Data reuse and meta-data handling remain tricky problem for both the designers and managers, especially when schemas reverse engineering is on demand and that some data are stored in materialized views. In this paper, we tackle such problem by using ontology-based meta-materialized views. Indeed, ontologies, which are semantics-based, ensure the stability of the underlying schemas of the data repositories and to ease the overall access and processing of the data and meta-data. Our proposal is sustained by a set of conceptual guidelines and outlined through a case study example.
Both association rules and ontologies are domain-based knowledge. However, the first is unexpected discovered knowledge from databases, while the second is a priori knowledge. In this paper, based on a generic meta-schema as common referential and theoretical foundation, we show how a set of computed and pruned association rules can be useful for enriching a domain ontology. To this end, the meta-schema is scanned with the itemsets appearing in each association rule. Then, according to the formal links between the concepts or the attributes involved, a semantic-based check constraint is built. As a result, the ontology and the database are continuously tuned with new semantics.
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