Institutions: Data-Science Environments

In November 2013, we announced a new partnership and $30 million in funding to harness the potential of data scientists for basic research and scientific discovery. With our partners, we launched three Data Science Environments at New York University, the University of California, Berkeley and the University of Washington with joint funding from the Alfred P. Sloan Foundation. This was an initial five-year, cross-institutional effort to bring data science to the forefront of cross-disciplinary academic research and has been extended through 2020. The Data-Science Environments are great examples of wide-scale adoption of data science across campus.

People: Investigator Awards

The aim of our investigator awards has been to catalyze new data-driven scientific discoveries and highlight the value of a new type of data-driven scientist through $21 million in grants to the academic institutions of fourteen highly talented researchers. These investigators in data-driven discovery will strengthen support for data scientists in academia and create greater opportunities for working between disciplines (scroll down to read more about each investigator). The awards support sustained collaborations among data science researchers to build on one another's work, capitalize on the best practices and tools, and create solutions that can be used more broadly by others.

Practices: Data Science Tools for Research

New tools and methodologies are needed to accelerate data-driven research. Since 2014, we have focused on the creation, transfer and dissemination of readily usable innovative tools, knowledge and techniques for engaging in data-driven scientific research. Through this work, we have supported the development and adoption of industrial-strength data tools like Jupyter and Julia Language, and community engagement efforts from organizations like The Carpentries that engage a larger population to learn about and tackle data-driven challenges in science. We will continue supporting the development of improved software tools for natural science research through 2021, focusing on tools that are applicable across fields and institutions.

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