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.