Combining Business Intelligence with Semantic Web: Overview and Challenges

Laborie, Sébastien, Ravat, Franck, Song, Jiefu and Teste, Olivier (2015) Combining Business Intelligence with Semantic Web: Overview and Challenges. In: 33eme Congrès sur l'INFormatique des Organisations et Systemes d'Information et de Decision (INFORSID 2015).

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Abstract

Under today’s highly complex and dynamic business environment, external data (most often issued from web) need to be included in traditional On-Line Analytical Processing (OLAP) analysis so that decision-makers would be well-informed before making effective decision. Including external web data requires knowing the exact semantic meaning in order to use the right information at the right time. Semantic Web (SW) technologies allow semantically annotating data so that we can exchange several descriptions over web data, do reasoning over these descriptions and ensure interoperability between humans and systems. A combination of BI technologies with SW will both enhance BI analysis with web data and allow analyzing SW data through BI tools. In this paper, we firstly introduce basic concepts of the BI and SW domains. Then, we present recent research results using SW to enhance OLAP analysis. At last, we identify challenges requiring future research efforts to achieve a complete incorporation of BI with SW.

Item Type: Conference or Workshop Item (Paper)
Language: English
Date: 2015
Uncontrolled Keywords: Semantic web - Data warehouse - Multidimensional analysis
Subjects: H- INFORMATIQUE
Divisions: Institut de Recherche en Informatique de Toulouse
Site: UT1
Date Deposited: 26 Mar 2019 13:30
Last Modified: 26 Mar 2019 13:30
URI: http://publications.ut-capitole.fr/id/eprint/29563

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