Thereby, traditional quality management systems face immense integration and interpretation difficulties concerning diverse and conflicting data sets that will more likely result in inefficiencies and
Research gap analysis derived from 3 engineering papers in our local library.
The gap
Thereby, traditional quality management systems face immense integration and interpretation difficulties concerning diverse and conflicting data sets that will more likely result in inefficiencies and a heightened risk of errors.
Consensus across the literature
Clustered from 3 gap mentions across 3 papers via embedding cosine ≥ 0.62.
Research trend
Established — well-defined area with open sub-problems.
Supporting evidence — 3 representative gaps
- Advancing Construction Quality Management: An Integrated Evidential Reasoning and Belief Functions Framework (2025) · doi
Thereby, traditional quality management systems face immense integration and interpretation difficulties concerning diverse and conflicting data sets that will more likely result in inefficiencies and a heightened risk of errors.
Keywords: thereby traditional quality management systems face immense integration interpretation difficulties concerning diverse conflicting sets likely - Challenges in ensuring metadata quality in institutional academic repositories: a qualitative study in Turkish research universities (2025) · doi
Other key challenges include software issues, lack of audit and control mechanisms, negative user attitudes, insufficient staff, limited knowledge and awareness of data management processes, absence of national-level standards and inadequate formal workflow procedures and metadata policies.
Keywords: challenges include software issues lack audit control mechanisms negative user attitudes insufficient staff limited knowledge - Advancing Clash Resolution In Digital Construction Models: A Practice-Oriented Analytical Perspective (2026) · doi
22, Issue 2, 903-923 inconsistent data standards; insufficient skills and low levels of BIM maturity; schedule compression coupled with rising project complexity; inappropriate or inconsistent application of Level of Detail; organizational and cultural resistance; and the limited advancement of automation, largely attributable to inadequate and poor-quality datasets.
Keywords: inconsistent issue standards insufficient skills levels maturity schedule compression coupled rising project complexity inappropriate application
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