Data & Computational Research


UC Irvine professor and Sloan grantee Holly Bik discusses Phinch, a Sloan-supported biodata visualization platform, at the 2016 NYU Data Summit. Developing tools that help researchers work more effectively with data is one of the primary goals of the Data and Computational Research program.

Program Goal

To accelerate scientific discovery by helping researchers fully exploit the opportunities created by recent advances in our ability to collect, transmit, analyze, store, and manipulate data.

The Issue

Recent advances in our ability to collect, transmit, analyze, store, and manipulate data have offered the opportunity to accelerate discovery, open new avenues for investigation, and enhance the robustness and reliability of research. At the same time, the scale and scope of the data now routinely used by researchers posed new challenges for effective data management, analysis, and reproducibility. Grants in this program sought to partner with research communities to develop tools, standards, practices, and institutions that enable the efficient management and sharing of data and code at every point in the scientific pipeline—from acquisition through analysis to archiving.

As funding under Data and Computational Research ramps down, resources will increasingly focus on the legacies of Sloan grantmaking in this area, shoring up existing projects and platforms that have received Sloan funding and setting these institutions up for continued operation after Sloan funding ceases.


Interested scholars should submit a letter of inquiry of no more than two pages to [email protected]

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