Ontologies and summarizability in OLAP

Authors:
Tapio Niemi;Marko Niinimäki
Affiliations:
Helsinki Institute of Physics, Technology Programme, Geneva, Switzerland;University of Applied Sciences of Western Switzerland, Geneva, Switzerland
Venue:
Proceedings of the 2010 ACM Symposium on Applied Computing
Year:
2010

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Abstract

Summarizability, i.e. the correctness of aggregation operations, is essential for OLAP analysis. Summarizability has commonly been studied in the context of dimension hierarchies, but the role of semantics of measure attributes and aggregation functions (sum, avg, min, max, count) has received less research interest. In this paper, we focus on the relationship between measure and dimension attributes and its effect on summarizability. We define the concept of measure-dimension consistency and show how it can be concluded from an OLAP ontology constructed by using Semantic Web technologies. Measure-dimension consistency can be used both for OLAP cube construction and queries and it is also very useful when integrating data over the internet.