Cross-Industry Performance Modeling: Toward Cooperative Analysis
One of the current unsolved problems in human factors is the difficulty in acquiring information from lessons learned and data collected among human performance analysts in different domains. There are several common concerns and generally accepted issues of importance for human factors, psychology and industry analysts of performance and safety. Among these are the need to incorporate lessons learned in design, to carefully consider implementation of new designs and automation, and the need to reduce human performance-based contributions to risk. In spite of shared concerns, there are several road blocks to widespread sharing of data and lessons learned from operating experience and simulation, including the fact that very few publicly accessible data bases exist(Gertman & Blackman, 1994, and Kirwan, 1997). There is a need to draw together analysts and analytic methodologies to comprise a centralized source of data with sufficient detail to be meaningful while ensuring source anonymity. We propose that a generic source of performance data and a multi-domain data store may provide the first steps toward cooperative performance modeling and analysis across industries.
- Research Organization:
- Idaho National Lab. (INL), Idaho Falls, ID (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC07-94ID13223
- OSTI ID:
- 8923
- Report Number(s):
- INEEL/CON-98-01014; ON: DE00008923
- Resource Relation:
- Conference: Human Factors and Ergonomic Society Annual Meeting, Chicago, IL, 10/05/98 - 10/09/98
- Country of Publication:
- United States
- Language:
- English
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