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About this collection

Extent

1 digital object.

Cite This Work

Labou, Stephanie; Pennington, Abigail; Yoo, Ho Jung S.; Baluja, Michael (2024). Data from: Toward Enhanced Reusability: A Comparative Analysis of Metadata for Machine Learning Objects and Their Characteristics in Generalist and Specialist Repositories. UC San Diego Library Digital Collections. https://doi.org/10.6075/J0JS9QMH

Description

This dataset contains data reported in the paper, Labou et al. 2024, which aims to understand how researchers are currently documenting ML research outputs for sharing, and the extent to which repository metadata fields enable reuse of ML objects. Contents of the dataset include: Supplemental Tables referenced in the paper, a snapshot of the code used to query or web scrape data repositories for ML objects, metadata extracts from the repositories, and a snapshot of the code used to analyze the extracts.

Creation Date

• 2021 to 2023

Date Issued

• 2024

Authors

• Labou, Stephanie G.
• Pennington, Abigail
• Yoo, Ho Jung S.

Programmer

• Baluja, Michael

Funding

Librarians Association of the University of California (LAUC) 2020-2021; Research Data Curation Program, UC San Diego Library.

Topics

• Data curation
• Data repository
• FAIR Data Principles
• Findability
• Interoperability
• Machine learning
• Metadata crosswalk
• Metadata schema
• Reusability

Formats

View formats within this collection

• data
• software
• text

Language

• English

Identifier

Identifier: Abigail Pennington: https://orcid.org/0000-0002-9364-1995

Identifier: Ho Jung S. Yoo: https://orcid.org/0000-0001-9677-0947

Identifier: Stephanie Labou: https://orcid.org/0000-0001-5633-5983

Related Resources

Primary associated publication

• Labou, Stephanie G., Abigail Pennington, Ho Jung S. Yoo, and Michael Baluja. 2024. "Toward Enhanced Reusability: A Comparative Analysis of Metadata for Machine Learning Objects and Their Characteristics in Generalist and Specialist Repositories." Journal of eScience Librarianship 13 (2): e685. https://doi.org/10.7191/jeslib.685

Source data

• Dryad (datadryad.org/stash)
• Figshare (figshare.com)
• Harvard Dataverse (dataverse.harvard.edu)
• Kaggle (kaggle.com/datasets)
• OpenML (openml.org)
• SPDX License List (spdx.org/licenses)
• UC San Diego Library Digital Collections (library.ucsd.edu/dc)
• UCI Machine Learning Repository (archive.ics.uci.edu)
• Zenodo (zenodo.org)

Other version

• Code for Metadata Extracts and Data Analysis (GitHub Repository): http://github.com/stephlabou/comparative-machine-learning-metadata
• PyCurator GitHub Repository: https://github.com/michaelbaluja/PyCurator

Collection image

• Image credit: DALL-E, version 2, Open AI, Mar. 2023. "Machine learning metadata" (prompt).