Discovering taxonomic structure in design archives with application to risk-mitigating actions in a large engineering organisation
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© 2016 Taylor & Francis. This paper demonstrates a general iterative technique for discovering a taxonomy that categorises information contained within a weakly structured design project archive. It is common for large engineering organisations to maintain archives about past design projects. In principle, engineering organisations could mine these archives to extract useful lessons and relationships that would improve future design projects. However, this is difficult in practice, since archives often consist of weakly structured data formats, such as plaintext documentation. This restricts the use of many useful analysis tools. The taxonomy-discovery process presented here is a critical first step towards unlocking the value of such archives. The technique is based on methods from the qualitative research literature. We demonstrate this process by creating a taxonomy of risk-mitigating actions in design projects based on a design project archive from a large engineering organisation. We discuss practical considerations such as missing contextual information as part of the case study. The taxonomy is sufficiently generic to be of use to other organisations. Furthermore, individual organisations can use the iterative technique introduced in this paper to tailor the taxonomy to their own project archives. Thus, this research provides an important foundation for unlocking the value of archived design project information.
author list (cited authors)
Hsiao, C., Ruffino, M., Malak, R., Tumer, I. Y., & Doolen, T.