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Temporal RDF System for Power Utilities

Authors:
Mohamed Gaha
Arnaud Zinflou
Alexandre Bouffard
Luc Vouligny
Mathieu Viau
Christian Langheit
Etienne Martin

Keywords: Ontology; Heterogeneous data source; Versioning; Data-Mining tools; Temporal data.

Abstract:
Temporal data is a critical component in many applications. This is especially true in analytical applications for the smart grid. The analytical process often requires uncovering and analysing data and complex relationships from heterogeneous and distributed data sources that change over time. A common approach for this task is the use of relational databases or even data warehouses, which unfortunately do not allow reasoning and inference. Ontologies and semantic technologies are proving useful to leverage the value already embodied in existing systems without replacing the enterprise systems. In this paper, we describe how the usage of a formal representation of knowledge can support elaborated processes such as storing and extracting temporal data. The first example uses a semantic approach to capture and manage time series changes. The second example is a direct application of the first one. It consists on an efficient RapidMiner extension that allows end users to transparently extract temporal data from heterogeneous data sources.

Pages: 32 to 37

Copyright: Copyright (c) IARIA, 2015

Publication date: July 19, 2015

Published in: conference

ISSN: 2308-4510

ISBN: 978-1-61208-420-6

Location: Nice, France

Dates: from July 19, 2015 to July 24, 2015