Abstract
Innovation processes are influenced by cyclical factors and involve many stakeholders from different disciplines within a company. Working together in transdisciplinary teams can save time and therefore improve the innovation process. However, the stakeholders have a completely different understanding of the processes based on their domain specific knowledge and experience and the requirements of their individual task. To avoid conflicts between the disciplines, this paper presents an interactive two-level graph-based approach to visualize cross-discipline model dependencies. This visualization can help to support the transdisciplinary communication and comprehension.
Original language | English |
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Pages (from-to) | 317-322 |
Number of pages | 6 |
Journal | IFAC Proceedings Volumes (IFAC-PapersOnline) |
Volume | 52 |
Issue number | 19 |
DOIs | |
State | Published - 2019 |
Event | 14th IFAC Symposium on Analysis, Design, and Evaluation of Human Machine Systems, HMS 2019 - Tallinn, Estonia Duration: 16 Sep 2019 → 19 Sep 2019 |
Keywords
- Communication
- Human factors
- Information integration
- Information retrieval
- Interaction
- Interdisciplinary design
- Man/machine interaction