Faculty of Computer Science

Research Group Theoretical Computer Science

Oberseminar: Heterogene formale Methoden

Abstract:

Our ability to reduce greenhouse gas emissions depends on the amount and type of energy we use. Consequently, energy experts are motivated to foresee the future and communicate their perspectives on how to create systems that are less harmful to the environment. However, the outlooks of energy studies are structured and published in a variety of ways. Such variation in narratives and formats makes it challenging to compare the results. Often, it is necessary to conduct extensive data preprocessing before a comparison. Therefore, the need for valid and frequent comparisons calls for methods capable of unifying different climate and energy scenarios in a coherent structure using a common standard vocabulary. Knowledge graphs are potent instruments for facilitating data access and integration.

In this talk, we present the Open Energy Knowledge Graph as a tool to store, explore and compare energy-related scenarios. By leveraging the Open Energy Ontology as its schema, the proposed knowledge graph makes it easier to understand, share, reuse, and compare scenarios from various organizations.