
dc.language.isoenen_US
dc.publishereuroCRISen_US
dc.relation.ispartofseriesCRIS2014: 12th International Conference on Current Research Information Systems (Rome, May 13-15, 2014)-
dc.subjectcurrent research information systemsen_US
dc.subjectVIVOen_US
dc.subjectCERIFen_US
dc.subjectOpenAGRISen_US
dc.subjectresearch information managementen_US
dc.subjectGoogleScholaren_US
dc.subjectmappingsen_US
dc.subjectsystem interoperabilityen_US
dc.titleCombining VIVO and Google Scholar data as sources for CERIF Linked Data: A case in the agricultural domainen_US
dc.typeConference Paperen_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.procs.2014.06.042-
dc.relation.conferenceCRIS2014 Conferenceen
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextopen-
item.cerifentitytypePublications-
item.openairetypeConference Paper-
item.fulltextWith Fulltext-
item.languageiso639-1en-
crisitem.author.orcid0000-0003-4951-8102-
Appears in Collections:Conference
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WT2_Nogales_Sicilia_Jorg_CRIS2014.pdfpresentation1.11 MBAdobe PDF
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