SciCat: A Curated Dataset of Scientific Software Repositories
CoRR(2023)
摘要
The proliferation of open-source scientific software for science and research
presents opportunities and challenges. In this paper, we introduce the SciCat
dataset -- a comprehensive collection of Free-Libre Open Source Software
(FLOSS) projects, designed to address the need for a curated repository of
scientific and research software. This collection is crucial for understanding
the creation of scientific software and aiding in its development. To ensure
extensive coverage, our approach involves selecting projects from a pool of 131
million deforked repositories from the World of Code data source. Subsequently,
we analyze README.md files using OpenAI's advanced language models. Our
classification focuses on software designed for scientific purposes,
research-related projects, and research support software. The SciCat dataset
aims to become an invaluable tool for researching science-related software,
shedding light on emerging trends, prevalent practices, and challenges in the
field of scientific software development. Furthermore, it includes data that
can be linked to the World of Code, GitHub, and other platforms, providing a
solid foundation for conducting comparative studies between scientific and
non-scientific software.
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