Tool Chain to Extract and Contextualize Process Data for AI Applications

Research output: Contribution to journalResearch articleContributedpeer-review



Summarizing a key use case of a research workstream of the German publicly funded KEEN project, methods and tool chains are demonstrated to extract and to contextualize process data in an automated way based on engineering information. The contextualized process data serves as a high-quality data source for machine learning methods. The article covers the applied basic methodical approaches, design decisions and the results of a successful pilot installation of the developed tool chain.


Original languageEnglish
Pages (from-to)1070-1076
Number of pages7
JournalChemie Ingenieur Technik
Issue number7
Publication statusPublished - 21 Apr 2023

External IDs

Scopus 85152526368
Mendeley 471ec302-938e-3516-a50f-4c723816a0db
WOS 000971665200001
ORCID /0009-0000-3287-0295/work/142237521


Research priority areas of TU Dresden

Subject groups, research areas, subject areas according to Destatis


  • artificial intelligence, Data contextualization, Data management, Process industry, Tool chain, Artificial intelligence