| Title: | Data and data quality in mathematics |
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| Authors: | ID Berčič, Katja (Author) |
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| Files: |  PDF - Presentation file, download (831,18 KB)
MD5: 46FC382BB40F4C87A672D46B749B0A5C
 URL - Source URL, visit https://www.intechopen.com/chapters/1232506
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| Language: | English |
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| Typology: | 1.16 - Independent Scientific Component Part or a Chapter in a Monograph |
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| Organization: |  IMFM - Institute of Mathematics, Physics, and Mechanics
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| Abstract: | 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. |
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| Keywords: | mathematical knowledge management, digital mathematics libraries and repositories, computer-assisted mathematics, implementation challenges, data quality dimensions, mathematical data |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Year of publishing: | 2026 |
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| Number of pages: | 22 str. |
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| PID: | 20.500.12556/DiRROS-29285  |
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| UDC: | 004.6:51 |
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| DOI: | 10.5772/intechopen.1013831 |
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| COBISS.SI-ID: | 277107715 |
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| Note: | Nasl. z nasl. zaslona;
Opis vira z dne 5. 5. 2026;
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| Publication date in DiRROS: | 06.05.2026 |
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| Views: | 129 |
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| Downloads: | 122 |
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