Understanding Industrial Processes using Process-Driven Visual Analytics

Josef Suschnigg, Stefan Thalmann, Matej Vukovic, Florian Ziessler, Jürgen Mangler, Tobias Schreck

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The application of data analysis techniques promises innovative and valuable insights into industrial processes. Those processes can be managed via process engines, which also collect large amounts of data, relevant to the respective process. To reduce the complexity of the large amounts of data and to support users gaining new process knowledge, also from streaming data in an online fashion, a visual analytics approach seems promising. The presented concept combines the process engine with interactive process-driven visual data analysis and gives an outlook on how a prototype, for industrial process understanding, will be implemented.
Original languageEnglish
Title of host publicationProceedings of the 10th International Conference on Professional Knowledge Management
Pages303-306
Number of pages4
DOIs
Publication statusPublished - 2019

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