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Finding Data Should be Easier than Finding Oil

Kharlamov, E., Skjaeveland, M., Hovland, D., Mailis, T., Jimenez-Ruiz, E. ORCID: 0000-0002-9083-4599, Xiao, G., Soylu, A., Horrocks, I. and Waaler, A. (2018). Finding Data Should be Easier than Finding Oil. In: 2018 IEEE International Conference on Big Data (Big Data). . UNSPECIFIED. ISBN 978-1-5386-5035-6

Abstract

The competitiveness of modern enterprises heavily depends on their ability to make the right business decisions by relying on efficient and timely analysis of the right business critical data. In large and data intensive companies such as Equinor, a Norwegian multinational oil and gas company with more than 20,000 employees, gathering such data is not a trivial task due to the growing size and complexity of corporate information sources. As a result, the data gathering task is often the most time-consuming part of the decision making process, in particular when it comes to the work processes of Equinor's exploration geologists that should find in a timely manner new exploitable accumulations of oil or gas in given areas by analysing data about these areas. In this work we present our experience in addressing this data challenge tast at Equinor. We have developed and deployed at Equinor a semantic data access system that relies on the Ontology Based Data Access (OBDA) approach. Our system is based on our solid theoretical contributions and has been extensively evaluated at Equinor.

Publication Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Publisher Keywords: Geology, Ontologies, Oils, Semantics, Companies, Query processing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QE Geology
Departments: School of Mathematics, Computer Science & Engineering > Computer Science
URI: https://openaccess.city.ac.uk/id/eprint/22925
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