Introducing the Open Energy Ontology: Enhancing Data Interpretation and Interfacing in Energy Systems Analysis

  • Meisam Booshehri
  • Lukas Emele
    Senior Researcher / Head of Energy Policy & Scenarios subdivision Energy & Climate
  • Simon Flügel
  • Johannes Frey
  • Ulrich Frey
  • Martin Glauer
  • Janna Hastings
  • Christian Hofmann
  • Carsten Hoyer-Klick
  • Ludwig Hülk
  • Anna Kleinau
  • Kevin Knosala
  • Leander Kotzur
  • Patrick Kuckertz
  • Till Mossakowski
  • Christoph Muschner
  • Fabian Neuhaus
  • Michael Pehl
  • Martin Robinius
  • Vera Sehn
  • Mirjam Stappel

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).

Published in: Energy and AI, 2021, 100074, ISSN 2666-5468