Research Data Management
About
The Research Data Management specialist group develops methods that improve the findability, accessibility, interoperability and reusability of research software and data in energy system research in line with the FAIR principles. This includes the development of special metadata formats, integrating model interfaces, approaches to data integration, validation and evaluation in model workflows, artificial intelligence methods for data procurement and ontologies as a common language basis. In addition, selected models and data from the institute are made available to potentially interested parties via graphical user interfaces.
Research Topics
·The research topics include the development of semantic data and metadata models and their implementation in state-of-the-art databases and knowledge graphs along the FAIR and Linked Open Data principles, the integration of software and data into reproducible and reusable computational workflows, the extraction of quantitative information from scientific literature using natural language processing and the development of high-quality user interfaces.
Members
Research Fields
·Within the framework of research data management, methods are being developed to improve the discoverability, accessibility, interoperability, and reusability of research data in accordance with the FAIR principles. In addition to classic result outputs, such as journal publications, data collections, or software models, supplementary outputs, such as presentations, documentation, code, video tutorials, and digital process workflows, are also being taken into account. In order to make the research data sustainably usable and efficiently exchangeable with the research community, metadata formats are being developed that are specially adapted to the needs of energy system analysis and include, amongst other things, information on data provenance and licensing regulations.
·Within the framework of externally-funded projects such as LOD-GEOSS and NFDI4Ing, distributed database structures and semantic knowledge graphs are being established which, as integrating interfaces, support the research area in the development of a common research data infrastructure. At the same time, the Open Energy Ontology initiative is being created as a common language basis for promoting scientific exchange and increasing the degree of automation and efficiency of energy system analysis through the machine-readable formalization of domain-specific concepts and contexts.

Graphical user interfaces (GUIs) offer the advantage of making data analysis more intuitive and easier to read and understand. They typically provide users with immediate visual feedback on the impact of each action. Our GUIs are primarily aimed at decision-makers who are involved in the Institute's projects and therefore want the easiest possible access to project results. These GUIs were created using the latest web technologies and powerful programming languages, allowing for smooth handling of the elements and making practical decisions in the shortest possible time.
The Hydrogen Atlas Africa, a GUI recently developed by the Institute, is an example of a web software that offers an analysis of hydrogen potential in Africa. It is a web atlas that quickly identifies suitable areas for the construction of wind farms, solar parks, and hydrogen production plants, thus enabling decision-making information for the development of a hydrogen infrastructure.
