Data Quality Evaluation Tool
- Project
- 20219 IML4E
- Type
- New library
- Description
The Data Quality Evaluation Tool is a comprehensive solution for evaluating the quality of data. It measures data quality based on the stringent quality measurements specified in ISO 25012/ 25024 and the latest ML-specific metrics from emerging standards.
- Contact
- Jürgen Großmann, Fraunhofer FOKUS
- juergen.grossmann@fokus.fraunhofer.de
- Research area(s)
- ML quality assessment.
- Technical features
The tool supports both image and tabular data with minimal configuration required for setup. It performs comprehensive quality checks that include essential attributes like syntactic and semantic accuracy, compliance, data completeness, and duplicate detection, among others. The assessments generate detailed logs, enabling users to trace quality issues back to specific files or records. Additionally, images with detected errors can be visualized for easier analysis and correction.
- Integration constraints
Windows/UNIX-based OS with Python (3.10.8)
- Targeted customer(s)
Companies developing machine learning solutions.
MLOps practioners.- Conditions for reuse
License information on request.
- Confidentiality
- Public
- Publication date
- 01-02-2023
- Involved partners
- Fraunhofer (DEU)
