Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació
Universitat Politècnica de Catalunya. IMP - Information Modeling and Processing
2020
With the growing popularity of Semantic Web technologies, more and more organizations natively manage data using Semantic Web standards, in particular RDF. This development gives rise to new requirements for Business Intelligence tools to enable analyses in the style of On-Line Analytical Processing (OLAP) over RDF data. In this demonstration, we therefore present the SETLBI (Semantic Extract-Transform-Load and Business Intelligence) integration platform that brings together the Semantic Web and Business Intelligence technologies. SETLBI covers all phases of integration: target definition, source to target mappings generation, semantic and non-semantic source extraction, data transformation, and target population and update. It facilitates Data Warehouse designers to build a semantic DataWarehouse, either from scratch or by defining a multi-dimensional view over existing RDF data sources, and further enables OLAP-style analyses.
This research is partially funded by the European Commission through the Erasmus Mundus Joint Doctorate Information Technologies for Business Intelligence (EM IT4BI-DC), the Poul Due Jensen Foundation, and the Danish Council for Independent Research (DFF) under grant agreement no. DFF-4093-00301B.
Peer Reviewed
Postprint (published version)
Conference report
English
Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació; Semantic web; Business intelligence; Data warehousing; ETL; Semantic data warehouse; Semantic ETL; Semantic data integration; Web semàntica; Intel·ligència competitiva; Gestor de dades
Association for Computing Machinery (ACM)
https://dl.acm.org/doi/10.1145/3366424.3383533
https://creativecommons.org/licenses/by/4.0/
Open Access
Attribution 4.0 International
E-prints [72986]