This project aims to develop infrastructure that transforms the process of discovery through semantically-aware analysis and visualization of data from the physical sciences, in the hopes of demonstrating the high impact that interdisciplinary data-driven research can have on scientific research as a whole.

Changes of a galaxy's properties over time are driven by the quantity of its cold gas, the raw material from which stars form. Thus, understanding the properties of a galaxy's cold gas component will tell us both how the star formation process changes over time and how this affects galaxies. Using a recently completed survey of carbon monoxide gas in a sample of nearby galaxies, the project…

A great challenge in astrophysics is to understand in detail how the initial smooth distribution of matter in the early Universe formed the first galaxies. Complementing observations of real galaxies, researchers use computational simulations to model the early Universe and study the results. This process allows one to learn how these first galaxies might have formed. However, the sheer size…

Scientific discovery across the physical sciences is increasingly dependent on the analysis of volumetric - or three-dimensional - data, that may come from a supercomputer simulation, direct measurement, or mathematical models. Researchers typically seek to extract meaningful insights from this data by visualizing and analyzing it in various ways. The ways in which scientists process…

The University of Illinois, in collaboration with multiple community college and public libraries, will develop a data storytelling toolkit for libraries (DSTL) to support meaningful and effective data communication, empowering libraries to utilize the rapidly growing data landscape. DSTL will connect real-world examples of data use with data stories (including narrative strategies and data…