An overview of data warehousing and OLAP technology
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Information Systems
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STEP '03 Proceedings of the Eleventh Annual International Workshop on Software Technology and Engineering Practice
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DOLAP '06 Proceedings of the 9th ACM international workshop on Data warehousing and OLAP
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Proceedings of the ACM tenth international workshop on Data warehousing and OLAP
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Journal of the American Society for Information Science and Technology
Handbook on Ontologies
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DMG 2005 Proceedings of the First VLDB conference on Data Management in Grids
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ISWC'06 Proceedings of the 5th international conference on The Semantic Web
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Proceedings of the 2010 EDBT/ICDT Workshops
DC proposal: online analytical processing of statistical linked data
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part II
Transforming statistical linked data for use in OLAP systems
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Enhancing OLAP analysis with web cubes
ESWC'12 Proceedings of the 9th international conference on The Semantic Web: research and applications
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In this paper, we present an advanced method for on-demand construction of OLAP cubes for ROLAP systems. The method contains the steps from cube design to ETL but focuses on ETL. Actual data analysis can then be done using the tools and methods of the OLAP software at hand. The method is based on RDF/OWL ontologies and design tools. The ontology serves as a basis for designing and creating the OLAP schema, its corresponding database tables, and finally populating the database. Our starting point is heterogeneous and distributed data sources that are eventually used to populate the OLAP cubes. Mapping between the source data and its OLAP form is done by converting the data first to RDF using ontology maps. Then the data are extracted from its RDF form by queries that are generated using the ontology of the OLAP schema. Finally, the extracted data are stored in the database tables and analysed using an OLAP software. Algorithms and examples are provided for all these steps. In our tests, we have used an open source OLAP implementation and a database server. The performance of the system is found satisfactory when testing with a data source of 450 000 RDF statements. We also propose an ontology based tool that will work as a user interface to the system, from design to actual analysis.