StdTrip+K: Design Rationale in the RDB-to-RDF Process

Berardi, Rita Cristina Galarraga; Breitman, Karin; Casanova, Marco A.; Lopes, Giseli Rabello; Medeiros, Adriana Pereira de

doi:10.1007/978-3-642-40285-2_26

Cited by 5 publications

(1 citation statement)

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“…The authors have performed detailed comparative analysis of various ontology construction techniques from relational database (RDB) based on database schema analysis (meta-data, cardinality restrictions and datatype information) and stored data (through data mining). The authors in [3] propose a particular process that integrates a design rationale approach with a triplification strategy. The process…”

Section: Motivation and Previous Related Workmentioning

confidence: 99%

RDB Data Triplification vs. Ontologies: The Case of Municipal Registry Data

Theocharis¹,

Tsihrintzis²

2016

IJCEE

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Nowadays the individualized provision of electronic services according to the needs of each user has become particularly important. Particular interest is acquired by the "intelligent" information retrieval with the application of innovative primary data management methods. Motivation for this work, has been the data located mainly in databases developed and managed by the public sector and associated with the development of e-Government. Its integration relies heavily on the integration of innovations that support intelligent information search and data interface in order to feed the various public organizations and governmental portal. In particular, this paper examines the possibility of converting information stored in relational databases in RDF triples that may subsequently be treated with semantic web technologies and fed into cognitive connected databases. We also present a case study, namely the development of an ontology for describing the assets held in the national population register of the Ministry of Interior of the Greek Government and the municipalities of Greece. The knowledge base associated with this ontology can be fed with the transformed data of the existing relational databases using appropriate software.

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Section: Motivation and Previous Related Workmentioning

confidence: 99%