Skip to main content
Article thumbnail
Location of Repository

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. 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:
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • (external link)
  • (external link)
  • Suggested articles

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.