Abstract
Advancements in artificial intelligence and machine learning have strongly impacted all fields of research in the past few years. The application of these new methods is often restricted due to a lack of access to sufficient amounts of high-quality data, an issue created through decades of manual and inconsistent data management. In the example of Li-ion battery research, which is a very dynamic field of research, this is an especially widespread problem. Since data is commonly still managed separately by the individual researchers, standard formats or tools are either missing completely or specific to an institute. To resolve this issue, we propose an ontology-based framework that emphasizes strong data harmonization and standardization. We combine these data structures with an intuitive web platform in order to simplify data management and reduce the time burden for the individual researcher. Our platform-based approach strengthens collaboration between institutions and enables battery researchers to create data sets that are suitable for data science and comparable across projects.
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Acknowledgements
The authors gratefully acknowledge the financial support of the German Federal Ministry for Education and Research (BMBF) within the project DigiBatMat (03XP0367D). DigiBatMat is a joint project of the August-Wilhelm Scheer Institute, the Leibniz Institute for New Materials, the Aalen University of Technology and Economics, the KIT Institute for Applied Informatics and Formal Description Methods as well as the Institute for Particle Technology and the Institute for Machine Tools and Manufacturing Technology from TU Braunschweig.
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Nebel, V., Mutz, M., Heim, Y., Werth, D. (2024). Overcoming the Challenges of Data Harmonization: A Platform Approach from Li-Ion Battery Research. In: Ullah, A., Anwar, S., Calandra, D., Di Fuccio, R. (eds) Proceedings of International Conference on Information Technology and Applications. ICITA 2022. Lecture Notes in Networks and Systems, vol 839. Springer, Singapore. https://doi.org/10.1007/978-981-99-8324-7_5
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