Funds from this grant support a project by the Foundation Center, a nonprofit organization that aggregates records from hundreds of foundations, to enhance the usefulness and accessibility of its data. Supported activities include the development of an application programming interface (API) to allow direct computational access the Foundation Center's database, enabling the third party developers to create apps or other programs that usefully access Foundation Center data. Also supported are efforts to enhance the Foundation Center's website, promoting more sophisticated database queries and the visualization of data showing grantmaking trends. This project is jointly supported by grants from the Knight Foundation and the Commonwealth Fund

Originally funded with the help of the Sloan Foundation in 1992, the Sloan Digital Sky Survey was the first major telescopic survey to publish its data under open principles. Every single image ever collected by the Survey's 2.5 meter optical telescope is available for download by astronomers, astrophysicists and other researchers. The sheer size of the data collected, however, presented its own problems. The Sloan Digital Sky Survey corpus was simply too large for every researcher to download a full copy. In response, Johns Hopkins astronomer Alex Szalay and others developed a data infrastructure that allowed astronomers to selectively query the SDSS database, extracting only those slices that were of interest to them, and which logged every database query for later documentation. To increase the usefulness of SDSS data, Szalay also built a system that allowed astronomers to upload their own datasets which could then be easily linked with the SDSS data "in the cloud" for individual analyses and for sharing with small groups of colleagues or the broader public. Funds from this grant supports efforts by Szalay to improve and expand the SDSS data infrastructure in a number of key dimensions, revamping the data uploading process to make it more user-friendly, enabling the server to extrapolate meta-data as a way to reduce time-intensive data entry, and customizing the database in ways that would make it friendlier to researchers working in other data-intensive fields, like genomics or climatology.

A "data scientist" is someone who combines mathematical and statistical sophistication, the computational skills necessary to perform hands?on analysis of data at large scale, and the communication abilities to convey results meaningfully through visualizations and narrative. This combination of skills is still quite rare and highly in demand: an oft?cited McKinsey report published in 2011 estimates that the United States will need an additional 140,000 to 190,000 data scientists by 2018. Nonprofit organizations lag industry in the use of data scientists. Even when an organization sees how data science could improve their understanding of their clients or improve the efficacy of their work, they often lack the internal expertise and resources to take action. DataKind is a new organization founded to bridge exactly this gap. Inspired by the Teach for America model, Datakind aims to connect mission?driven organizations with designers, programmers, and statisticians from the burgeoning data science community who are looking for personally fulfilling opportunities to volunteer their time and expertise. Funds from this grant will provide two-years of pilot support to DataKind to provide a consistent revenue stream while it builds a client base of organizations and volunteers, develops a sustainable business model, and cultivates long-term funding sources.

This grant provides two years of core operating support to the Deep Carbon Observatory (DCO), headquartered at the Carnegie Institution of Washington. Funds will support the continued operation and activities of the DCO's governing secretariat and international steering committee, which is responsible for coordinating and synthesizing the individual initiatives pursued by the DCO's four scientific directorates. Though this grant, the Secretariat will pursue a diverse array of important goals, including further development of the organizational infrastructure of the DCO, strengthening the network of collaborating DCO institutions, overseeing the production of a "baseline report" that quantifies the current state of knowledge of deep earth carbon, managing a "launch" of the project aimed at major media and the public, securing matching gifts and other sources of funding for DCO activities, and developing a detailed vision for the final six years of the project.

In a conventional journal, the mechanisms for feedback on published articles are limited to a letter to the editor or direct correspondence with the author. As an increasing quantity and diversity of scholarly products are disseminated on the web, one could imagine much more efficient and constructively visible commenting mechanisms. Initial experiments in so-called "post-publication review," however, have fallen flat. Comment boxes on online articles and other research materials overwhelmingly lie empty. Perhaps comment boxes are the wrong tool. Rather than asking a reader to comment on a full article, a much more granular approach might fare better, allowing readers to comment on a particular point, equation, or assumption in a published work. Funds from this grant support the development of hypothes.is, a particularly promising effort to build precisely such a granular web annotation system. This one-year grant to Planetwork NGO will support the design, testing, and launch of hypothes.is, bringing an innovative new pilot platform to fruition that has the potential to reshape how researchers communicate and interact with one another and with online scholarly resources.

In March of 2012, Christophe Pйrignon and Christophe Hurlin unveiled RunMyCode (runmycode.org), a pilot platform for linking research datasets and code with scholarly articles. The site links published papers with a RunMyCode "companion website" that provides a real-time environment where researchers can rerun the computations reported in the paper and reproduce the experimental findings reported. Initially launched with 40 econometrics and finance papers, the platform is an innovative attempt to use the Web to enhance the reproducibility and verifiability -and thus the reliability-of scientific research. Funds from this grant support a project by Columbia University's Victoria Stodden, Chief Science Officer of RunMyCode, to expand and enhance the platform. Over 16 months, Stodden will test the RunMyCode model in a number of additional fields, including computational mathematics, statistics, and biostatistics. Stodden will also pilot integration with existing scholarly platforms, enabling researchers to discover relevant RunMyCode companion websites when looking at online articles, code repositories, or data archives. Additional funds support the development of a comprehensive business plan and funding strategy for RunMyCode.