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Dataset / Data from: Toward Enhanced Reusability: A Comparative Analysis of Metadata for Machine …

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Title
Data from: Toward Enhanced Reusability: A Comparative Analysis of Metadata for Machine Learning Objects and Their Characteristics in Generalist and Specialist Repositories
Contributor
Baluja, Michael
Date Created and/or Issued
2021 to 2023
Contributing Institution
UC San Diego, Research Data Curation Program
Collection
Data from: Toward Enhanced Reusability: A Comparative Analysis of Metadata for Machine Learning Objects and Their Characteristics in Generalist and Specialist Repositories
Rights Information
Under copyright
Constraint(s) on Use: This work is protected by the U.S. Copyright Law (Title 17, U.S.C.). Use of this work beyond that allowed by "fair use" or any license applied to this work requires written permission of the copyright holder(s). Responsibility for obtaining permissions and any use and distribution of this work rests exclusively with the user and not the UC San Diego Library. Inquiries can be made to the UC San Diego Library program having custody of the work.
Use: This work is available from the UC San Diego Library. This digital copy of the work is intended to support research, teaching, and private study.
Rights Holder and Contact
UC Regents
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.
Librarians Association of the University of California (LAUC) 2020-2021; Research Data Curation Program, UC San Diego Library.
Research Data Curation Program, UC San Diego, La Jolla, 92093-0175 (https://lib.ucsd.edu/rdcp)
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
Type
dataset
Identifier
ark:/20775/bb4517297w
Language
English
Subject
Machine learning
Metadata crosswalk
Reusability
Data curation
Metadata schema
Data repository
Interoperability
Findability
FAIR Data Principles

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