Model Cards and Data Sheets Three Years On: An Audit of Documentation Completeness in Public Repositories

Authors

  • Stijn Vandromme Centre for Responsible AI, Herve Centre for Machine Intelligence, Verviers, Belgium Author
  • Martine Muller-Bech Centre for Responsible AI, Sure Valley Centre for Machine Intelligence, Ettelbruck, Luxembourg Author
  • Asdis Palsdottir-Sig Department of Software Engineering, Snaefellsnes Institute of Applied Artificial Intelligence, Stykkisholmur, Iceland Author

DOI:

https://doi.org/10.5281/zenodo.22660543

Keywords:

Model Cards and Data Sheets Three Years On; Applied machine learning; Evidence synthesis; Production deployment; MLOps

Abstract

Model Cards and Data Sheets Three Years On is an area of active development in applied machine learning, with evidence that
has accumulated unevenly across its component questions. We review the current evidence base for model cards and data sheets
three years on, spanning methodological, implementation, governance, and cost dimensions, focusing on where practice has
converged and where it continues to vary, and set out the practical considerations relevant to a team considering its adoption. We
conclude that selective, context-specific use is best supported by the evidence currently available, rather than uniform adoption or
avoidance.

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Grabowski P, Petrescu G, et al. "Model Cards and Data Sheets Three Years On: a case study". IEEE Trans Knowl Data Eng 40(2014): 476-482. DOI: 10.3389/fdgth.2026.1896184

Hendriksen W, Wojcik H, et al. "Model Cards and Data Sheets Three Years On: a survey". J Artif Intell Res 42(2017): 487-494. DOI: 10.3390/diagnostics15162117

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Jankowiak G, Grabowski J, et al. "Model Cards and Data Sheets Three Years On: a field deployment report". Neural Comput Appl 46(2023): 509-518. DOI: 10.3389/fdgth.2026.1763884

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Published

2023-08-30

Issue

Vol. 2 No. 2 (2023): Vol 2 Issue 2 2023

Section

Articles

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