A framework for ontology-based temporal modelling of business intelligence
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Ontologies provide the means for supporting business intelligence (BI) and information management through the interpretation of unstructured content. On the basis of the semantics of ontologies, information can be extracted from natural language texts, and on a further level of processing knowledge that facilitates BI can be discovered. However, in order to act this way, ontologies need to be properly modelled and evolved so that they are constantly aligned with changes that occur in the real world. This paper presents a framework for modelling the temporal aspects of a semantic knowledge base with direct impact on the BI process.
Keywordsontology business intelligence information management ontology evolution
The authors would like to thank the CEO of Biovista, Dr. Andreas Persidis, for providing the case study and its supporting material, including requirements, data sets, and helpful feedback on the paper.
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