Ontology-supported schema enrichment of a relational data warehouse with multidimensional concepts from document-oriented data source : doctoral thesis - Ptiček, Marina (M. Ptiček ; Faculty of electrical engineering and computing, 2022)
The topic of this doctoral thesis is schematic integration of data that are stored in two different data models. Acquisition and integration of external data has the potential to improve predictive analytical models used in business intelligence. Analytical data are typically stored in a relational data warehouse, but the popularity of document-oriented data indicates their increasing availability in the information market. The relational model differs significantly from document-oriented model, which is characterized by semi-structuredness, heterogeneity, and absence of schema definition, all of which is a problem for their schematic integration. In this thesis, Semantic Web ontologies are used as a reconciling medium in bridging the differences between the multidimensional model in the relational implementation and the document-oriented dataset, which implies describing the relational data warehouse schema and the schema of the document-oriented dataset using ontologies to semi-automate their comparison and integration. The contribution of this thesis comprises two components: 1) method for ontology extraction from a document-oriented data source that results in an ontology suitable for multidimensional modeling, and 2) ontology-supported semi-automatic procedure for enrichment of a relational data warehouse schema with the multidimensional concepts found in a document-oriented data source.