Ontology Based Access to Exploration Data at Statoil
Ontology Based Data Access (OBDA) is a prominent approach to query databases which uses an ontology to expose data in a conceptually clear manner by abstracting away from the technical schema-level details of the underlying data. The ontology is ‘connecte
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University of Oxford, Oxford, UK [email protected] 2 University of Oslo, Oslo, Norway Free University of Bozen-Bolzano, Bolzano, Italy 4 Statoil ASA, Stavanger, Norway 5 fluid Operations AG, Walldorf, Germany
Abstract. Ontology Based Data Access (OBDA) is a prominent approach to query databases which uses an ontology to expose data in a conceptually clear manner by abstracting away from the technical schema-level details of the underlying data. The ontology is ‘connected’ to the data via mappings that allow to automatically translate queries posed over the ontology into data-level queries that can be executed by the underlying database management system. Despite a lot of attention from the research community, there are still few instances of real world industrial use of OBDA systems. In this work we present data access challenges in the data-intensive petroleum company Statoil and our experience in addressing these challenges with OBDA technology. In particular, we have developed a deployment module to create ontologies and mappings from relational databases in a semi-automatic fashion, and a query processing module to perform and optimise the process of translating ontological queries into data queries and their execution. Our modules have been successfully deployed and evaluated for an OBDA solution in Statoil.
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Introduction
The competitiveness of modern enterprises heavily depends on their ability to make use of business critical data in an efficient and timely manner. Providing this ability in data intensive enterprises is not a trivial task as the growing size and complexity of information sources makes data access and exploitation increasingly challenging. Indeed, data is often scattered across heterogeneous and autonomously evolving systems or has been adapted over the years to the needs of the applications they serve, making it difficult to extract data in a useful format for the business of the organisation. Statoil is a large and data intensive enterprise where the workflow of many units heavily depends on timely access to data. For example, the job of exploration geologists is to analyse existing relevant data in order to find exploitable c Springer International Publishing Switzerland 2015 M. Arenas et al. (Eds.): ISWC 2015, Part II, LNCS 9367, pp. 93–112, 2015. DOI: 10.1007/978-3-319-25010-6 6
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accumulations of oil or gas in given areas. This process is typically done in two separate steps: first by gathering data from multiple sources, then by analysing the data using specialised analytical tools. As is often the case in large enterprises, naming conventions for schema elements, constraints, and the structure of database schemata are very complex and documentation may be limited or nonexistent. As a result, the data gathering task is often the most timeconsuming part of the decision making process. Ontology Based Data Access (OBDA) [21] is a prominent approach to data access in which an ontology is used to mediate between data users and data sources. The ontology p
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