reliable, robust, and accessible

big data neuroscience

Ph.D. Preliminary Meeting

Gregory Kiar

Outline

• background
• clowdr
• provenance graph evaluation
• replication/extension of analysis
• timeline

background

• data collection and federation is booming
• but a reproducibility crisis plagues science
• we need for stable methods and evaluation

the "plan"

• extend platforms for HPC in the cloud
• create framework for evaluating prov. graphs
• replicate and improve impactful study

clowdr

• Streamlining the tool-to-impact cycle
• Prototype, parallelize, and publish
• Microservice: no server, no database

clowdr + cbrain = cc

• a common API for data and compute
• CBRAIN as a portal for Compute Canada

provenance graphs

• we can record pipeline's internal calls
• construct a provenance graph of execution
• compare graphs across executions?

example

Possible types of differences could be:

• convergence rate
• resulting file size
• execution time
• resources used
• warnings
• errors

node = command
edge = data

neuroinformatics replication

• replicate existing impactful study
• perform stability analysis
• improve the stability of tool(s)
• replicate study with new tool
• attempt to generalize old and new findings

for instance?

timeline

• clowdr: 1 year
• provenance analysis: 1.5 years
• replication and extension study: 1 year
• total: 3.5 years (grad. Spring 2021)

acknowledgements

references

All references can be found in my proposal.

Thank you!!!