Finding Data Should be Easier than Finding Oil

Evgeny Kharlamov, Martin Skjaveland, Dag Hovland, Theofilos Mailis, Ernesto Jimenez-Ruiz, Guohui Xiao, Ahmet Soylu, Ian Horrocks, Arild Waaler
<span title="">2018</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/faqqmambavbalpofpx3p6nntua" style="color: black;">2018 IEEE International Conference on Big Data (Big Data)</a> </i> &nbsp;
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
more &raquo; ... e-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. • quality of the system's deployment, • efficiency of the system's query processing, and • effectiveness and efficiency of the system's query formulation support.
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