Extension of the Open Energy Ontology

Kurzfassung

An important prerequisite for the development of a connected database infrastructure is the documentation of a consistent terminology. The aim is to ensure that data is understood equally by both human and machine users. A categorization is to be developed from which a common data model can be derived. The overarching goal is to bring together many experts from different fields and capture their knowledge in a shared ontology. Ontologies enable the unambiguous categorization of terms and definitions. With a standardized ontology, it becomes possible to compare data with different structures. The foundation of the Open Energy Ontology (OEO) is being developed in the research project \emph{SzenarienDB}. The OEO is using the Web Ontology Language (OWL) with the help of the open-source software Protégé\footnote{\url{https://protege.stanford.edu/}}. Based on this foundation, a modular system of ontologies is being developed. Since the research field of energy system analysis covers a wide range of areas, the ontology will be divided into well-defined subdomains. Conceptual spaces such as geography, economics, social science, and computer science and modeling play a role.The general structure and the development process is described in more detail in \citet{OpenEnergyOntology}. Technical goal of the extension of the OEO is to increase the level of formalization of data schemas and ontologies. An important factor that ensures the sustainability of the results is the availability of tools and processes for domain experts within the consortium and the community to ensure long-term maintenance and expansion of the created ontologies. This report consists of several chapters corresponding to different work packages that focus on various data types and areas within the LOD-GEOSS project. Each work package is led by different institutions with significant expertise in the respective data domains. Other participating stakeholders contribute their experiences from their diverse modeling worlds to ensure the developed results have broad applicability.