INSIDE: an Ontology-based Data Integration System Applied to the Oil and Gas Sector


Context: Data integration remains a major challenge facing organizations in the information age. Despite the advances made in recent decades, new approaches have become necessary to deal with new challenges such as Big Data. Problem: Semantic heterogeneity is a significant problem faced by companies in the oil and gas sector, as it makes it difficult to exchange information with other companies. Furthermore, there is a shortage of data integration systems that use open source technologies to deal with semantics, interoperability and scalability. Solution: INSIDE - Semantic Interoperability for Engineering Data Integration - an information system based on ontologies for data integration developed for an oil and gas company. SI Theory: This work is influenced by Representation Theory, based on the idea that an information system is a faithful representation of certain phenomena in the real world. Method: Review of state of the art on system architectures for data integration and use of methodologies for elaborating ontologies that represent the knowledge base of the information system. Summary of Results: Implementation of a prototype that allows querying heterogeneous data sources using a vocabulary familiar to the user, removing ambiguities from data with semantics. Contributions and Impact in IS area: The development of a solution for data integration using open source technologies tested with real-world data from a company in the oil and gas sector that can serve as a reference for developing new applied systems to other sectors.

Palavras-chave: Information Systems, Data Integration, Semantic Web, Ontology


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CAMPOS, Júlio Gonçalves; ALMEIDA, Vitor Pinheiro De; ARMAS, Elvismary Molina De; SILVA, Geiza Maria Hamazaki Da; CORSEUIL, Eduardo Thadeu; GONZALEZ, Fernando Rodrigues. INSIDE: an Ontology-based Data Integration System Applied to the Oil and Gas Sector. In: SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 19. , 2023, Maceió/AL. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 .