# ECS -- an Interactive Tool for Data Quality Assurance

arXiv: https://arxiv.org/abs/2307.04368 · HTML: https://mlsanity.com/paper/2307.04368/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 28 references that are in the map.
- First posted on arXiv 10 Jul 2023.

## Builds on (most cited first, 3 of 3)

- [UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction](https://mlsanity.com/paper/1802.03426/) (2018)
- [Data Quality Certification using ISO/IEC 25012: Industrial Experiences](https://mlsanity.com/paper/2102.11527/) (2021)
- [QI2 -- an Interactive Tool for Data Quality Assurance](https://mlsanity.com/paper/2307.03419/) (2023)

## Abstract (arXiv)

With the increasing capabilities of machine learning systems and their potential use in safety-critical systems, ensuring high-quality data is becoming increasingly important. In this paper we present a novel approach for the assurance of data quality. For this purpose, the mathematical basics are first discussed and the approach is presented using multiple examples. This results in the detection of data points with potentially harmful properties for the use in safety-critical systems.