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Journal Article

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

Authors

Booshehri,  Meisam
External Organizations;

Emele,  Lukas
External Organizations;

Flügel,  Simon
External Organizations;

Förster,  Hannah
External Organizations;

Frey,  Johannes
External Organizations;

Frey,  Ulrich
External Organizations;

Glauer,  Martin
External Organizations;

Hastings,  Janna
External Organizations;

Hofmann,  Christian
External Organizations;

Hoyer-Klick,  Carsten
External Organizations;

Hülk,  Ludwig
External Organizations;

Kleinau,  Anna
External Organizations;

Knosala,  Kevin
External Organizations;

Kotzur,  Leander
External Organizations;

Kuckertz,  Patrick
External Organizations;

Mossakowski,  Till
External Organizations;

Muschner,  Christoph
External Organizations;

Neuhaus,  Fabian
External Organizations;

/persons/resource/michaja.pehl

Pehl,  Michaja
Potsdam Institute for Climate Impact Research;

Robinius,  Martin
External Organizations;

Sehn,  Vera
External Organizations;

Stappel,  Mirjam
External Organizations;

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Fulltext (public)

25641oa.pdf
(Publisher version), 2MB

Supplementary Material (public)
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Citation

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


Cite as: https://publications.pik-potsdam.de/pubman/item/item_25641
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).