Key points are not available for this paper at this time.
The complexity of construction projects and the multiplicity of stakeholders, organizations, and standards involved call for a unified and common language to support linked data and allow for semantic inference among multiple projects, processes, and actors. While several taxonomies are developed for knowledge management in construction, most of them either have remained at a high level of information exchange or are focused on adapting project data with standards in a specific domain and have served a very narrow and particular range of queries. Although taxonomies that are established at such levels create a broad and general framework for organizing knowledge, they will not enable "cross-analyses" because of incomplete coverage of a particular domain. Hence, this paper proposes a user-level taxonomy, focusing on critical administrative processes in construction projects, that is, change order management. Text mining was applied to extract key concepts from the data of past projects focusing on two main facets, namely, processes and actors. Taxonomy has been developed to serve as the foundation of a new ontology that aims to enable organizations to perform cross-facet and cross-phase semantic queries in large construction databases.
Baboldashti et al. (Mon,) studied this question.