Addressing Streaming and Historical Data in OBDA Systems: Optique’s Approach
Authors: 
I. Horrocks
Authors: 
T. Hubauer
Authors: 
E. Jiménez-Ruiz
Authors: 
E. Kharlamov
Authors: 
M. Koubarakis
Authors: 
R. Möller
Authors: 
K. Bereta
Authors: 
C. Neuenstadt
Authors: 
Ö. Özçep
Authors: 
M. Roshchin
Authors: 
P. Smeros
Authors: 
D. Zheleznyakov
Date published: 
2013
Published In: 
In Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data (Know@LOD 2013). Montpellier, France. May 26-30
Type: 
Conference Article
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.
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