A combination technology framework and process for accelerating science, xDCI is shorthand that stands for cross-disciplinary data science cyberinfrastructure. xDCI provides scientists with a technology framework that enables their research communities to rapidly deploy robust cyberinfrastructure that can easily ingest, move, share, analyze and archive scientific data in all its varieties. The xDCI framework integrates its services and tools with the practices of domain scientists, which means they are better able to fast-track their science once they’ve deployed the xDCI cyberinfrastructure.

As data science cyberinfrastructure, xDCI supports data-intensive research in a number of scientific domains including genomics, environmental science, biomedical and health sciences, and the social sciences. xDCI leverages open source software packages such as SciDAS (Scientific Data Analysis at Scale) and iRODS (the integrated Rule Oriented Data System) to address significant challenges in data storage, sharing, analysis, and visualization.

RENCI offers xDCI as a solution to scientific communities that will simplify the process of creating and using data science cyberinfrastructure, including tools for analyzing, sharing and managing large data sets. By using the xDCI framework, scientists are able to incorporate data science tools into their work, speed up and simplify processes for data sharing, collaboration, analysis and management, and thereby enable scientific discoveries at a faster pace.

Project Team

Ashok Krishnamurthy (Project lead)

Ray Idaszak (Project co-lead)

Stan Ahalt

Kira Bradford

Chris Calloway

Claris Castillo

Jason Coposky

Jon Crabtree

Sarah Davis

Howard Lander

Christopher Lenhardt

Arcot Rajasekar

Kimberly Robasky

Terrell Russell

Erik Scott

Don Sizemore

Marcin Sliwowski

Michael Stealey

Hao Xu

Hong Yi


xDCI, a data science cyberinfrastructure for interdisciplinary research

xDCI, accelerating data cyberinfrastructure and research for Community Science Gateways