FAIR data is an enabler for artificial intelligence in chemical engineering
“The transformation of the chemical industry to a circular economy requires the design of integrated and efficient processes. In the current setting, this challenging task relies on manual literature review and flowsheet simulations. However, no public database for chemical process data exists. Instead, data is stored in unstructured formats in multiple different places. This is a major hurdle for process development as knowledge from earlier developments is not easily findable, accessible, interoperable, and reusable (FAIR). This lack of structured data is also a major hurdle for advancing process design through artificial intelligence (AI).”
“In the ChemEngAI research group, we envision establishing the Chemical Engineering Knowledge Graph (ChemEng KG). The ChemEng KG aims to process chemical information in a FAIR, 5-Star linked data format (making data openly available on the Web and linked to other data). This will enable researchers and industry to find and reuse process information, accelerating the development of processes. In addition, the graph database will be an enabler technology for breakthroughs in process development through AI and optimization.”
At the end of 2021, the ChemEng KG project received the NWO Open Science Fund and 4TU.ResearchData FAIR Data Fund to develop this work.
If you have any questions, please feel free to contact Artur Schweidtmann directly.
More information: https://www.tudelft.nl/tnw/over-faculteit/afdelingen/chemical-engineering/principal-scientists/artur-schweidtmann
Author: Artur Schweidtmann (Delft University of Technology)
Editor: Connie Clare (4TU.ResearchData)
Adapted cover photo by Colin Behrens from Pixabay
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