Querying Bibliography Data Based on Linked Data

Abstract

Usually, a common data model is used for creating and getting a résumé in web applications. Though different web applications provide the same quality résumé information, they encounter difficulties in analyzing and processing data in their different sources. Linked data technology allows overcoming these problems by integrating the data coming from different sources, linking large, voluminous, and distributed data sets with semantic sources in web of data, and forming an open linked data cloud. This study mainly aims to combine, publish, and explore the semantic information in the academic résumés of scientists/researchers working in universities and/or research establishments by use of linked data. The study deals with the use and exploration of academic résumé information through linked data approach. It was intended to conduct effective SPARQL queries on linked data network via FOAF-Academic, DBLP and Résumé/Curriculum Vitae (CV) ontologies so that different data sources would be integrated.