SEAA 2026: Supplementary Artifact for MLOps Quality Assurance

SEAA 2026 Supplementary Artifact by Vladislav Indykov provides supporting material for a research framework on structured Quality Assurance in MLOps. The artifact includes a taxonomy of MLOps products evaluated on 79 open-source projects and a mapping of quality attributes based on 55 scholarly sources. It was last updated on June 4, 2026.

Use Cases

• Tailoring quality metrics to a specific MLOps implementation based on its structural features.
• Evaluating the quality attributes of data-related and model-related processes in ML systems.
• Designing a structured QA process for MLOps development and operational phases.
• Benchmarking open-source MLOps projects against a defined taxonomy of features.

Strengths

• Includes a taxonomy evaluated on 79 open-source projects.
• Provides a mapping of quality attributes based on 55 scholarly sources.
• Released under a permissive CC-BY-4.0 license.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

figshare

Collection Method

Research artifact accompanying a scholarly publication.

Freshness

Last updated 2026-06-04 11:35:53; freshness should be verified.