Interactive Data Analytics Service (IDAS)

The Interactive Data Analytics Service (IDAS) is a high-performance computing (HPC) resource that supports large-scale and collaborative data analytics workflows involving RStudio for R and Jupyter Notebook for Python, R, and Julia. IDAS features its own HPC and graphics processing units (GPUs) and allows users to perform interactive data analysis tasks with applications used for machine learning and other artificial intelligence workflows.

IDAS serves both general research and classroom needs which were optimized during its pilot phase in the summer of 2019. A dozen faculty and staff from six departments test-drove the research platform, and classroom attributes were trialed by students in RS Data Scientist Kang Lee’s summer business analytics class.

About the Toolkit

RStudio is an integrated development environment (IDE) for R. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management. 

Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data-cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning and much more. 

Get started today! 

Request an IDAS account for research use
Request to use IDAS for teaching a course
Read IDAS documentation on the UIowa Wiki 
Stay up-to-date with IDAS maintenance and alerts

IDAS Plans for the Future

  • Enable access to Argon investor queues
  • Deploy IDAS resources on the cloud to meet remote demand


  • February 4, 2019 - Project kick-off meeting
  • April 8, 2019 - Complete stakeholder engagements/requirements analysis
  • June 4, 2019 - Classroom pilot launch
  • June 21, 2019 - Research pilot launch
  • August 19, 2019 - Initial functionality launch
  • December 26, 2019 - RStudio available for research use. Access to LSS and Argon available.
  • March 17, 2020 - RStudio Classroom moved to a multi-server environment. Sessions are now evenly distributed across all nodes. Doubled the amount of compute resources available to RStudio Classroom.

For more information about service updates, please visit our Change Log.

Questions? Contact