SiSEG-Auto Semantic Annotation Service to Integrate Smart Energy Data

Maliheh Haghgoo, Amirhossein Nazary Aghche Mazary and Antonello Monti
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Maliheh Haghgoo: E.ON Energy Research Center, Institute for Automation of Complex Power Systems, RWTH Aachen University, Mathieustraße 10, 52074 Aachen, Germany
Amirhossein Nazary Aghche Mazary: E.ON Energy Research Center, Institute for Automation of Complex Power Systems, RWTH Aachen University, Mathieustraße 10, 52074 Aachen, Germany
Antonello Monti: E.ON Energy Research Center, Institute for Automation of Complex Power Systems, RWTH Aachen University, Mathieustraße 10, 52074 Aachen, Germany

Energies, 2022, vol. 15, issue 4, 1-16

Abstract: In a modern smart energy system, the amount of available data from various sources is growing significantly. Other sectors such as medical or social sectors exhibit the same phenomenon. Due to the amount, complexity and heterogeneity of data, a complex algorithm is required for the integration and analysis of heterogeneous data sources. The Web of Things and semantic-based approaches address the fragmentation of standards, platforms, services and technologies in smart energy and non-energy sectors, and enable heterogeneous data integration and interoperability. This paper presents SiSEG, a semantic annotation service that is developed to automate the process of annotating data and address the problem of heterogeneous data integration in a reusable and extensible way by using the fuzzy method. Moreover, the accuracy of SiGEG has been evaluated.

Keywords: semantic annotation; smart energy data integration; web of things; heterogeneous data-set; semantic web; AI (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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