Authors:
Mario Nascimento Marques Junior
;
Eder Mateus Nunes Gonçalves
;
Silvia Botelho
and
Emanuel Estrada
Affiliation:
Center of Computational Sciences, Federal University of Rio Grande, Rio Grande, Brazil
Keyword(s):
Data Digitalization, Oil and Gas Industry, Ontology, Semantic Model.
Abstract:
Databooks are essential for monitoring and validating construction projects in the oil industry, containing crucial information like quality certificates and technical reports. However, manual analysis of these databooks is time-consuming, labor-intensive, and error-prone. This study proposes an intelligent system to streamline databook search and validation, enhancing efficiency and accuracy. Developing a valid conceptual model for databooks and their components presents a significant challenge. To overcome this, we focus on acquiring semantics for databooks and utilizing a semantic model for compliance checks. We introduce an ontology designed specifically for verifying completeness and compliance in Brazilian oil industry documents, encompassing domain knowledge and verification processes. Using the Methontology methodology, we create the ontology and integrate it with an annotation tool to validate its ability to incorporate semantic structures and facilitate compliance verificat
ion. Comparative analysis with manual verification by experts shows identical outcomes, confirming the effectiveness of the automated compliance checking process. The ontology-based approach offers advantages such as time savings, enhanced accuracy, and simplified work for specialists. This study contributes to oil industry document analysis by providing a semantic model that streamlines databook verification, with potential applications for compliance verification of complex documents in various domains.
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