Qualimetry and CTMinfo: Ontological Foundations for Reproducible Quantitative Quality Assessment and System Efficiency
Qualimetry, as a scientific discipline introduced by Georgy Azgaldov, aims at the quantitative assessment of quality across objects of different nature. Despite its strong theoretical foundation, its practical implementation remains limited due to the absence of a unified and unambiguous description of objects. This work formulates the thesis that reproducible quantitative quality assessment cannot be achieved in the presence of ontological ambiguity. The paper identifies ontological determinacy as a necessary precondition for objectivity, comparability, and reproducibility of quality evaluation. The CTMinfo system is proposed as an ontological infrastructure that ensures unambiguous object identification, complete specification of characteristics, and elimination of semantic inconsistencies. Within this framework, qualimetry becomes practically applicable and reproducible. The study is conceptual in nature and focuses on defining the necessary conditions for the applicability of quantitative quality assessment. In addition, the paper highlights the systemic economic and environmental implications of ontological ambiguity, including global losses associated with poor data quality, inefficient procurement, and resource overconsumption. The results suggest that eliminating ontological ambiguity is not only a methodological requirement but also a systemic necessity for sustainable industrial and economic development.
Authors
- Dmitriy V. Andriyanov
Institutions
- Capgemini (Netherlands) (NL)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-04-01
- DOI
- https://doi.org/10.5281/zenodo.19371085
- Primary Topic
- Data Quality and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00