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Title: Combining VIVO and Google Scholar data as sources for CERIF Linked Data: A case in the agricultural domain
Authors: Nogales, Alberto 
Sicilia, Miguel Angel 
Jörg, Brigitte 
Keywords: current research information systems;VIVO;CERIF;OpenAGRIS;research information management;GoogleScholar;mappings;system interoperability
Issue Date: 14-May-2014
Publisher: euroCRIS
Source: "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)
Procedia Computer Science 33: 266-271 (2014)
Series/Report no.: CRIS2014: 12th International Conference on Current Research Information Systems (Rome, May 13-15, 2014)
Conference: CRIS2014 Conference 
The 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.
Delivered at the CRIS2014 Conference in Rome; published in Procedia Computer Science 33 (Jul 2014).

Contains conference paper (6 pages) and presentation (16 slides)
Appears in Collections:Conference

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