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: University of North Carolina, Chapel Hill
    amount: $501,416
    city: Chapel Hill, NC
    year: 2018

    To improve the ability to curate and verify replication datasets within the Dataverse data archiving platform by integrating computational notebooks and software containerization with data curation workflows

    • Program Digital Technology
    • Sub-program Scholarly Communication
    • Investigator Jonathan Crabtree

    This grant funds a project led by Jonathan Crabtree, Director of Cyberinfrastructure at the University of North Carolina’s Odum Institute, to improve and expand the capabilities of the Dataverse open source data repository platform. Odum is responsible for executing and implementing the Replication and Verification Policy for the American Journal of Political Science (AJPS) and uses Dataverse as the underlying platform where authors who publish in AJPS can upload their data and software code to ensure results may be replicated. Because Dataverse was originally designed for data and not software, however, the process can be unwieldy and time consuming. Crabtree and his team plan to use the Jupyter computing platform and the open source software “containerization” toolkit Docker to create a “Confirmable Reproducible Research (CoRe2) environment” for Dataverse that would combine the ability to containerize computational research with communication and workflow tools. This would greatly speed and partially automate the process of verifying that submitted research results can be verified using the code and data uploaded. Grant funds will provide support for this project for three years.  years.

    To improve the ability to curate and verify replication datasets within the Dataverse data archiving platform by integrating computational notebooks and software containerization with data curation workflows

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  • grantee: Harvard University
    amount: $499,697
    city: Cambridge, MA
    year: 2018

    To improve the ability to curate and verify replication datasets within the Dataverse data archiving platform through a suite of software containerization and metadata tools, and to support the development of a new data curation service at the Harvard Dataverse

    • Program Digital Technology
    • Sub-program Scholarly Communication
    • Investigator Merce Crosas

    This grant funds a series of four projects by Mercи Crosas, Chief Data Science and Technology Officer at Harvard’s Institute for Quantitative Social Science to expand and improve software handling capabilities of the Dataverse open source data repository platform. First Crosas will integrate Dataverse with Encapsulator, an open source tool that allows the creation of a computational “time capsule” that preserves the exact computational environment used to conduct a piece of data analysis. Second, Crosas will create links between Dataverse and Code Ocean, a computational reproducibility platform that was spun out of Cornell Technion’s incubator program. Third, Crosas will develop a set of metadata versioning and exploration tools that will increase incentives for data curation by returning richer usage statistics to data providers and publishers. Finally, Crosas will model and pilot a fee-based curation service that would allow the sustainable scaling of data and code curation in Dataverse. This work, like all other development on and organizational innovation within the Dataverse community, will be freely available and useful to the dozens of other institutions running the software to power their own data archives.

    To improve the ability to curate and verify replication datasets within the Dataverse data archiving platform through a suite of software containerization and metadata tools, and to support the development of a new data curation service at the Harvard Dataverse

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  • grantee: Center for Open Science
    amount: $499,431
    city: Charlottesville, VA
    year: 2018

    To implement and test features to signal credibility and trust on preprint services

    • Program Digital Technology
    • Sub-program Scholarly Communication
    • Investigator Brian Nosek

    The Center for Open Science’s (COS) preprint platform was designed to serve a variety of scholarly communities, especially lowering barriers to entry for those disciplines new to preprint publication whose needs were not being served by the larger, more highly powered preprint servers like arXiv. This grant funds a project by COS founder Brian Nosek to use the COS preprint platform as the setting for a series of experiments that will test how user trust is affected by different preprint platform features. Nosek proposes to use the launch of already-planned features like annotation and visual icons to run a set of experiments on the assignment of trust by readers of scientific research. While the budget includes some technical development, the bulk of the requested funding will support the COS “metascience” team to take a mixed-methods research approach, combining surveys with analysis of usage data from the preprint servers to understand the impact of annotation and “reproducibility badges” on readers’ perceptions of trustworthiness of individual preprints and of the preprint server overall.

    To implement and test features to signal credibility and trust on preprint services

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  • grantee: National Information Standards Organization
    amount: $197,372
    city: Baltimore, MD
    year: 2018

    To support the implementation of MathML in the open source Chromium browser

    • Program Digital Technology
    • Sub-program Scholarly Communication
    • Investigator Todd Carpenter

    Somewhere between 50% and 60% of internet users use Google Chrome to browse the web. Chrome, unfortunately, doesn’t natively display mathematics using the standard XML markup language MathML. This forces sites like Wikipedia to generate static images of mathematical notation from the underlying MathML when Chrome can’t render the markup on its own. Not only does this have implications for accessibility, it also inhibits the development of innovative new interfaces and applications that would rely on dynamic interaction with mathematical notation via browser-based programming languages like JavaScript. Funds from this grant will support a project led by the National Information Standards Organization to implement full MathML rendering in Chromium (the open source codebase underlying the Chrome web browser). Technical development will be undertaken by developers at Igalia, an open source software consultancy that has played a key role in MathML integration in other major web engines.

    To support the implementation of MathML in the open source Chromium browser

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  • grantee: University of Zurich
    amount: $19,610
    city: Zurich, Switzerland
    year: 2018

    To encourage standardization of survey instruments in the domain of studies about people’s Internet uses to allow for more comparison and replication

    • Program Digital Technology
    • Sub-program Scholarly Communication
    • Investigator Eszter Hargittai

    To encourage standardization of survey instruments in the domain of studies about people’s Internet uses to allow for more comparison and replication

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  • grantee: FORCE11
    amount: $20,000
    city: San Diego, CA
    year: 2018

    To partially support the 2018 Future of Research Communication and eScholarship meeting

    • Program Digital Technology
    • Sub-program Scholarly Communication
    • Investigator Cameron Neylon

    To partially support the 2018 Future of Research Communication and eScholarship meeting

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  • grantee: National Science Communication Institute
    amount: $20,000
    city: Seattle, WA
    year: 2018

    To support two regional meetings on the future of scholarly communication as well as the launch of the Research & Scholarly Communication Network

    • Program Digital Technology
    • Sub-program Scholarly Communication
    • Investigator Glenn Hampson

    To support two regional meetings on the future of scholarly communication as well as the launch of the Research & Scholarly Communication Network

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  • grantee: University of Pittsburgh
    amount: $582,852
    city: Pittsburgh, PA
    year: 2018

    To develop software and services for transforming mathematical results as they appear in journal article abstracts into formally structured data that machines can read, process, search, check, compute with, and learn from as logical statements

    • Program Digital Technology
    • Sub-program Scholarly Communication
    • Investigator Thomas Hales

    Computers do nothing but process logical statements. Mathematics consists of nothing but such statements. It would be reasonable to assume, then, that computers would be adept, perhaps uniquely, at reading, understanding, and cataloging the academic literature of mathematics. Not yet. People and machines, it turns out, speak different mathematical languages. If computers are to help manage mathematical knowledge, they need to be taught how to read math papers. The grant funds efforts by mathematician Thomas Hales to begin that instruction. Hales has raised an international army of graduate students and postdoctoral researchers, which he plans to unleash on the abstracts of thousands of mathematical papers. They will carefully translate the definitions and results that appear in these abstracts into formal programming language. These formalized abstracts—“fabstracts,” for short—can then be used to train machine learning algorithms to “read” textual mathematics.   

    To develop software and services for transforming mathematical results as they appear in journal article abstracts into formally structured data that machines can read, process, search, check, compute with, and learn from as logical statements

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  • grantee: Yale University
    amount: $741,681
    city: New Haven, CT
    year: 2018

    To accelerate scientific discovery by using statistical machine learning to enable advanced search of mathematical literature

    • Program Digital Technology
    • Sub-program Scholarly Communication
    • Investigator John Lafferty

    To accelerate scientific discovery by using statistical machine learning to enable advanced search of mathematical literature

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  • grantee: Cold Spring Harbor Laboratory
    amount: $67,100
    city: Cold Spring Harbor, NY
    year: 2018

    To support a Banbury meeting on signals of trust within scholarly communication

    • Program Digital Technology
    • Sub-program Scholarly Communication
    • Investigator Rebecca Leshan

    To support a Banbury meeting on signals of trust within scholarly communication

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