Data Smells: Categories, Causes and Consequences, and Detection of Suspicious Data in AI-based SystemsResearch Paper
High data quality is fundamental for today’s AI-based systems. However, although data quality has been an object of research for decades, there is a clear lack of research on potential data quality issues (e.g., ambiguous, extraneous values). These kinds of issues are latent in nature and thus often not obvious. Nevertheless, they can be associated with an increased risk of future problems in AI-based systems (e.g., technical debt, data-induced faults). As a counterpart to code smells in software engineering, we refer to such issues as Data Smells. This article conceptualizes data smells and elaborates on their causes, consequences, detection, and use in the context of AI-based systems. In addition, a catalogue of 36 data smells divided into three categories (i.e., Believability Smells, Understandability Smells, Consistency Smells) is presented. Moreover, the article outlines tool support for detecting data smells and presents the result of an initial smell detection on more than 240 real-world datasets.
Tue 17 MayDisplayed time zone: Eastern Time (US & Canada) change
09:30 - 11:00 | AI SmellsCAIN 2022 at CAIN main room Chair(s): Ipek Ozkaya Carnegie Mellon Software Engineering Institute, Thomas Zimmermann Microsoft Research | ||
09:30 30mOther | Activity: Brainwriting CAIN 2022 | ||
10:00 15mResearch paper | Code Smells for Machine Learning ApplicationsResearch Paper CAIN 2022 Haiyin Zhang AI for Fintech Research, ING, Luís Cruz Deflt University of Technology, Arie van Deursen Delft University of Technology, Netherlands Pre-print | ||
10:15 15mResearch paper | Data Smells: Categories, Causes and Consequences, and Detection of Suspicious Data in AI-based SystemsResearch Paper CAIN 2022 Harald Foidl University of Innsbruck, Michael Felderer University of Innsbruck, Rudolf Ramler Software Competence Center Hagenberg Pre-print | ||
10:30 15mResearch paper | Data smells in Public DatasetsResearch Paper CAIN 2022 Arumoy Shome Delft University of Technology, Luís Cruz Deflt University of Technology, Arie van Deursen Delft University of Technology, Netherlands Pre-print | ||
10:45 15mOther | Discussion on Smells in AI CAIN 2022 |