With an increasing importance of energetic aspects of appliances, such as consumption and emission values, due to financial and political goals, energy system modeling is gaining more attention. This results in numerous frameworks and models for specific applications producing a huge amount of heterogeneous data. In order to leverage this data across models and frameworks, methods for data handling such as comparison, integration, or exchange need to be improved. As a first part of that, the meaning of vocabulary needs to be unified. Furthermore, a machine-readable approach is desirable, so that further processing can be automated more easily. The Open Energy Ontology (OEO) tries to solve these problems by providing definitions of concepts that can be used for the annotation of data sets, hence clarifying the meaning of used terms. A lack of concepts from the transport domain was identified, and therefore, this thesis provides an enhancement to the OEO by adding terms for the transport domain in a systematic, relevance-based manner. As a guidance for the approach, research questions were formulated and evaluated. Most of the added terms belong to one of the categories vehicle types, transport types, infrastructure, operational environment, energy carrier for propulsion, operational mode, or measurement values. In addition, the usage of the OEO for annotating three exemplary data sets is examined, and assumptions from two exemplary studies are formalized with OEO concepts. These applications showed some difficulties that are further discussed, alongside limitations and assumptions. Among the difficulties are the definition of axioms, the choice of concepts during annotation, and the expressiveness of the implementation language. For the limits, the scope and the level of detail are two important points. The most important assumption is about the handling of annotations, where no precise, single OEO concept exists.
Lastly, some ideas for further research based on the contributions and insights of this thesis are suggested.
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With an increasing importance of energetic aspects of appliances, such as consumption and emission values, due to financial and political goals, energy system modeling is gaining more attention. This results in numerous frameworks and models for specific applications producing a huge amount of heterogeneous data. In order to leverage this data across models and frameworks, methods for data handling such as comparison, integration, or exchange need to be improved. As a first part of that, the me...
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