Journal article
Semantics for Digital Engineering Archives Supporting Engineering Design Education
The AI magazine, v 31(1)
01 Mar 2010
Abstract
This article introduces the challenge of digital preservation in the area of engineering design and manufacturing and presents a methodology to apply knowledge representation and semantic techniques to develop digital engineering archives. This work is part of an ongoing, multiuniversity effort to create cyber infrastructure based engineering repositories for undergraduates (CIBER-U) to support engineering design education. The technical approach is to use knowledge representation techniques to create formal models of engineering data elements, work flows, and processes. With these techniques formal engineering knowledge and processes can be captured and preserved with some guarantee of long-term interpretability. The article presents examples of how the techniques can be used to encode specific engineering information packages and work flows. These techniques are being integrated into a semantic wiki that supports the CIBER-U engineering education activities across nine universities and involving more than 3500 students since 2006.
Metrics
Details
- Title
- Semantics for Digital Engineering Archives Supporting Engineering Design Education
- Creators
- William Regli - Drexel UniversityJoseph B. Kopena - Drexel UniversityMichael Grauer - Drexel UniversityTimothy Simpson - Pennsylvania State UniversityRobert Stone - Oregon State UniversityKemper Lewis - University at Buffalo, State University of New YorkMatt Bohm - Oregon State UniversityDavid Wilkie - Drexel UniversityMartin Piecyk - Drexel UniversityJordan Osecki - Drexel University
- Publication Details
- The AI magazine, v 31(1)
- Publisher
- Amer Assoc Artificial Intell
- Number of pages
- 14
- Grant note
- CISE/IIS-0456001; CISE/SCI-0537370; CISE/SCI-0537125 / National Science Foundation (NSF)
- Resource Type
- Journal article
- Language
- English
- Web of Science ID
- WOS:000276177700003
- Scopus ID
- 2-s2.0-79951875515
- Other Identifier
- 991019346720104721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence