Interview with Franziska Schöniger
Researcher in the Energy Economics Group (EEG) at the Institute of Energy Systems and Electrical Drives
Data management is a very important part of our modeling work
What is your field of research?
I am working for the Energy Economics Group, being part of the working group “Renewable Energy Policy and Markets”. Within this group, renewable energy technologies and markets and their future prospects are analyzed. We address questions of policy design, market interactions, and sustainability aspects (e.g. for bioenergy) alongside analyses of broader, techno-economic impacts of increasing shares of renewable energies in the future.
Can you give us examples of how you use data management in your everyday work?
Modeling is a key element in our assessments, done at the energy system level with a focus on the impact of policy interventions, the design of instruments/support schemes, or aspects of system integration for renewables in Europe’s power system. For these activities, we develop our own models or extend the (sector and geographical) coverage of open-source tools. The open-source movement in the (energy) modeling world has gained momentum in recent years and offers huge opportunities for energy and climate research. However, this confronts researchers with new challenges in data management. Thus, data management is a very important part of our modeling work: from organizing input data to making output data visible and transparent. Therefore, I use data management as part of our project work for European or national research projects as well as for publications in the course of my PhD.
The teaching at our institute also includes data management practices, e.g. in the course “Open Source Energy System Modeling, opens an external URL in a new window” where students can learn the fundamentals of (open-source) data management and how to apply them in practice.
Are you using data repositories for data publication?
I use public data repositories (e.g. Zenodo) to make modeling data publicly available and assign licenses. I use this for example for the data underlying my modeling activities in research projects or scientific publications. Also, the open-source energy modeling community is collaborating via open repositories and is e.g. present on GitHub to cooperate and share modeling frameworks and data with others.