Making all research data accessible, discoverable, and usable

Globus Labs is a research group led by Prof. Ian Foster and Dr. Kyle Chard that spans the Computation Institute, Department of Computer Science, and Math and Computer Science Division at the University of Chicago and Argonne National Laboratory. Our modest goal is to realize a world in which all research data are reliably, rapidly, and securely accessible, discoverable, and usable. To this end, we work on a broad range of research problems in data-intensive computing and research data management. Our work is made possible by much-appreciated support from the National Science Foundation, National Institutes of Health, Department of Energy, National Institute of Standards and Technology, and other sources, and in addition to computer science, engages fields as diverse as materials science, biology, archaeology, climate policy, and social sciences. We work closely with the team developing the Globus research data management platform, who often challenge us to think bigger—and sometimes implement our less crazy ideas.


We are developing methods for online data analysis and reduction on exascale computers

We are developing methods to index large amounts of scientific data distributed over heterogeneous storage systems

We are developing methods to automatically extract scientific facts buried in scientific publications


Kyle Chard will be giving a presentation about Parsl - a parallel scripting library for Python - at Scipy 2018 this July in Austin. We hope to see you there!

Ian Foster gave a keynote presentation about “Going Smart and Deep on Materials” at the Annual Meeting of The Minerals, Metals, and Materials Society (TMS) society. There, he talked about our work towards making data science more prevalent in materials engineering.

Anna Woodard has joined Globus Labs as a postdoc! Anna earned her PhD in Physics from Notre Dame, where she studied top quarks as part of the CMS collaboration. She will be working with Kyle Chard to simplify parallel computing in Python as part of the Parsl Project.

BigDataX Research Experiences for Undergraduates funded by NSF. More info here.