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Objective information theory: A Sextuple model and 9 kinds of metrics
Abstract
In the contemporary era, the importance of information is undisputed, but there has never been a common understanding of information, nor a unanimous conclusion to the researches on information metrics. Based on the previous studies, this paper analyzes the important achievements in the researches of the properties and metrics of information as well as their main insufficiencies, and discusses the essence and connotation, the mathematical expressions and other basic problems related to information. On the basis of the understanding of the objectivity of information, it proposes the definitions and a Sextuple model of objective information; discusses the basic properties of information, and brings forward the definitions and mathematical expressions of nine kinds of metrics of information, i.e., extensity, detailedness, sustainability, richness, containability, delay, distribution, validity and matchability. Through these, this paper establishes a basic theory frame of Objective Information Theory to support the analysis and research on information and information system systematically and comprehensively.
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“Studies of Ukrainian e-government show that staff skills, process design, and management practices are decisive for ensuring high-quality information in government [29].”
From Data Quality in the Age of AI: A Review of Governance, Ethics, and the FAIR Principles (2025) · cites this paper as [29]
In the citing paper
“Shortcomings such as insufficient training, weak governance, and organizational inefficiencies limit outcomes, underscoring that data quality challenges in government are rooted as much in people and structures as in systems [29].”
From Data Quality in the Age of AI: A Review of Governance, Ethics, and the FAIR Principles (2025) · cites this paper as [29]
In the citing paper
“Public administration research confirms that technology alone does not ensure high-quality information.”
From Data Quality in the Age of AI: A Review of Governance, Ethics, and the FAIR Principles (2025) · cites this paper as [29]
In the citing paper
“The organizational dimension of information quality in public administration is underexplored, as governance structures, staff skills, and administrative processes strongly influence reliability, but are mainly insufficiently studied [29].”
From Data Quality in the Age of AI: A Review of Governance, Ethics, and the FAIR Principles (2025) · cites this paper as [29]
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Cited by
Sorted by citations
Data Quality in the Age of AI: A Review of Governance, Ethics, and the FAIR Principles
Guillen-Aguinaga, M., Aguinaga-Ontoso, E., Guillen-Aguinaga, L., Guillen-Grima, F., & Aguinaga-Ontoso, I. (2025) · Data · doi:10.3390/data10120201 · Cited by 37
Metadata
- Authors
- Xu, J., Ma, X., Shen, Y., Tang, J., Xu, B., & Qiao, Y.
- Affiliations
- China Academy of Electronics and Information Technology (CN)
- Tsinghua University (CN)
- Venue
- 2014 Science and Information Conference
- Publisher
- IEEE
- Published
- 2014-08
- Pages
- 793-802
- OpenAlex
- W2964324413
- Cited by
- 8
- References
- 0
- Citations by year
- 2025: 2 · 2023: 1 · 2021: 1 · 2020: 2 · 2016: 2
- FWCI
- 0.57
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Science and Information Conference (publishedVersion)
- Funders
- RAND Corporation
- Topics
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Scientific Research and Philosophical Inquiry
- Physical Sciences › Computer Science › Artificial Intelligence › Diverse Interdisciplinary Research Studies
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Systems and Dynamics
- Keywords
- information metrics, information sustainability, information richness, information delay, information distribution, information validity, information characteristics, information systems
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