Abstract
The worldwide patent database remains one of the least utilized resources in engineering design practice. Analyzing individual patent documents may be particularly challenging. Emerging computational approaches may soon enable us to automatically remodel the information content of patent documents to make them easier to read. For these approaches to be effective in practice, there is an urgent need to understand how design engineers process multimedia documents and how best to present information to them. To this end, we model the cognitive processes involved in patent analysis in terms of two models: the TRACE model of goal-directed document processing, and the Cognitive Theory of Multimedia learning (CTML). These models provide a cognitive basis for understanding the difficulties that designers may face during patent analysis. It also facilitates the identification and testing of information design principles that can be used to remodel patent documents to make them easier to search and comprehend. By testing these principles, our goal is to establish requirements for a new generation of patent analytics tools that are consistent with the ways that engineering designers think. This work introduces a new interdisciplinary research agenda, bringing together research about engineering design, patent analytics, multimedia learning, document search, and information design.
Original language | English |
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Pages (from-to) | 401-406 |
Number of pages | 6 |
Journal | Procedia CIRP |
Volume | 109 |
Early online date | 22 Jun 2022 |
DOIs | |
Publication status | Published - 31 Dec 2022 |
Event | 32nd CIRP Design Conference, CIRP Design 2022 - Gif-sur-Yvette, France Duration: 28 Mar 2022 → 30 Mar 2022 |
Bibliographical note
Funding Information:This research is funded by the Digital Engineering Technology & Innovation (DETI) partnership, UK.
Keywords
- analysis
- cognition
- comprehension
- Engineering design
- information design
- information-seeking
- patents
ASJC Scopus subject areas
- Control and Systems Engineering
- Industrial and Manufacturing Engineering