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: Mozilla Foundation
    amount: $819,480
    city: Mountain View, CA
    year: 2014

    To build educational resources, prototype tools, and foster an ongoing dialogue between the open web community and researchers in order to make science more open, collaborative, and efficient

    • Program Digital Technology
    • Sub-program Data & Computational Research
    • Investigator Kaitlin Thaney

    Since 2011, the Mozilla Foundation, developer of the popular Firefox web browser, has hosted a series of “Software Carpentry” boot camps developed by computer scientist Greg Wilson to teach basic software engineering practices to researchers who in a professional capacity were writing code to manage data but had never received any formal software development training.  The project has been a success.  Interest in the boot camps has been robust both in the U.S. and Europe and Mozilla has expanded their effort into a larger project, called the Open Science Lab,  aimed at collaborating with the scientific community to develop open source tools and other resources to aid in scientific research and collaboration.  Funds from this grant provide continued operational support to Mozilla for this project.

    To build educational resources, prototype tools, and foster an ongoing dialogue between the open web community and researchers in order to make science more open, collaborative, and efficient

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  • grantee: The University of Chicago
    amount: $499,156
    city: Chicago, IL
    year: 2014

    To facilitate more efficient movement, management, and sharing of research data

    • Program Digital Technology
    • Sub-program Data & Computational Research
    • Investigator Ian Foster

    One of the more surprising difficulties of working with big data—more than a few hundred gigabytes—is the sheer difficulty of moving it from place to place.  Though the price of cloud and local computing has dropped and the availability of bandwidth has increased, the standard protocols for transferring data over the Internet (http and ftp) simply start to break down at that scale.  Errors multiply, requiring laborious file integrity checking and repetitive restarting of transfer operations.  There is, as yet, no satisfactory solution to the simple yet thorny issue of moving meso? and larger scale data from one computer to another. Globus, a data management tool developed by a team at the University of Chicago’s Computation Institute, offers a promising solution to these problems, allowing the seamless transfer of large datasets with none of the drawbacks of existing methods.  The project is currently pivoting from support by grant funding to a sustainable nonprofit business model based on both individual and institutional subscriptions (and has already signed up six major universities as charter members).  However, it is facing a catch?22:  The team needs robust marketing and customer support capacity to build up a customer base, but without a customer base they will not have the funds to provide marketing and customer support.  Funds from this grant provide temporary bridge funding to the Globus platform, enabling the project to provide top quality service while it builds a customer base and moves towards independent sustainability.

    To facilitate more efficient movement, management, and sharing of research data

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  • grantee: Data & Society Research Institute
    amount: $10,000
    city: New York, NY
    year: 2014

    To organize and run a workshop on the social, cultural, and ethical dimensions of big data

    • Program Digital Technology
    • Sub-program Data & Computational Research
    • Investigator Danah Boyd

    To organize and run a workshop on the social, cultural, and ethical dimensions of big data

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  • grantee: New York University
    amount: $15,000
    city: New York, NY
    year: 2014

    To run a workshop and associated hack day on strategies and tools for cross-platform identity and contribution management in citizen science

    • Program Digital Technology
    • Sub-program Data & Computational Research
    • Investigator Franзois Grey

    To run a workshop and associated hack day on strategies and tools for cross-platform identity and contribution management in citizen science

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  • grantee: New York University
    amount: $1,500,000
    city: New York, NY
    year: 2013

    To advance data-intensive scientific discovery through new methods, new tools, new partnerships, and new career paths

    • Program Digital Technology
    • Sub-program Data & Computational Research
    • Investigator Yann LeCun

    While data science is already contributing to scientific discovery, substantial systemic challenges need to be overcome to maximize its impact on academic research. This is one of three grants, made as part of a five-year, $37.8 million partnership with the Gordon and Betty Moore Foundation, that aim to empower natural and social scientists by strengthening the ability of select U.S. colleges and universities to successfully conduct data-rich and computationally intensive research. Over the next three years, supported campuses will use grant funds to develop meaningful and sustained interactions between disciplinary researchers in the natural and social sciences (e.g. astrophysics, genetics, economics) and researchers in the methodological fields that deal with large scale data collection and analysis (e.g. applied mathematics, statistics, computer science). In addition, supported campuses will establish long term, sustainable career paths for data scientists, and develop an ecosystem of analytical tools and research practices that will facilitate effective research across a range of diverse scientific disciplines. Additional funded activities include holding workshops and training sessions for scientists who work with data, identifying data-science bottlenecks faced by researchers, and disseminating lessons-learned to the academic and research communities.

    To advance data-intensive scientific discovery through new methods, new tools, new partnerships, and new career paths

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  • grantee: University of Washington
    amount: $1,500,000
    city: Seattle, WA
    year: 2013

    To advance data-intensive scientific discovery through new methods, new tools, new partnerships, and new career paths

    • Program Digital Technology
    • Sub-program Data & Computational Research
    • Investigator Edward Lazowska

    While data science is already contributing to scientific discovery, substantial systemic challenges need to be overcome to maximize its impact on academic research. This is one of three grants, made as part of a five-year, $37.8 million partnership with the Gordon and Betty Moore Foundation, that aim to empower natural and social scientists by strengthening the ability of select U.S. colleges and universities to successfully conduct data-rich and computationally intensive research. Over the next three years, supported campuses will use grant funds to develop meaningful and sustained interactions between disciplinary researchers in the natural and social sciences (e.g. astrophysics, genetics, economics) and researchers in the methodological fields that deal with large scale data collection and analysis (e.g. applied mathematics, statistics, computer science). In addition, supported campuses will establish long term, sustainable career paths for data scientists, and develop an ecosystem of analytical tools and research practices that will facilitate effective research across a range of diverse scientific disciplines. Additional funded activities include holding workshops and training sessions for scientists who work with data, identifying data-science bottlenecks faced by researchers, and disseminating lessons-learned to the academic and research communities.

    To advance data-intensive scientific discovery through new methods, new tools, new partnerships, and new career paths

    More
  • grantee: University of California, Berkeley
    amount: $1,500,000
    city: Berkeley, CA
    year: 2013

    To advance data-intensive scientific discovery through new methods, new tools, new partnerships, and new career paths

    • Program Digital Technology
    • Sub-program Data & Computational Research
    • Investigator Saul Perlmutter

    While data science is already contributing to scientific discovery, substantial systemic challenges need to be overcome to maximize its impact on academic research. This is one of three grants, made as part of a five-year, $37.8 million partnership with the Gordon and Betty Moore Foundation, that aim to empower natural and social scientists by strengthening the ability of select U.S. colleges and universities to successfully conduct data-rich and computationally intensive research. Over the next three years, supported campuses will use grant funds to develop meaningful and sustained interactions between disciplinary researchers in the natural and social sciences (e.g. astrophysics, genetics, economics) and researchers in the methodological fields that deal with large scale data collection and analysis (e.g. applied mathematics, statistics, computer science). In addition, supported campuses will establish long term, sustainable career paths for data scientists, and develop an ecosystem of analytical tools and research practices that will facilitate effective research across a range of diverse scientific disciplines. Additional funded activities include holding workshops and training sessions for scientists who work with data, identifying data-science bottlenecks faced by researchers, and disseminating lessons-learned to the academic and research communities.

    To advance data-intensive scientific discovery through new methods, new tools, new partnerships, and new career paths

    More
  • grantee: Woodrow Wilson International Center for Scholars
    amount: $600,001
    city: Washington, DC
    year: 2013

    To work with government, emergent distributed networks, and other stakeholders to make mass collaboration for data collection, analysis, and problem-solving more trustworthy, efficient, and actionable

    • Program Digital Technology
    • Sub-program Data & Computational Research
    • Investigator Lea Shanley

    While citizen science projects, crowdsourcing, and other forms of mass collaboration on the Web hold the promise to contribute significantly to scientific research, they often lack adequate institutional or systemic controls to properly mitigate data privacy, cybersecurity, legal, and financial risks. Without such controls in place, government entities or other large institutions are often barred from collaborating with citizen science initiatives, limiting their usefulness and impact. This grant supports efforts by the Commons Lab at the Woodrow Wilson International Center for Scholars to help reduce these barriers by identifying, assessing and prioritizing the risks associated with mass collaboration projects and developing standards, policies, best practices, and other resources that both government agencies and citizen entrepreneurs can use to work together more effectively. Over the next two years, the Wilson Center will publish two peer-reviewed journal articles on privacy, human subjects, and intellectual property issues; host a roundtable series on cybersecurity; construct an inventory of U.S. government involvement in mass collaboration projects; hold a policy briefing for government agencies; and analyze governance models for mass collaboration projects.

    To work with government, emergent distributed networks, and other stakeholders to make mass collaboration for data collection, analysis, and problem-solving more trustworthy, efficient, and actionable

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  • grantee: University of California, Davis
    amount: $245,721
    city: Davis, CA
    year: 2013

    To develop a web-based framework for the visualization of scientific data generated by standard data pipelines

    • Program Digital Technology
    • Sub-program Data & Computational Research
    • Investigator Holly Bik

    In many scientific fields, the process of cleaning and preparing data is managed by increasingly well-established software pipelines. Raw data goes in and structured, refined data comes out ready for analysis. Data pipelines are particularly valuable in fields where the data coming out of instruments are relatively standardized—genomic sequencers, for example, or astronomical telescopes. One potential benefit of data pipelines is that they lower the barriers to sophisticated data visualization, since platforms to explore data visually could be directly connected to data pipelines rather than rely on costly work by individual researchers to prepare and load data. Yet while basic visualization capabilities have been hard-wired to specific data pipelines, there is no generic framework that could interface between data pipelines and data visualization tools.This grant supports efforts by biologist Holly Bik of the University of California, Davis to develop just such a framework. Partnering with leading data visualization firm Pitch Interactive, Bik will work with an initial set of use cases to develop a framework for data visualization on top of existing genomic data pipelines, keeping an eye toward its applicability to other fields.

    To develop a web-based framework for the visualization of scientific data generated by standard data pipelines

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  • grantee: University of California, Berkeley
    amount: $179,267
    city: Berkeley, CA
    year: 2013

    To produce a suite of mature R products that allow researchers to easily access disparate data sources, and develop the R scientific community through training and engagement

    • Program Digital Technology
    • Sub-program Data & Computational Research
    • Investigator Karthik Ram

    Three open source programming languages form a canon of sorts for the emerging field of data science: Python for general computation; Hadoop for managing massive unstructured data; and R for statistical analysis. Funds from this grant support efforts by Karthik Ram, a postdoctoral scholar at the University of California, Berkeley, to expand and strengthen the R community through the development of products aimed at lowering the barriers to the use of R. Ram has developed an R software module, for instance, that greatly simplifies the process of gathering data from archives and services commonly accessed by scientists, like Dryad, the Global Biodiversity Information Facility, or the Biodiversity Heritage Library. Ram’s module thus obviates the need for scientists to write their own idiosyncratic code to parse data from such repositories. Grant funds will support the further development of R modules by Ram and his team, as well as outreach efforts to the scientific community to provide training and speed adoption of the new tools.

    To produce a suite of mature R products that allow researchers to easily access disparate data sources, and develop the R scientific community through training and engagement

    More