CAiSE’13

Short-bio

Christoph Schütz is a PhD student at Johannes Kepler University Linz, Austria. His research interests include data warehousing, business process modeling, and data privacy. In 2012, Christoph was a visiting researcher at Portland State University. In 2011, Christoph was awarded the TDWI award for his Master’s thesis on hetero-homogeneous data warehouses.

Abstract

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.