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dc.contributor.authorunicampGomes Junior, Luiz Celsopt_BR
dc.contributor.authorunicampSantanchè, Andrépt_BR
dc.titleThe web within: leveraging web standards and graph analysis to enable application-level integration of institutional datapt_BR
dc.contributor.authorGomes Jr., Luizpt_BR
dc.contributor.authorSantanchè, Andrépt_BR
unicamp.authorGomes, L., Jr., Institute of Computing, University of Campinas (UNICAMP), Campinas, SP, Brazilpt_BR
unicamp.authorSantanchè, A., Institute of Computing, University of Campinas (UNICAMP), Campinas, SP, Brazilpt_BR
dc.subjectBig datapt_BR
dc.subjectLinguagens Query (Computação)pt_BR
dc.subjectRedes complexaspt_BR
dc.subjectWeb semânticapt_BR
dc.subjectProcessamento de consultapt_BR
dc.subject.otherlanguageBig datapt_BR
dc.subject.otherlanguageQuery languages (Computer science)pt_BR
dc.subject.otherlanguageComplex networkspt_BR
dc.subject.otherlanguageSemantic webpt_BR
dc.subject.otherlanguageQuery processingpt_BR
dc.description.abstractThe expansion of the Web and of our capacity of producing and storing information have had a profound impact on the way we organize, manipulate and share data.We have seen an increased specialization of database back-ends and data models to respond to modern application needs: text indexing engines organize unstructured data, standards and models were created to support the Semantic Web, Big Data requirements stimulated an explosion of data representation and manipulation models. This complex and heterogeneous environment demands unified strategies that enable data integration and, especially, cross-application, expressive querying. Here we present a new approach for the integration of structured and unstructured data within organizations. Our solution is based on the Complex Data Management System (CDMS), a system being developed to handle data typical of complex networks. The CDMS enables a relationship-centric interaction with data that brings many advantages to the institutional data integration scenario, allowing applications to rely on common models for data querying and manipulation. In our framework, diverse data models are integrated in a unifying RDF graph. A novel query model allows the combination of concepts from information retrieval, databases, and complex networks into a declarative query language that extends SPARQL. This query language enables flexible correlation queries over the unified data, enabling support for a wide range of applications such as CMSs, recommendation systems, social networks, etc. We also introduce Mappers, a data management mechanism that simplifies the integration of heterogeneous data and that is integrated in the query language for further flexibility. Experimental results from real data demonstrate the viability of our approach.en
dc.description.abstractThe expansion of the Web and of our capacity of producing and storing information have had a profound impact on the way we organize, manipulate and share data.We have seen an increased specialization of database back-ends and data models to respond to modpt_BR
dc.relation.ispartofLecture notes in computer sciencept_BR
dc.identifier.citationLecture Notes In Computer Science (including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics). Springer Verlag, v. 8990, n. , p. 26 - 54, 2015.pt_BR
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dc.contributor.departmentsem informaçãopt_BR
dc.contributor.departmentDepartamento de Sistemas de Informaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.subject.keywordQuery model integrationpt_BR
dc.subject.keywordData integrationpt_BR
dc.subject.keywordDB/IR integrationpt_BR
dc.subject.keywordGraph data modelspt_BR
dc.subject.keywordGraph query languagespt_BR
dc.subject.keywordComplex datapt_BR
dc.creator.orcidsem informaçãopt_BR
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