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  Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis

Booshehri, M., Emele, L., Flügel, S., Förster, H., Frey, J., Frey, U., Glauer, M., Hastings, J., Hofmann, C., Hoyer-Klick, C., Hülk, L., Kleinau, A., Knosala, K., Kotzur, L., Kuckertz, P., Mossakowski, T., Muschner, C., Neuhaus, F., Pehl, M., Robinius, M., Sehn, V., Stappel, M. (2021): Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis. - Energy and AI, 5, 100074.
https://doi.org/10.1016/j.egyai.2021.100074

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 Creators:
Booshehri, Meisam1, Author
Emele, Lukas1, Author
Flügel, Simon1, Author
Förster, Hannah1, Author
Frey, Johannes1, Author
Frey, Ulrich1, Author
Glauer, Martin1, Author
Hastings, Janna1, Author
Hofmann, Christian1, Author
Hoyer-Klick, Carsten1, Author
Hülk, Ludwig1, Author
Kleinau, Anna1, Author
Knosala, Kevin1, Author
Kotzur, Leander1, Author
Kuckertz, Patrick1, Author
Mossakowski, Till1, Author
Muschner, Christoph1, Author
Neuhaus, Fabian1, Author
Pehl, Michaja2, Author              
Robinius, Martin1, Author
Sehn, Vera1, AuthorStappel, Mirjam1, Author more..
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: Heterogeneous data, different definitions and incompatible models are a huge problem in many domains, with no exception for the field of energy systems analysis. Hence, it is hard to re-use results, compare model results or couple models at all. Ontologies provide a precisely defined vocabulary to build a common and shared conceptualisation of the energy domain. Here, we present the Open Energy Ontology (OEO) developed for the domain of energy systems analysis. Using the OEO provides several benefits for the community. First, it enables consistent annotation of large amounts of data from various research projects. One example is the Open Energy Platform (OEP). Adding such annotations makes data semantically searchable, exchangeable, re-usable and interoperable. Second, computational model coupling becomes much easier. The advantages of using an ontology such as the OEO are demonstrated with three use cases: data representation, data annotation and interface homogenisation. We also describe how the ontology can be used for linked open data (LOD).

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 Dates: 2021-04-052021-04-272021-05-27
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.egyai.2021.100074
MDB-ID: No data to archive
Research topic keyword: Energy
Model / method: Open Source Software
PIKDOMAIN: RD3 - Transformation Pathways
Organisational keyword: RD3 - Transformation Pathways
Regional keyword: Europe
Working Group: Energy Systems
OATYPE: Gold Open Access
 Degree: -

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Title: Energy and AI
Source Genre: Journal, other, oa
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Pages: - Volume / Issue: 5 Sequence Number: 100074 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/energy-and-ai
Publisher: Elsevier