Towards Semantic Geo/BI: A Novel Approach for Semantically Enriching Geo/BI Data with OWL Ontological Layers (OOLAP and ODW) to Enable Semantic Exploration, Analysis and Discovery of Geospatial Business Intelligence Knowledge
International Journal of Information Engineering and Electronic Business
To contribute in filling up the semantic gap in data warehouses and OLAP data cubes, and enable semantic exploration and reasoning on them, this paper highlights the need for semantically augmenting Geo/BI data with convenient semantic relations, and provides OWL-based ontologies (ODW and OOLAP) which are capable of replicating data warehouses (respectively OLAP data cubes) in the form semantic data with respect of Geo/BI data structures, and which enable the possibility of augmenting these
... ntic BI data with semantic relations. Moreover, the paper demonstrates how ODW and OOLAP ontologies can be combined to current Geo/BI data structures to deliver either pure semantic Geo/BI data or mixed semantically interrelated Geo/BI data to business professionals. Enriched semantic/business metadata: To help OLAP users in establishing a link between OLAP metrics values and business goals they have to reach,  proposed to enrich business metadata with a UML-based meta-model which defines details regarding enterprise goals (e.g. Goal name, Goal perspective, Metric name, Metric target value + unit, etc.). That model of goals is then linked to the data warehouse containing the BI data, by using the technique of model weaving, which consists of establishing links describing the relationships between the goals model and the data warehouse model. This linkage is then used to display business metadata (e.g. business goals) related to OLAP fact data (e.g metrics values) such as illustrated in Fig. 1 provided by the authors. The same technique is used by  to "integrate Goals with Process Warehouse for Business Process Analysis". Ontology-based semantic annotation: semantic annotation is another method proposed by authors to fill in the semantic gap within BI data.  for example proposed to enrich OLAP data cubes by annotating them with ontological descriptions. These annotations are then exploited to display the semantics attached to a dimension or a measure like for instance, how it is aggregated or calculated. Fig. 2 shows an example of semantic annotation regarding the calculation formula of the measure ROI (Return On Investment).