The proliferation of open source software (OSS) and different types of reuse has made it incredibly difficult to perform an essential legal and compliance task of accurate license identification within the software supply chain. This study presents a reusable and comprehensive dataset of OSS licenses, created using the World of Code (WoC) infrastructure. By scanning all files containing “license” in their file paths, and applying the approximate matching via winnowing algorithm to identify the most similar license from the SPDX and Open Source list, we found and identified 5.5 million distinct license blobs in OSS projects. The dataset includes a detailed project-to-license (P2L) map with commit timestamps, enabling dynamic analysis of license adoption and changes over time. To verify the accuracy of the dataset we use stratified sampling and manual review, achieving a final accuracy of 92.08%, with precision of 87.14%, recall of 95.45%, and an F1 score of 91.11%. This dataset is intended to support a range of research and practical tasks, including the detection of license noncompliance, the investigations of license changes, study of licensing trends, and the development of compliance tools. The dataset is open, providing a valuable resource for developers, researchers, and legal professionals in the OSS community.

In Open Source Software, the source code and any other resources available in a project can be viewed or reused by anyone subject to often permissive licensing restrictions. In contrast to some studies of dependency-based reuse supported via package managers, no studies of OSS-wide copy-based reuse exist. This dataset seeks to encourage the studies of OSS-wide copy-based reuse by providing copying activity data that captures whole-file reuse in nearly all OSS. To accomplish that, we develop approaches to detect copy-based reuse by developing an efficient algorithm that exploits World of Code infrastructure: a curated and cross referenced collection of nearly all open source repositories. We expect this data will enable future research and tool development that support such reuse and minimize associated risks.

The Open-Source Software community has become the center of attention for many researchers, who are investigating various aspects of collaboration in this extremely large ecosystem. Due to its size, it is difficult to grasp whether or not it has structure, and if so, what it may be. Our hackathon project aims to facilitate the understanding of the developer collaboration structure and relationships among projects based on the bi-graph of what projects developers contribute to by providing an interactive collaboration graph of this ecosystem, using the data obtained from World of Code [1] infrastructure. Our attempts to visualize the entirety of projects and developers were stymied by the inability of the layout and visualization tools to process the exceedingly large scale of the full graph. We used WoC to filter the nodes (developers and projects) and edges (developer contributions to a project) to reduce the scale of the graph that made it amenable to an interactive visualization and published the resulting visualizations. We plan to apply hierarchical approaches to be able to incorporate the entire data in the interactive visualizations and also to evaluate the utility of such visualizations for several tasks.