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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.

Research software plays a crucial role in advancing scientific knowledge, but ensuring its sustainability, maintainability, and long-term viability is an ongoing challenge. The Sustainable Research Software Institute (SRSI) Model has been designed to address the concerns, and presents a comprehensive framework designed to promote sustainable practices in the research software community. However the SRSI Model does not address the transitional requirements for the Exascale Computing Project (ECP) Software Technology (ECP-ST) focus area specifically. This white paper provides an overview and detailed description of how ECP-ST will transition into the SRSI in a compressed time frame that a) meets the needs of the ECP end-of-technical-activities deadline; and b) ensures the continuity of the sustainability efforts that are already underway., Comment: 7 pages, 1 figure

Research software plays a crucial role in advancing scientific knowledge, but ensuring its sustainability, maintainability, and long-term viability is an ongoing challenge. To address these concerns, the Sustainable Research Software Institute (SRSI) Model presents a comprehensive framework designed to promote sustainable practices in the research software community. This white paper provides an in-depth overview of the SRSI Model, outlining its objectives, services, funding mechanisms, collaborations, and the significant potential impact it could have on the research software community. It explores the wide range of services offered, diverse funding sources, extensive collaboration opportunities, and the transformative influence of the SRSI Model on the research software landscape, Comment: 13 pages, 1 figure

In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. The study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and ii) data management requirements for data-driven science using artificial intelligence., Comment: 14 pages, no figures, only tables