Mentions

This page describes how alternative mentions of datasets are identified for dataset in the Scholar Data database. Unlike formal citations, alternative mentions capture dataset reuse in contexts where standard citation practices are less common or not established, such as code repositories, machine learning models, and patents.

Sources

Software Heritage

The Software Heritage archive is the world's largest public collection of source code, preserving over 250 million projects from platforms like GitHub and GitLab. Scholar Data scans README files from GitHub repositories for dataset identifier mentions, capturing reuse in computational pipelines, models, and similar software outputs.

Hugging Face

The Hugging Face Hub is the central platform for sharing pre-trained machine learning models. Scholar Data scans model cards for dataset identifier mentions, capturing reuse in open-source ML workflows.

USPTO Patents

Scholar Data scans granted patents from the United States Patent and Trademark Office (USPTO) for dataset identifier mentions, covering patents from January 2002 onward.

Coverage

Scholar Data currently tracks over 90,000 mentions to datasets indexed in the Scholar Data databases.

Source	Last Updated/Version used	Mentions
Software Heritage	January 2026	85,129
Hugging Face	January 2026	5,243
USPTO Patents	January 2026	1,519
Total		91,891

A Note on Mention Counting

Mentions are identified by scanning source content for dataset identifiers. All mentions are counted broadly. Scholar Data does not apply additional filtering to verify whether a dataset was actively used in the associated work, as opposed to simply referenced. Given the overall scarcity of dataset mentions, counting all signals is considered the right approach at the moment to incentivize and reward data sharing.

Why Might a Mention Be Missing?

• The code repository, model card, or patent was published after the last database update
• The mention appears in a platform not yet covered by the sources listed above