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2020 Year in Review

High performance systems Dec 30, 2020

Throughout the year, teams from the Indiana University Pervasive Technology Institute and UITS Research Technologies fostered compelling scientific advances with long-term positive results. Here are some highlights:

IUanyWare’s Quick Pivot

With classrooms and research groups relying on digital platforms in the wake of the COVID-19 pandemic, IU’s cyberinfrastructure keeps pace through the client virtualization service IUanyWare, IU’s digital bridge. Stephanie Cox, manager of IUanyWare, says building capacity to support digital learning and working from home was part of IU cyberinfrastructure’s long-term plan, but “we were about three years away from this capacity,” said Cox. The spring semester’s pivot to a digital campus made it essential to reduce that timeline. So, to get all campuses fully online, Cox and her small team worked around the clock over spring break, supporting students, faculty, and staff throughout the spring, summer, and fall terms.

Jetstream in the Classroom

As a Biology professor at Doane University, a small university in Crete, Nebraska, Erin Doyle uses the Jetstream cloud in the computational biology classroom to help students understand the scope of bioinformatics. Before Jetstream, Doyle’s students accessed virtual machines that often took up too much memory on their laptops; now, it’s easy. “I can just create a virtual machine, everyone logs into the web browser so it’s not using a lot of memory. Jetstream makes it so much easier to get everybody up and running,” Doyle explained.

Research Desktop (RED) Assists with Data Analysis

Colleen Rosales, an Environmental Science PhD candidate at Indiana University, says radicals – tiny, short-lived, notoriously hard to measure chemical species – play a major role in the chemistry of air pollution. Her research aims to improve the measurement of radicals and build upon science’s understanding of both indoor and outdoor air pollution. To power her calculations using Mathmatica software, Rosales uses Indiana University’s RED or Research Desktop, which allows her to expedite data analysis.

IU-Regenstrief Data Commons

Regenstrief Institute and Indiana University are partnering to provide a data commons to support research related to the pandemic. This platform, called the COVID-19 Research Data Commons, or CoRDaCo, will provide secure and efficient access to critical COVID-19 data without the usual barriers of health data privacy regulations. Through CoRDaCo, Regenstrief and IU’s University Information Technology Services’ (UITS) Scalable Compute Archive (RT-SCA) use curated datasets of COVID-19 patient data to generate synthetic medical data. Synthetic data reflects the characteristics of real patient data, but does not include real patient information. Because it is statistically similar, it can be used in the same way as real data, without compromising privacy, and allowing faster access to the information.

REDCap Keeps the Hoosier Moms Study Running

The Hoosier Moms study is part of IU’s Precision Health Initiative Grand Challenges program, led by IU School of Medicine. The study, with over 13,000 data entries, aims to improve understanding of possible genetic links between gestational diabetes and Type 2 diabetes. Flexible and accurate data management, supported by Indiana University’s research survey tool, REDCap, keeps the Hoosier Moms study on track, whether a mom-to-be chooses to join the genetics-based study when she is 8 weeks or 18 weeks along in her pregnancy.

Supplementing the Reading Process

The Distant Reader gateway, developed in 2019 at Notre Dame University by Eric Lease Morgan, supplements the traditional reading process by allowing users to make sense of a large body of text when there’s just too much to process in one mind. The tool works with a “corpus,” supplied by the researcher, which can be a web-based text, a file, or a set of files, and “reads” them, harvesting and caching the content. The gateway then uses natural language processing (NLP) and text mining, transforms the corpus into machine-readable formats and a relational database, summarizes what it learned, and then creates a “study carrel” to which the researcher receives a link. To make all of this possible, the Distant Reader uses a dynamic virtual cluster deployed on the Jetstream cloud.

For updates on workshops, internships, research opportunities, and all things supercomputing, follow @IU_PTI on Twitter.

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