Software is increasingly central to scientific research, but academia often fails to leverage best practices for software engineering from industry or elsewhere. To realize the full potential of software in advancing discovery—whether in data science, computational modeling, or machine learning—this program aims to adapt and extend approaches from other contexts into academic software development while recognizing the unique workflows and incentives of the research enterprise. Rather than funding individual scientific software development projects, grants in this area focus mainly on tooling, institutions, economic models, and incentives around the production, maintenance, and adoption of research software.
Open source in research
Open source is much more than a licensing strategy, it is a set of community practices that enable the distributed production and maintenance of software that are not widely adopted in the research enterprise. The Better Software for Science program seeks opportunities to better understand and align best practices in open source with academic research, with a particular eye toward the health and maintenance of digital infrastructural dependencies upon which computational research relies.
Software Publication and Archiving
Software is not well-integrated into the scholarly communication system; scientific software is often not cited or well-archived, and can require substantial work to reuse. The Better Software for Science program seeks opportunities to elevate software as a first-order research product as well as efforts that aim to improve the linkages between software and other research outputs such as articles, preprints or data.
Career paths and incentives
The work of building and maintaining research software is often undervalued and marginalized in the research enterprise. The Better Software for Science program seeks opportunities to foreground and institutionalize the individuals and communities who are essential to the utility and durability of software in science, with particular attention to the roles of research software engineer, data scientist, and software curator.
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