Multidimensional integrated ontologies: a framework for designing semantic data warehouses
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Otros documentos de la autoría: Nebot Romero, Victoria; Berlanga Llavori, Rafael; Pérez Martínez, Juan Manuel; Aramburu Cabo, María José; Pedersen, Torben Bach
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
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comunitat-uji-handle3:10234/8634
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Título
Multidimensional integrated ontologies: a framework for designing semantic data warehousesAutoría
Fecha de publicación
2009Editor
Springer Verlag (Germany)ISSN
0302-9743Cita bibliográfica
NEBOT, Victoria, et al. Multidimensional integrated ontologies: A framework for designing semantic data warehouses. En Journal on data semantics XIII. Springer, Berlin, Heidelberg, 2009. p. 1-36.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://link.springer.com/chapter/10.1007/978-3-642-03098-7_1Versión
info:eu-repo/semantics/submittedVersionPalabras clave / Materias
Resumen
The Semantic Web enables companies and organizations to gather huge amounts of valuable semantically annotated data concerning their subjects of interest. Nowadays, many applications attach metadata and semantic ... [+]
The Semantic Web enables companies and organizations to gather huge amounts of valuable semantically annotated data concerning their subjects of interest. Nowadays, many applications attach metadata and semantic annotations taken from domain and application ontologies to the information they generate. From our point of view, the concepts in these ontologies could describe the facts, dimensions, categories and values implied in the analysis subjects of a data warehouse. In this paper we propose the Semantic Data Warehouse to be a repository of ontologies and semantically annotated data resources. We also propose an ontology-driven framework to design multidimensional analysis models for Semantic Data Warehouses. This framework provides means for building an integrated ontology, called the Multidimensional Integrated Ontology (MIO), including the classes, relationships and instances that represent interesting analysis dimensions and measures. The reasoning capabilities of a MIO can be used to check the properties required by current multidimensional databases (e.g., dimension orthogonality, category satisfiability, etc.). In this paper we also sketch how the instance data of a MIO can be translated into OLAP cubes for analysis purposes. Finally, some implementation issues of the overall framework are discussed [-]
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Lecture notes in computer science, 2009, v. 5530Derechos de acceso
© Springer Verlag (Germany)
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info:eu-repo/semantics/openAccess
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info:eu-repo/semantics/openAccess
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