ChRIS Research Integration Service

[jennydaman]

Title

ChRIS Research Integration Service

Short description and the goals for the OHBM BrainHack

ChRIS is a platform for making reproducible, container-based analysis easy to develop and easy to use.

Our goal for BrainHack is to get feedback on the application's user experience, and do development work of wrapping existing software as ChRIS plugins.

Link to the Project

https://chrisproject.org

Image for the OHBM brainhack website

https://github.com/FNNDSC/cube-design/blob/master/_common-assets/ChRISlogo-color.svg.png?raw=true

Project lead

Jennings Zhang, https://github.com/jennydaman jennydaman#4016

Rudolph Pienaar, https://github.com/rudolphpienaar

Main Hub

Glasgow

Other Hub covered by the leaders

• Glasgow
• Asia / Pacific
• Europe / Middle East / Africa
• Americas

Skills

Optional: docker, python, JSON

Recommended tutorials for new contributors

• Set up a brainhack friendly computing environment
• A introduction to Bash
• Python: Writing a script
• Python: Data analysis with Python
• Python: Visualisation
• Machine learning basics
• BIDS
• Machine learning for neuroimaging
• VCS: Using Git and Github
• VCS: Data management with Datalad
• Virtualization
• High Performance Computing: Oracle cloud resource

Good first issues

No response

Twitter summary

No response

Short name for the Discord chat channel (~15 chars)

ChRIS

Please read and follow the OHBM Code of Conduct

• I agree to follow the OHBM Code of Conduct during the hackathon

[astewartau]

This sounds cool! I wonder whether there is much crossover with the goals of Neurodesk? Is this something that was considered? I'm interested to know as Neurodesk is developed in my lab and aims to address a similar problem, so we are definitely interested in any ideas that may come out from this project or things that could be missing. Thanks! https://www.neurodesk.org/

[jennydaman]

@astewartau we should chat!

The goals are the same though Neurodesk and ChRIS are two different approaches. ChRIS could be described as a workflow management system or a science gateway. Other similar projects are cbrain and Brainlife.

Neurodesk seems ideal for doing computational analysis interactively, whereas ChRIS workflows are automatic.

ChRIS (and cbrain, Brainlife, ...) provide solutions for execution, pipelining, and data provenance. With Neurodesk, the user addresses these issues manually: deploying Neurodesk on a compute resource, scripting pipelines, and something like Datalad for data provenance.

I think Neurodesk and ChRIS fulfill different roles to a research developer: Neurodesk provides an easy environment to quickly and reproducibly experiment with common tools. Next, the developer would code up their own analysis as a ChRIS plugin so that it can be shared and executed reproducibly at scale with users and collaborators.

[astewartau]

That sounds extremely useful, thanks for the explanation!