Analysis of INCOSE Systems Engineering journal and international symposium research topics

Abstract

The pressure on systems engineering is ever‐increasing to support the development and implementation of systems that meet a complex environment's demands. As a growing discipline, systems engineering requires insight into past research to identify opportunities for future growth. Analyzing the bibliometric data on published research provides valuable information on a scientific discipline's past progress and future prospects. Therefore, this paper extracts the research topics published in INCOSE's journal Systems Engineering and the annual international symposium proceedings to analyze their composition and allocation to papers. The implemented process applies natural language processing and topic modeling to extract the main topics from these papers' titles and abstracts. Analyzing these research topics' composition and mapping them to processed articles helps to understand their relative importance. The analysis's output confirms the importance of modeling in systems engineering, as it is the most popular topic. The additional focus of research papers on the systems engineering process, practice, and methodologies also indicates that the field is still growing and evolving. Some important topics to systems engineering, which were not found as prominent topics, are humans' roles in systems, verification and validation, and other specialty fields. This new knowledge about the structure of research into systems engineering can identify future research project opportunities to continue growing the field.

Study of Equivalence in Systems Engineering Within the Frame of Verification

“…Overall, the literature review was consistent with a recent survey of INCOSE sponsored publications, which found a lack of research on verification [43]. Additionally, the literature suggests that a common belief exists that verification models only need to represent the system design "as far as required for test purposes" and representativeness largely remains a qualitative definition (e.g., high-, medium-, low-) [42].…”

“…The literature suggests that (i) increased mathematical rigor is desired for SE (e.g., [18,29]), (ii) verification is known to be in need of theoretical foundations [9], (iii) verification research in SE literature has been found to be minimal [43], (iv) verification requirements are typically expressed in textual form rather than mathematical or model-based form (e.g., [42]), (v) representativeness of verification models to system design is largely limited to a heuristic-basis and documented in qualitative terms (e.g., [42]), (vi) relationship-based definition of verification models is unexplored research territory, and (vii) limited explicit use of morphisms exists in the SE literature.…”