Publication | Closed Access
Ontologies and summarizability in OLAP
20
Citations
9
References
2010
Year
Unknown Venue
EngineeringData AggregationOntology EngineeringEntity SummarizationSemanticsSemantic WebOlap AnalysisAggregate FunctionInformation RetrievalData ScienceManagementData IntegrationData ManagementStatisticsMeasure-dimension ConsistencyComputer ScienceOlap OntologyOnline Analytical ProcessingMultidimensional DatabaseOntological AnalysisOntology LanguageData Modeling
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.
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