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 California, Los Angeles
    amount: $1,250,000
    city: Los Angeles, CA
    year: 2017

    To complete and synthesize the work of the Deep Energy community of the Deep Carbon Observatory

    • Program Science
    • Sub-program Deep Carbon Observatory
    • Investigator Edward Young

    The grant provides two years of support to Deep Energy (DE) community of the Deep Carbon Observatory. Representing 176 researchers in 32 nations, the group is about half from the United States and half from the rest of the world, the Deep Energy Community is the branch of the DCO that examines the abundance, distribution, and origins of deep Earth abiotic hydrocarbons and the reactions between energy and rock that produce energy. Grant funds will provide research support to the community as it completes a set of eight initiatives on reduced carbon formation, the fate of reduced carbon, confined hydrogen behavior, isotopic bond ordering of methane, ocean floor serpentinization, Precambrian cratons, analysis of sediment cores taken from a drilling site in Oman, and monitoring of subsurface microbial activity rates. The last project, joint with the Deep Carbon Observatory’s Deep Life community, aims to determine how rapidly changes in subsurface metabolic activity occur in response to seismic events. (In plain words, earthquakes might cause deep microbial blooms.) Along with completing these studies, the DE community would carry out a range of activities to synthesize and integrate the component activities, including through the DCO’s collective effort to create a system of models of deep Earth carbon.

    To complete and synthesize the work of the Deep Energy community of the Deep Carbon Observatory

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  • grantee: University of California, San Diego
    amount: $750,000
    city: La Jolla, CA
    year: 2017

    To develop and disseminate techniques for 3D mapping of the microbiology and metabolism of built environments

    • Program Science
    • Sub-program Microbiology of the Built Environment
    • Investigator Robin Knight

    This grant to professor Rob Knight and Pieter Dorrenstein at the University of California San Diego funds efforts to develop and disseminate techniques for 3D mapping of the microbiology and metabolism of built environments. Knight and Dorrenstein will use commodity scanning and motion capture systems to build 3D models of built environments, track microbial movement through a room, and identify hundreds of swab locations in 3D space automatically. They also plan to upgrade QIITA (https://qiita.ucsd.edu/), the open source microbial study management platform, to include “living data” concepts from the Global Natural products Social Network (GNPS), allowing re-annotation of MoBE datasets and connection of 3D maps with microbes and molecules from thousands of other studies. They will also produce scans of at least eight visually and scientifically compelling built environments. To reach these objectives, the University of California, San Diego, team plans to develop and disseminate improved integrated software tools. They will produce a pipeline and kit for collecting datasets and producing 3D maps, which will then be tested by MoBE community members. They expect to create a set of visually and technically compelling maps of built environmental spaces in 3D, with sequence and metabolite information. They plan to share the information online through websites, blogs, and conference presentations. They plan to train at least 30 graduate students, postdoctoral fellows, and faculty and/or research staff through two workshops. Knight and Dorrenstein will share their research and findings through peer-reviewed publications. The expected outcome of this proposal is new, high-quality 3D maps of built environments that help future funders and stakeholders better visualize and understand the microbiology of the built environment.

    To develop and disseminate techniques for 3D mapping of the microbiology and metabolism of built environments

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  • grantee: University of California, Davis
    amount: $784,007
    city: Davis, CA
    year: 2017

    To provide final renewed support for the Microbiology of the Built Environment Network (microBEnet)

    • Program Science
    • Sub-program Microbiology of the Built Environment
    • Investigator Jonathan Eisen

    This grant provides two years of operational support for the operation and enhancement of microbe.net, a website that provides services to the diverse community of researchers working at the intersection of microbiology and the built environment. Over the next two years, a team led by Jonathan Eisen at the University of California, Davis, plan to sustain the role of microBEnet as a critical hub for the field; develop and disseminate education, training, and outreach materials that will help sustain the MoBE field; build partnerships around key reference data sets in order to attract new methods, investigators, and collaborations in the field; develop synergistic interactions with other MoBE projects; and move microBEnet toward independent, long-term sustainability. The work plan includes further expansion of the network of site contributors and users. Eisen also plans to develop MoBE course materials; collect and post MoBE research protocols, conference reports, and unpublished white papers; support the addition of a MoBE component to existing Citizen Science projects; and encourage community members to curate Wikipedia pages on MoBE topics. In addition, Eisen plans to continue sequencing efforts to leverage reference datasets (genomes, metagenomics, and 16S rRNA surveys) to draw in new people to the field.

    To provide final renewed support for the Microbiology of the Built Environment Network (microBEnet)

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  • grantee: University of California, Riverside
    amount: $499,480
    city: Riverside, CA
    year: 2017

    To support continued development of a browser-based interactive platform for exploring -omic datasets

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

    Bioinformaticist Holly Bik was particularly interested in broadening the ability of metagenomics researchers to take advantage of data visualization in order to explore and understand population distributions. With Sloan support, Bik developed Phinch, a web-based visualization platform that easily integrates with common tools like QIIME. This grant provides three years of funding to Bik to scale up Phinch and grow its user base into a sustainable community-supported software project. Her plan is to begin with a user workshop to refine already-collected requirements from existing users and metagenomics pipeline maintainers, then move back into active development. The technical goals laid out for the platform include the integration of statistical tools into visualization interfaces, an important step to help researchers move from exploration of data through visualization into more robust analysis.

    To support continued development of a browser-based interactive platform for exploring -omic datasets

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  • grantee: New York University
    amount: $550,000
    city: New York, NY
    year: 2017

    To support the development of and data exchange between Datavyu (a tool for video coding) and Databrary (a platform for archiving and controlled sharing of video data)

    • Program Digital Technology
    • Sub-program Data & Computational Research
    • Investigator Karen Adolph

    In the behavioral sciences, fields like child development and behavioral ecology often rely on video as a primary source of research data. The major research repositories of behavioral video, however, do not have much more sophistication than YouTube, relying on keywords and transcripts for discovery and failing to leverage incredibly sophisticated coding data into analytic tools. Karen Adolph at NYU and Rick Gilmore of Penn State are accomplished psychologists who are responsible for developing a leading video coding tool, the open source Datavyu, and an innovative platform for behavioral video archiving, Databrary. The former is notable for its flexibility and fine-grained resolution, and the latter for its ability to set precise access controls to comply with the myriad restrictions related to the use of human subjects of the projects whose data it hosts. This grant supports an 18-month project by Adolph and Gilmore to use Datavyu and Databrary to model integration between coding tools and data repositories more generally. Since both platforms are open source and have active user communities, they are excellent candidates to prototype how standards-compliant coding data might be transferred into a data repository alongside its raw video, and how that repository might then leverage that coding data into new discovery and analytic interfaces. This work could generalize to a host of other coding tools, not to mention the handful of other social science data archives like ICPSR and Dataverse that are tentatively moving into hosting behavioral video data.

    To support the development of and data exchange between Datavyu (a tool for video coding) and Databrary (a platform for archiving and controlled sharing of video data)

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  • grantee: Julia Computing
    amount: $912,609
    city: Newton, MA
    year: 2017

    To support the continued development of the Julia programming language

    • Program Digital Technology
    • Sub-program Data & Computational Research
    • Investigator Viral Shah

    Developed by a small group of MIT computer science students, Julia was designed to be the “Goldilocks” of computer programming languages, combining the ease of use of high level languages like R or Python with the computing power of workhorse languages like C or Fortran. Julia has steadily grown in popularity since its 2012 release and has found particularly enthusiastic use in economics and finance. Further improving the language however, requires addressing several key pain points for research users. Funds from this grant support a project to update the Julia language and substantially improve usability for researchers by improving documentation and error messaging, building a substantially faster compiler, and developing a package manager to facilitate the discovery and use of third-party extensions. In addition, this grant includes resources for a concerted push to diversify the currently overwhelmingly white and male Julia developer community. Testing the application of models that have been successful in other open source software projects, the team will devote substantial effort to engagement with women and underrepresented minority groups, and offer travel subsidies for participation in Julia events to diversify its community.

    To support the continued development of the Julia programming language

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  • grantee: The University of Chicago
    amount: $750,000
    city: Chicago, IL
    year: 2017

    To study how the choice of computational tools such as programming languages and data-analysis environments impacts their users

    • Program Digital Technology
    • Sub-program Data & Computational Research
    • Investigator James Evans

    In linguistics, the Sapir-Whorf hypothesis holds that the structure of a language affects its speakers’ world view and modes of thought. University of Chicago computational sociologist James Evans and University of Wisconsin cognitive scientist Gary Lupyan hypothesize that a version of this hypothesis applies to programming languages. They propose to explore the “cognitive and social consequences of programming and data analysis environment” choices, specifically how the characteristics of programming languages might influence a developer’s efficiency, creativity, and collaboration. To evaluate this hypothesis, Evans and Lupyan will undertake exploratory studies of observational data on software development broadly then then look more closely at specific cases in scientific software development. They will use large-scale project data from GitHub to determine which specific features of programming languages (e.g., static vs. dynamic variable typing) might be best operationalized as independent variables that influence the ways in which developers think and work. They will then test the hypotheses that surface through that exploratory work using a series of comparative-language experiments to be run in constrained development environments, including the Jupyter Notebook platform. Grant funds provide three years of research support for the project.

    To study how the choice of computational tools such as programming languages and data-analysis environments impacts their users

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  • grantee: Rochester Institute of Technology
    amount: $470,458
    city: Rochester, NY
    year: 2017

    To develop a mathematically-aware search engine for popular use by both students and experts

    • Program Digital Technology
    • Sub-program Scholarly Communication
    • Investigator Richard Zanibbi

    A “math aware” search engine is exactly what it sounds like, a search engine that speaks and understands the language of mathematics. It would be able to locate not only words on pages, but to identify and recognize mathematical symbols, expressions, equations, formulas, and theorems. This is harder than it sounds, since common mathematical symbols can take on special meanings depending on the context in which they appear. This grant funds work by computer scientists Richard Zanibbi and Lee Giles to create an easy to use, fully math aware search engine. Zanibbi and Giles plan to develop state-of-the-art methods for extracting, indexing and retrieving math in documents; develop algorithms for the recognition of handwritten math and math captured in images; and implement these in a user-friendly interface with helpful features like autocompletion of common queries. The new engine will then be tested on Wikipedia and on CiteSeerX, an open-source repository of academic papers. The completed search engine, if successful, would vastly expand the possibilities of discovered for amateur and professional mathematicians alike, with numerous applications in both research and education.

    To develop a mathematically-aware search engine for popular use by both students and experts

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  • grantee: Association of Research Libraries
    amount: $315,100
    city: Washington, DC
    year: 2017

    To develop and disseminate a Code of Best Practices in Fair Use for Software Preservation

    • Program Digital Technology
    • Sub-program Scholarly Communication
    • Investigator Krista Cox

    This grant funds an initiative by the Association of Research Libraries to document and clarify copyright and intellectual property law issues related to the archiving of software. Led by intellectual property lawyer, Peter Jaszi, the initiative has three parts. First, Jaszi and a team of collaborators will undertake a broad literature review and conduct some 40 long-form interviews with legal experts, librarians, museum curators, software developers and other stakeholders to produce “a report on problems that arise in software preservation regarding issues of copyright and fair use.” The report will then become the basis for a set of small workshops to generate, after legal review, a code of reasonable best practices used by archivists to resolve those problems. Finally, a substantial outreach push will build community consensus in support of those best practices. The work will be stewarded by the Association of Research Libraries, whose membership has a strong interest in this area, but will also draw heavily on the museum community, as well as major professional organizations in computer science, and other computationally intensive disciplines. The effort promises the legal state-of-play surrounding several thorny intellectual property issues related to software archiving, promote better archival practices across the country and further the cause of reproducibility in research, which depends on the continued availability of software used to generate scientific results.

    To develop and disseminate a Code of Best Practices in Fair Use for Software Preservation

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  • grantee: Columbia University
    amount: $490,298
    city: New York, NY
    year: 2017

    To integrate behavioral insights into the foundations of standard macroeconomic models by re-examining the role of the Euler equation

    • Program Economics
    • Initiative Behavioral and Regulatory Effects on Decision-making (BRED)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Emi Nakamura

    How do people decide between consuming more today and saving more for the future? Mainstream macroeconomists have one answer: the Euler Equation. Simply put, it says that an optimizing agent will consume today up to the point where adding one more unit now would provide the same utility that could be expected if consuming that extra unit were deferred until tomorrow instead. In principle, the attitude expressed by the Euler Equation seems reasonable enough. Surely if you knew that having a second dessert right now, for example, would not be as enjoyable as having that dessert tomorrow, you would do well to wait. Yet as a practical matter, such calculations are difficult or impossible for individuals to make. And we all know from experience that hardly anyone ever tries. Real people rely on heuristics at best, and are sometimes not only inconsistent but also self-defeating. The Euler Equation also has theoretical implications that limit its applicability to the real world. For instance, to a population governed by the Euler Equation, the timing of consumption does not depend on when income arrives. So Euler populations will not alter their behavior in response income events like tax cuts. But clearly people in the real world do so alter their behavior. This grant funds the research of Emi Nakamura and Jon Steinsson of Columbia University to test alternatives to the Euler Equation against a uniquely comprehensive dataset of the consumer behavior of the residents of Iceland, which has Iceland has usefully kept records of nearly every financial transaction in the country. The goal is to devise a replacement for the Euler Equation and to create new macroeconomic models that are both less naпve and more useful in predicting consumer behavior in the real world.

    To integrate behavioral insights into the foundations of standard macroeconomic models by re-examining the role of the Euler equation

    More