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Addressing Streaming and Historical Data in OBDA Systems: Optique’s Approach (Statement of Interest)

By Ian Horrocks, Thomas Hubauer, Ernesto Jimenez-ruiz, Evgeny Kharlamov, Manolis Koubarakis, Ralf Möller, Konstantina Bereta, Christian Neuenstadt, Özgür Özçep, Mikhail Roshchin, Panayiotis Smeros and Dmitriy Zheleznyakov

Abstract

Abstract. In large companies such as Siemens and Statoil monitoring tasks are of great importance, e.g., Siemens does monitoring of turbines and Statoil of oil behaviour in wells. This tasks bring up importance of both streaming and historical (temporal) data in the Big Data challenge for industries. We present the Optique project that addresses this problem by developing an Ontology Based Data Access (OBDA) system that incorporates novel tools and methodologies for processing and analyses of temporal and streaming data. In particular, we advocate for modelling time time aware data by temporal RDF and reduce monitoring tasks to knowledge discovery and data mining.

Year: 2014
OAI identifier: oai:CiteSeerX.psu:10.1.1.415.6426
Provided by: CiteSeerX
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