Data and data quality in mathematics

Berčič, Katja (author)

Pure mathematics is often viewed, even by its practitioners, as a discipline in which data play little or no role. Data, when acknowledged at all, are often seen as a byproduct of research rather than a research product in their own right. Yet databases and datasets are increasingly central to the way mathematicians formulate conjectures, test hypotheses, and explore complex structures. Unlike empirical data, data in mathematics often consist of exact values derived from symbolic definitions or computations and commonly describe highly structured objects such as graphs, elliptic curves, or manifolds. This combination of abstraction, precision, and low redundancy poses distinctive challenges for data quality, shifting the focus away from concerns like noise and bias toward correctness, completeness, consistency, and accessibility.

• Language: English
• Keywords: mathematical knowledge management, digital mathematics libraries and repositories, computer-assisted mathematics, implementation challenges, data quality dimensions, mathematical data
• Work type: Other
• Typology: 1.16 - Independent Scientific Component Part or a Chapter in a Monograph
• Organization: FMF - Faculty of Mathematics and Physics
• Publication status: Published
• Publication version: Version of Record
• Year: 2026
• Number of pages: 22 str.
• PID: 20.500.12556/RUL-182282
• UDC: 004.6:51
• DOI: 10.5772/intechopen.1013831
• COBISS.SI-ID: 277107715
• Publication date in RUL: 06.05.2026

Record is a part of a monograph

• Title: Data quality matters : best practices for integrity and assurance
• Editors: Sebastian Ventura, José M. Luna, Antonio R. Moya Martín-Castaño
• Place of publishing: London
• Publisher: IntechOpen
• Year: 2026
• ISBN: 978-1-83634-985-3
• COBISS.SI-ID: 277104899

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Keywords: obdelava podatkov, podatki v matematiki, kvaliteta podatkov

Projects

• Funder: Other - Other funder or multiple funders
• Project number: FA9550-21-1-0024
• Name: /

• Funder: ARIS - Slovenian Research and Innovation Agency
• Project number: P1-0294
• Name: Računsko intenzivne metode v teoretičnem računalništvu, diskretni matematiki, kombinatorični optimizaciji ter numerični analizi in algebri z uporabo v naravoslovju in družboslovju