QI²: an interactive tool for data quality assurance
- The importance of high data quality is increasing with the growing impact and distribution of ML systems and big data. Also, the planned AI Act from the European commission defines challenging legal requirements for data quality especially for the market introduction of safety relevant ML systems. In this paper, we introduce a novel approach that supports the data quality assurance process of multiple data quality aspects. This approach enables the verification of quantitative data quality requirements. The concept and benefits are introduced and explained on small example data sets. How the method is applied is demonstrated on the well-known MNIST data set based an handwritten digits.
Author: | Simon GeerkensORCiD, Christian SieberichsORCiD, Alexander BraunORCiD, Thomas Waschulzik |
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open access (DINI-Set): | open_access |
Qualitätssicherung: | peer reviewed |
open access : | Hybrid - Subskriptionszeitschrift |
agreement: | DEAL Springer Nature |
Fachbereich/Einrichtung: | Hochschule Düsseldorf / Fachbereich - Elektro- & Informationstechnik |
Document Type: | Article |
Year of Completion: | 2024 |
Language of Publication: | English |
Publisher: | Springer Nature |
Parent Title (English): | AI and Ethics |
Volume: | 4 |
First Page: | 141 |
Last Page: | 149 |
URN: | urn:nbn:de:hbz:due62-opus-42945 |
DOI: | https://doi.org/10.1007/s43681-023-00390-6 |
ISSN: | 2730-5961 |
Tag: | DEAL; DFG Publikationskosten; HSD Publikationsfonds Data integrity; Data quality; Machine learning; Performance metrics; Quality assurance |
Funding institution: | DFG / zentraler HSD-Publikationsfonds |
Corresponding Author: | Simon Geerkens |
Dewey Decimal Classification: | 6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften / 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten |
Licence (German): | Creative Commons - CC BY - Namensnennung 4.0 International |
Release Date: | 2024/01/15 |
Note: | Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 532148125 and supported by the central publication fund of Hochschule Düsseldorf University of Applied Sciences Data availability declaration: The data that support the findings of this scientific publication are available from the corresponding author upon reasonable request. |