Semi-Automatically Generated Hybrid Ontologies for Information Integration

ABSTRACT Large and medium-sized enterprises and organizations are in many cases characterized by a heterogeneous and distributed information system infrastructure. For data processing activities as well as data analytics and mining, it is essential to establish a correct, complete and efficient consolidation of information. Information integration and aggregation are therefore fundamental steps in many analytical workflows. Furthermore, in order to evaluate and classify the result of an integrated data query and thus, the quality of resulting data analytics, it is previously necessary to determine the data quality of each processed data source. This paper aims mainly at the first aspect of the mentioned twofold challenge. Both, data dictionary as well as information source content are analyzed to derive the conceptual schema, which is then provided as a machine-readable description of the information source semantics. Several descriptions of the semantics can be integrated to a global view by eliminating possible redundancies and by applying ontology similarity measures. Attributes for data quality metrics are included in the descriptions but not yet determined. The implementation of the presented approach is evaluated by extracting the semantics of a specific MySQL database, represented as RDF triples

DBKDA 2020, The Twelfth International Conference on Advances in Databases, Knowledge, and Data Applications

The Twelfth International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2020) continued a series of events covering a large spectrum of topics related to advances in fundamentals on databases, evolution of relation between databases and other domains, data base technologies and content processing, as well as specifics in applications domains databases. Advances in different technologies and domains related to databases triggered substantial improvements for content processing, information indexing, and data, process and knowledge mining. The push came from Web services, artificial intelligence, and agent technologies, as well as from the generalization of the XML adoption. High-speed communications and computations, large storage capacities, and load-balancing for distributed databases access allow new approaches for content processing with incomplete patterns, advanced ranking algorithms and advanced indexing methods. Evolution on e-business, ehealth and telemedicine, bioinformatics, finance and marketing, geographical positioning systems put pressure on database communities to push the ‘de facto’ methods to support new requirements in terms of scalability, privacy, performance, indexing, and heterogeneity of both content and technology