FAIR Data in Energy Systems Analysis

Kurzfassung

Modelling of future energy systems requires large amounts of heterogeneous input data and also generates heterogeneous result data across a number of scientific disciplines such as e.g. meteorology, engineering, geography, social-sciences and economy. As this modelling work supports the transition to a more sustainable society, open and transparent modelling is important to inform the public debate. The domain of energy systems analysis is therefore moving towards FAIR (Findable, Accessible, Interoperable and Reuseable) data. With this poster we want to show an infrastructure we developed around the dbpedia databus, the open energy platform, open energy metadata, and the open energy ontology which eases open data sharing, semantic data searches, data discovery and interoperable data reuse within our modelling domain. Meteorological data is important in planning and operation of future energy systems. To ease the use of this data and to improve the integration of meteorological data into the data pipelines, energy relevant meteorological data should also use these infrastructures for sharing and annotation of data.