If you are working with data using the Python programming language, you probably rely on an open source software library called NumPy which provides tools to store large multidimensional arrays and matrices, algorithms for their analysis and manipulation, and means to move them from one software package to another. Without NumPy, scientific computing in Python would be slower, more cumbersome, and more error-prone. Initially released in 2005, NumPy’s core code has built up a substantial “technical debt,” which not only constrains the future development of the platform but also creates a high barrier to entry into its open source developer community. This grant supports an ambitious project led by NumPy core developer Nathaniel Smith to discharge this technical debt and set in place standards and architecture to encourage more sustainable development going forward. Using this funding, Smith and a team of developers will develop new modular systems for creating data types and arrays of data within NumPy; conduct a wholesale clean-up of the NumPy codebase; and launch a new community engagement process that includes face-to-face meetings, the onboarding of new contributors, and processes for proposing and evaluating larger architectural changes to the platform.

The Moore-Sloan Data Science Environments (DSEs) are a major collaboration between Sloan and the Gordon and Betty Moore Foundation to support three university-based data science centers devoted to empowering data-driven research through the creation of new tools, resources, infrastructure, and career paths that help university researchers make the most of the possibilities that data science opens for the 21st century scientist. Supported centers have been launched at the University of California, Berkeley; NYU; and the University of Washington. This grant provides funds for the hire and support of a DSE coordinator who will take responsibility for internal communication between the DSEs, serve as a visible point of contact for inquiries and outward messaging for best practices coming out of the DSEs, and develop a network to connect and support “alumni” who have in one way or another left the DSE universities and are now building data science capacity at other universities. This new coordinator position will be initially housed within the Hopewell Fund, an arm of the New Venture Fund.

Data Carpentry is community-driven organization that develops and teaches workshops on the fundamental data skills needed to conduct research. A sister effort to Software Carpentry, which provides researchers with hands-on training in the basic software engineering skills that are increasingly needed for the conduct of 21st century science but are unlikely to be taught in standard scientific PhD curricula, Data Carpentry workshops target researchers who think of themselves not as software developers, but who may write custom code for the management, preparation, and analysis of their research data. Because the size, shape, and format of data differ substantially across disciplines, the “Data Carpentry” curriculum is necessarily domain-specific in a way that Software Carpentry is not. After initial successes in ecology, genomics, geospatial data, and biology, the Data Carpentry leaders will use the funds from this grant to grow into new disciplines (image analysis, economics, and chemistry), in the process standardizing their curriculum development processes in order to make it easier to form new disciplinary communities. Over the next two years, Data Carpentry plans to assemble Advisory Committees for each area of focus, run curriculum-building hackathons, and then pilot each bootcamp several times before releasing to the broader community of Software/Data Carpentry members.

The Research Data Alliance is an international grassroots organization that brings technologists, developers, and researchers together to jointly develop and adopt data-sharing infrastructure, tools, and practices. RDA working groups tackle some of the thorniest topics facing data science today, including reproducibility, data preservation, interoperability, data citation, and best practices for data repositories. RDA provides useful services to the data-driven research community, including to many grantees supported through the Foundation’s Digital Information Technology program. Funds from this grant provide core operating support to the U.S. regional chapter of the RDA and support efforts to build out the organization’s U.S. administrative infrastructure and grow its membership base. Funded activities over the next three years include the production of reports detailing RDA data sharing recommendations, member outreach, creation of adoption case studies for RDA products and services, trainings, annual stakeholder meetings, and the development of a long term business plan for independent sustainability.

This grant provides three years of support to an ongoing postdoctoral fellowship program administered by the Council on Library and Information Resources (CLIR) that aims both to grow data and software curation capacity within research libraries and to develop the next generation of data and software curators who will bring deep research experience into the organizational context of the university library. Fellows are PhD-level researchers who are selected, in part, for their potential to build collaborative relationships with natural and social scientists across the university. Since the launch of the program in 2012, fellows have been placed at a wide variety of universities, working with scientists and library staff on projects to improve the university’s data and software curation services and responding to requests from researchers to build tools and resources that speak to their needs. Recent participating institutions include UC Berkeley, MIT, Yale, the California Digital Library, Vanderbilt, the Federal Reserve Bank of Kansas City and the U.S. Agency for International Development. Funds from this grant will support the 2018-2020 class of CLIR fellows, which includes a cohort of four software curation fellows as well as four additional data curation fellows in the natural and social sciences. In addition to covering some salary, travel, and professional development support for fellows, grant funds cover operational costs associated with the administration of the program.