1 citations · 1 across the 5 of their papers we have counts for
5 papers
SetGo: Metadata Readiness for Scientific AI Datasets
Sean R. Wilkinson, Polina Shpilker, Wesley Brewer
Scientific datasets intended for AI use require both computational readiness for model training and metadata readiness for discovery, sharing, and reuse. The Readiness Engine for D…
Automated Data Readiness for Scientific AI
Sean R. Wilkinson, Valentine G. Anantharaj, Jong Youl Choi +8
Leadership computing facilities steward large-scale scientific datasets that routinely require substantial transformation before serving as AI training data. However, no existing f…
MEDFORD in a Box: Improvements and Future Directions for a Metadata Description Language
Polina Shpilker, Benjamin Stubbs, Michael Sayers +6
Scientific research metadata is vital to ensure the validity, reusability, and cost-effectiveness of research efforts. The MEDFORD metadata language was previously introduced to si…
Automatic Metadata Capture and Processing for High-Performance Workflows
Polina Shpilker, Line Pouchard
Modern workflows run on increasingly heterogeneous computing architectures and with this heterogeneity comes additional complexity. We aim to apply the FAIR principles for research…
MEDFORD: A human and machine readable metadata markup language
Polina Shpilker, John Freeman, Hailey McKelvie +7
Reproducibility of research is essential for science. However, in the way modern computational biology research is done, it is easy to lose track of small, but extremely critical,…