Optique: Simple, Oil & Gas-oriented Access to Big Data in Exploration
- M. G. Skjæveland (University of Oslo) | D. Cameron (University of Oslo) | M. Giese (University of Oslo) | D. Hovland (University of Oslo) | A. Waaler (University of Oslo) | E. Bjørge (Statoil) | K. Tungland (Statoil)
- Document ID
- Society of Petroleum Engineers
- SPE Intelligent Energy International Conference and Exhibition, 6-8 September, Aberdeen, Scotland, UK
- Publication Date
- Document Type
- Conference Paper
- 2016. Society of Petroleum Engineers
- Ontology-based data access, Semantic technologies, Data Integration, Query Federation, Big Data
- 1 in the last 30 days
- 251 since 2007
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The growth of available information sources in the industry requires new efficient methods for data access by end-users whose ability to analyse data is at the core of making business decisions. Data analysis suffer from end-users' ability to efficiently clean and integrate and query data spread across a multitude of different data sources. Current centralised approaches, where an IT expert translates the requirements of domain experts into Extract-Transform-Load (ETL) processes to integrate the data and to apply predefined analytical reporting tools, are too heavy-weight and inflexible. To support interactive and efficient data exploration directly by domain experts, without IT expert involvement, a more flexible and modular information systems architecture is needed.
The Optique platform reduces the time and cost of data access dramatically by automating the process of translating an information requirement into the retrieval of the relevant data. The key to this automated translation is Ontology-Based Data Access (OBDA), where the central idea is to use an ontology, a semantically rich conceptual model of the problem domain, and mappings, that describe the relationship between the ontology and the data sources, to allow users to formulate queries and receive answers in a domain-centric and intelligible form, without any knowledge of the implementational details of the data sources. We present the Optique platform as a next generation OBDA system featuring user-friendly query formulation interface(s), automated query translation over multiple sources using novel ontology and mapping management components, and distributed query optimisation and execution exploiting cloud resources for scale-out.
At Statoil Exploration, the Optique platform integrates multiple large and complex data sources from different vendors, and allows G&G experts to execute and present detailed information needs in the subsurface domain directly into existing expert client tools and also into web portals for easy information distribution of central assets across the enterprise.
|File Size||1 MB||Number of Pages||8|
Calvanese, D., Cogrel, B., Komla Ebri, S., Kontchakov, R., Lanti, D., Rezk, M., Rodriguez-Muro, M., and Xiao, G., Ontop 2016, Answering SPARQL Queries over Relational Databases, Semantic Web Journal, http://www.semantic-web-journal.net/content/ontop-answering-sparql-queries-over-relational-databases-1.
Crompton, J., 2008, Keynote address at the W3C Workshop on Semantic Web in Oil & Gas Industry, Houston, TX, USA, 9–10 December, http://www.w3.org/2008/12/ogws-slides/Crompton.pdf (Accessed 9 June 2016).
Giese, M., Soylu, A., Vega-Gorgojo, G.. 2015, Optique: Zooming in on Big Data, IEEE Computer, 48(3), March, pp. 60–67, http://doi.ieeecomputersociety.org/10.1109/MC.2015.82.
Kllapi, H., Sakkos, P., Delis, A., Gunopulos, D., and Ioannidis, Y., 2015. Elastic Processing of Analytical Query Workloads on IaaS Clouds, The Computing Research Repository (CoRR), http://arxiv.org/abs/1501.01070.
Jimenez-Ruiz, E., Kharlamov, E., Zheleznyakov, D., Horrocks, I., Pinkel, C., Skjæveland, M. G., Thorstensen, E., Mora, J. 2015, BootOX: Practical Mapping of RDBs to OWL 2, in M. Arenas. (Eds.): The Semantic Web – ISWC 2015, 14th International Semantic Web Conference, Bethlehem, PA, USA, October 11–15, Part II, LNCS 9367, pp. 113–132, http://dx.doi.org/10.1007/978-3-319-25010-6_7.
Kharmalov, E., Solomakhina, N.Özçep, Ö.L.. 2015, How Semantic Technologies Can Enhance Data Access at Siemens Energy, in The Semantic Web – ISWC 2014, 13th International Semantic Web Conference, Riva del Garda, Italy, October 19-23, Proceedings, Part I, LNCS 8796, pp. 601–619. http://dx.doi.org/10.1007/978-3-319-11964-9_38.
Kharmalov, E., Hovland, D.Jiménez-Ruiz, E.. 2015, Ontology Based Access to Exploration Data at Statoil, in M. Arenas. (Eds.): The Semantic Web – ISWC 2015, 14th International Semantic Web Conference, Bethlehem, PA, USA, October 11–15, Part II, LNCS 9367, pp. 93–112. http://dx.doi.org/10.1007/978-3-319-25010-6_6.
Özçep, L., Möller, R., and Neuenstadt, C., 2015. Stream-Query Compilation with Ontologies, Proceedings of the 28th Australasian Joint Conference on Artificial Intelligence 2015 (AI 2015), http://link.springer.com/chapter/10.1007%2F978-3-319-26350-2_40.
Skjæveland, MG., Lian, E., Horrocks, I, 2013. Publishing the Norwegian Petroleum Directorate's FactPages as Semantic Web Data. In The Semantic Web – ISWC 2013, volume 8219 of LNCS, Springer, http://dl.acm.org/citation.cfm?id=2717190.
Soylu, A., Giese, M., Jimenez-Ruiz, E. 2015, Experiencing OptiqueVQS: a multi-paradigm and ontology-based visual query system for end users, Universal Access in the Information Society, Springer, http://link.springer.com/article/10.1007%2Fs10209-015-0404-5.