25th International Conference on Advanced Information Systems Engineering (CAiSE 2013), Valencia, Spain, June 17-21, 2013
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
Business model ontologies capture the complex interdependencies between business objects. The analysis of the hence formalized knowledge eludes traditional OLAP systems which operate on numeric measures. Many real-world facts, however, do not boil down to a single number but are more accurately represented by business model ontologies.In this paper, we adopt business model ontologies for the representation of non-numeric measures in OLAP cubes. We propose modeling guidelines and adapt traditional OLAP operations for ontology-valued measures.
Keywords: Business Intelligence, Business Modeling, Resource-Event-Agent, Resource Description Framework