Grants Database

The Foundation awards approximately 200 grants per year (excluding the Sloan Research Fellowships), totaling roughly $80 million dollars in annual commitments in support of research and education in science, technology, engineering, mathematics, and economics. This database contains grants for currently operating programs going back to 2008. For grants from prior years and for now-completed programs, see the annual reports section of this website.

Grants Database

Grantee
Amount
City
Year
  • grantee: McGill University
    amount: $382,020
    city: Montrйal, Canada, Canada
    year: 2021

    To improve the usability of large-userbase scientific open source software through early engagement of software users

    • Program Technology
    • Sub-program Better Software for Science
    • Investigator Jin Guo

    Most private sector software development is informed by user experience (UX) designers who work to ensure products provide meaningful and relevant experiences to users, but UX is treated as an afterthought, if considered at all, within open source scientific software. The result is that much open source scientific software with graphical user interfaces is counterintuitive and difficult to use, with predictable effects on adoption. This grant funds work by Jin Guo of McGill University and Jinghui Cheng of Polytechnique Montrйal to develop and test techniques and tools to facilitate better integration of design considerations into open source software development. An essential feature of successful UX design processes is understanding user needs and soliciting and evaluating their feedback iteratively. Facilitating such activities can be difficult, particularly on open source projects where the management team is stretched thin. Drawing on their familiarity with natural language processing and human-computer interaction, Guo and Cheng will attempt to streamline user participation in UX design through three streams of research. The first will be on tools that provide prompts, suggestions and frameworks to users to reduce vagueness and ambiguity in their design feedback, clearly demarcate problems from proposed solutions, and help ensure user comments are maximally useful to developers. The second will focus on tools that use natural language recognition to analyze, summarize, and synthesize user comments, allowing the development team to digest and prioritize feedback effectively and efficiently. The third will focus on tools that engage users in contributing pre-implementation design artifacts, like wireframes, sketches, and interface mockups.

    To improve the usability of large-userbase scientific open source software through early engagement of software users

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  • grantee: New York University
    amount: $520,503
    city: New York, NY
    year: 2021

    To develop a decentralized, federated framework for institutional archiving of research software and other open scholarly materials

    • Program Technology
    • Sub-program Better Software for Science
    • Investigator Victoria Rampin

    Research by Vicky Rampin, Librarian for Research Data Management and Reproducibility at NYU's Division of Libraries, revealed that while there is widespread use of version control among academic researchers writing source code, there are limited approaches to its preservation. In response, Rampin, together with Martin Klein at Los Alamos National Laboratory, has developed an ambitious plan for CoSAI, Collaborative Software Archiving for Institutions, a project that will create a decentralized and federated platform that will knit together several existing archiving and software preservation tools. Decentralization means that no one institution can be a bottleneck or failure point for archiving workflows—a thorny problem on other platforms—while federation both shares costs among partners and implements one of the gold standards in archiving: ensuring the robustness of preservation through having multiple copies of files mirrored across independent sites. CoSAI will focus on research software and aims to archive not just the code developed on sites like GitHub, but the (currently) ephemeral record of supplementary material related to the code (e.g., discussion threads, issues, etc.). By leveraging existing open source tools like Memento Tracer and building on workflow engines such as OCCAM, CoSAI will be able to capture web resources from code repositories at high quality and in a reproducible manner.

    To develop a decentralized, federated framework for institutional archiving of research software and other open scholarly materials

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  • grantee: Open Collective Foundation
    amount: $50,000
    city: Walnut, CA
    year: 2021

    To strengthen the public interest communities and networks that sustain open-source digital infrastructure

    • Program Technology
    • Sub-program Better Software for Science
    • Investigator Pia Mancini

    To strengthen the public interest communities and networks that sustain open-source digital infrastructure

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  • grantee: Carnegie Mellon University
    amount: $40,984
    city: Pittsburgh, PA
    year: 2021

    To conduct exploratory analyses on why maintainers disengage from open source projects by cataloguing disengagement factors and hypotheses based on demographic characteristics

    • Program Technology
    • Sub-program Better Software for Science
    • Investigator Christian Kдstner

    To conduct exploratory analyses on why maintainers disengage from open source projects by cataloguing disengagement factors and hypotheses based on demographic characteristics

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  • grantee: University of Colorado, Boulder
    amount: $574,444
    city: Boulder, CO
    year: 2021

    To build an inclusive and diverse community around standards for and the review of scientific Python open source software (OSS)

    • Program Technology
    • Sub-program Better Software for Science
    • Investigator Leah Wasser

    The review process for software is analogous to but in some ways different from a manuscript review; in addition to assessing the integrity of the methods manifested in the software’s algorithms, reviewers can consider features of the code itself and how well it is “bundled” for use by others. Does it run well under varying conditions? How interoperable is it with other platforms? What is the quality of its documentation? Such review is important for two main reasons. First, software that receives high marks by reputable reviewers lowers barriers to use.  Scientists can trust that well-reviewed code is robust, trustworthy, and easy to implement, even if they did not write the code themselves.  Second, well-regarded software reviews (and citations) can signal value and thus increase the incentives for software engineers and others to develop and maintain research software.  This grant funds a project by ecologist and data scientist Leah Wasser to further advance research software review in Python, arguably the dominant programming language for data science. pyOpenSci will mimic many of the core functions of the rOpenSci ecosystem including a grassroots process to develop common community standards, a transparent review process that leverages critical tooling from the Journal of Open Source Software, and efforts to build a strong, well-connected, diverse network of developers, engineers, and working scientists committed to the project.

    To build an inclusive and diverse community around standards for and the review of scientific Python open source software (OSS)

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  • grantee: Atlanta University Center Consortium
    amount: $249,994
    city: Atlanta, GA
    year: 2021

    To pilot postbaccalaureate training in open source software development for Black students and infuse open source skills into HBCU curricula

    • Program Technology
    • Sub-program Better Software for Science
    • Investigator Talitha Washington

    To pilot postbaccalaureate training in open source software development for Black students and infuse open source skills into HBCU curricula

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  • grantee: Community Initiatives
    amount: $248,729
    city: Oakland, CA
    year: 2021

    To build an inclusive and diverse instructor community around teaching foundational data literacy skills for conducting efficient, open, and reproducible research

    • Program Technology
    • Sub-program Better Software for Science
    • Investigator Kari Jordan

    To build an inclusive and diverse instructor community around teaching foundational data literacy skills for conducting efficient, open, and reproducible research

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  • grantee: Code for Science and Society
    amount: $86,000
    city: Portland, OR
    year: 2021

    To drive the definition and adoption of FAIR principles for research software

    • Program Technology
    • Sub-program Better Software for Science
    • Investigator Michelle Barker

    To drive the definition and adoption of FAIR principles for research software

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  • grantee: Code for Science and Society
    amount: $36,850
    city: Portland, OR
    year: 2021

    To advance understanding of the economics of open infrastructure maintenance and sustainability, by examining the themes of system interoperability, distributed governance, and collective funding

    • Program Technology
    • Sub-program Better Software for Science
    • Investigator Kaitlin Thaney

    To advance understanding of the economics of open infrastructure maintenance and sustainability, by examining the themes of system interoperability, distributed governance, and collective funding

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  • grantee: Open Collective Foundation
    amount: $605,000
    city: Walnut, CA
    year: 2020

    To support research and implementation projects on the maintenance of open source digital infrastructure

    • Program Technology
    • Sub-program Better Software for Science
    • Investigator Alyssa Wright

    To support research and implementation projects on the maintenance of open source digital infrastructure

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