Ensure Documentation and Publishing new

Overview

Sustainability Dimension	Governance
ML Development Phase	Deployment and Monitoring
ML Development Stakeholders	Business Stakeholder, ML Development, Software Development, Auditing & Testing

Description

The DP “Ensure Documentation and Publishing” helps organizations to scale their ML efforts by documentation, publishing, versioning, and metadata management of ML artifacts (e.g., code, training data) (Visengeriyeva et al., 2023). Besides development documentation, it is important to aggregate model characteristics using toolkits such as datasheets, model cards, and model registries (Mitchell et al., 2019). Hence, it is essential to maintain documentation throughout the entire ML development process to ensure reproducibility and usability.

Sources

• Visengeriyeva, L., Kammer, A., Bär, I., Knish, A., & Plöd, M. (2023). MLOps and Model Governance. https://ml-ops.org/content/model-governance
• Mitchell, M., Wu, S., Zaldivar, A., Barnes, P., Vasserman, L., Hutchinson, B., Spitzer, E., Raji, I. D., & Gebru, T. (2019). Model Cards for Model Reporting. Proceedings of the Conference on Fairness, Accountability, and Transparency, 220–229. https://doi.org/10.1145/3287560.3287596