Affiliation:
1. Purdue University West Lafayette IN USA 47907
Abstract
AbstractThe INCOSE Fellows have been leading an effort to develop heuristics that will help systems engineers pass on their knowledge of the best practices within the discipline.We performed bibliometric analysis on the text corpus of 164 heuristics and of the sources cited in them to gain insights into what the heuristics data is telling us about the discipline of systems engineering.We performed co‐occurrence analysis using VOSviewer, which is a software application that identifies pairs of terms and connects them. This analysis found terms that occur together across multiple heuristics by applying a natural language processing algorithm that identified the terms and formed clusters of terms that are strongly related to each other. To gain further insight into the cooccurrence results, the INCOSE Fellows participated in a contest to name the clusters and create narratives that provide a rationale for the cluster names and why it makes sense for the terms to belong to the clusters they were assigned to. Finally, a ballot was created to send out to a broader collection of INCOSE members to vote on the best name for each cluster among the names provided by the Fellows. The three‐step process of bibliometric analysis, cluster naming by the Fellows, and voting by the members identified emergent disciplines essential to the practice of systems engineering.We also performed bibliographic coupling analysis and co‐citation analysis using VOSviewer. A bibliographic coupling link is a link between two heuristics that both cite the same source. A co‐citation link is a link between two sources that are both cited by the same heuristic. The coupling analysis identified clusters among the heuristics that revealed communities of practice within systems engineering, and the co‐citation analysis identified clusters among the cited references to reveal communities of theory in systems engineering.