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@ARTICLE{Booshehri:894340,
      author       = {Booshehri, Meisam and Emele, Lukas and Flügel, Simon and
                      Förster, Hannah and Frey, Johannes and Frey, Ulrich and
                      Glauer, Martin and Hastings, Janna and Hofmann, Christian
                      and Hoyer-Klick, Carsten and Hülk, Ludwig and Kleinau, Anna
                      and Knosala, Kevin and Kotzur, Leander and Kuckertz, Patrick
                      and Mossakowski, Till and Muschner, Christoph and Neuhaus,
                      Fabian and Pehl, Michaja and Robinius, Martin and Sehn, Vera
                      and Stappel, Mirjam},
      title        = {{I}ntroducing the {O}pen {E}nergy {O}ntology: {E}nhancing
                      data interpretation and interfacing in energy systems
                      analysis},
      journal      = {Energy and AI},
      volume       = {5},
      issn         = {2666-5468},
      address      = {Amsterdam},
      publisher    = {Elsevier ScienceDirect},
      reportid     = {FZJ-2021-03188},
      pages        = {100074 -},
      year         = {2021},
      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).},
      cin          = {IEK-3},
      ddc          = {624},
      cid          = {I:(DE-Juel1)IEK-3-20101013},
      pnm          = {1111 - Effective System Transformation Pathways (POF4-111)
                      / 1112 - Societally Feasible Transformation Pathways
                      (POF4-111)},
      pid          = {G:(DE-HGF)POF4-1111 / G:(DE-HGF)POF4-1112},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001058083100005},
      doi          = {10.1016/j.egyai.2021.100074},
      url          = {https://juser.fz-juelich.de/record/894340},
}