Knowledge graphs

Knowledge graphs link our data in a meaningful way.

We ‘face’ heterogeneous unstructured data sources within chemical engineering, developing sophisticated data processing pipelines. These specialized pipelines can transform such data into structured and linked target data. The Chemical Engineering Knowledge Graph will provide linked data for future AI applications in chemical engineering.

Key publications

• Schweidtmann, A. M., Esche, E., Fischer, A., Kloft, M., Repke, J. U., Sager, S., & Mitsos, A. (2021). Machine Learning in Chemical Engineering: A Perspective. Chemie Ingenieur Technik.
• Weber, J. M., Guo, Z., Zhang, C., Schweidtmann, A. M., & Lapkin, A. A. (2021). Chemical data intelligence for sustainable chemistry. Chemical Society Reviews.