Digital Information Technology
Data and Computational Research
From the natural sciences to the social sciences to the humanities to the arts, the availability of more data and cheaper computing is transforming research. As costs for sensors, sequencing, and other forms of data collection decline, researchers can generate data at greater and greater scale, relying on parallel increases in computational power to make sense of it all and allowing the investigation of phenomena too large or complex for conventional observation.
Grants in this sub-program aim to help researchers develop tools, establish norms, and build the institutional and social infrastructure needed to take full advantage of these important developments in data-driven, computation-intensive research. Emphasis is placed on projects that encourage access to and sharing of scholarly data, that promote the development of standards and taxonomies necessary for the interoperability of datasets, that enable the replication of computational research, and that investigate models of how researchers might deal with the increasingly central role played by data management and curation.
What do we know about the data stewardship gap? University of Michigan