| Bibliography | Weber, Christian; Hirmer, Pascal; Reimann, Peter: A Model Management Platform for Industry 4.0 - Enabling Management of Machine Learning Models in Manufacturing Environments.
In: Abramowicz, Witold (ed.); Alt, Rainer (ed.); Klein, Gary (ed.); Paschke, Adrian (ed.); Sandkuhl, Kurt (ed.): Proceedings of the 23rd International Conference on Business Information Systems (BIS).
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
Lecture Notes in Business Information Processing, english.
Springer International Publishing, November 2020.
ISSN: 1865-1348.
Article in Proceedings (Conference Paper).
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| CR-Schema | H.3.4 (Information Storage and Retrieval Systems and Software)
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| Keywords | Model Management; Machine Learning; Metadata Tracking |
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| Abstract | Industry 4.0 use cases such as predictive maintenance and product quality control make it necessary to create, use and maintain a multitude of di erent machine learning models. In this setting, model management systems help to organize models. However, concepts for model management systems currently focus on data scientists, but do not support non-expert users such as domain experts and business analysts. Thus, it is dicult for them to reuse existing models for their use cases. In this paper, we address these challenges and present an architecture, a metadata schema and a corresponding model management platform.
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| Department(s) | University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems
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| Project(s) | GSaME-NFG
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| Entry date | May 5, 2020 |
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