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.

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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
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article

Qualimetry and CTMinfo: Ontological Foundations for Reproducible Quantitative Quality Assessment and System Efficiency

Dmitriy V. Andriyanov
Zenodo (CERN European Organization for Nuclear Research)
Data Quality and Management
article

Qualimetry and CTMinfo: Ontological Foundations for Reproducible Quantitative Quality Assessment and System Efficiency

Dmitriy V. Andriyanov
article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Capgemini (Netherlands) (NL)
Industry, innovation and infrastructure
Openalex Percentile: Top 27%
Data Quality and Management
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