Addressing streaming and historical data in OBDA systems : optique's approach (statement of interest)

First published in
CEUR workshop proceedings  
Number in series
992
Start Page
33
End Page
40
Citation
CEUR Workshop Proceedings (992): Seite 33-40 (2013)
Contribution to Conference
2nd International Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data, KNOW@LOD 2013, Montpellier; France  
Scopus ID
2-s2.0-84908699836
Publisher
RWTH Aachen
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.
DDC Class
004: Informatik