Welcome to the C3 Digital Transformation Institute!

You have been given a grant as part of the new C3 Digital Transformation Institute (DTI)!
To make the start of your DTI experience as painless as possible, we have assembled a set of resources to

  1. Introduce researchers of all stripes to the C3 system
  2. Help researchers determine what level of training they will need to leverage C3's resources
  3. Point researchers directly to relevant documentation they will need
  4. Provide worked examples of different research workflows and how they may be ported into
    C3's environment, or may use C3's resources

Introduction to the C3 system

C3 is a Java-based data analytics engine designed to make the ingestion and analysis of heterogeneous data sources
as painless as possible.

C3 provides a system to join data from multiple sources into a single unified federated data image.

With the federated data image defined, C3 then provides an API to access that data, and in the case of time-series data,
perform numerous transformations and computations all producing normalized time-series data at regular intervals.

While C3 supports many data science capabilities familiar to the researcher, some expected functionality may be missing.
For these cases, C3 supports implementing new data processing functions in python and javascript.

Like any other API porting your own workflows will take some care and time to learn properly.

Please leverage this guide to make porting your

Services available from C3

How does C3 differ from traditional HPC systems?

What types of software can be run on C3?

What types of software cannot be run on C3?

How do I get started?

Use this guide to determine what training you need to utilize C3's resources effectively. We have separated
researchers into four levels based on what level of interaction with C3's resources they require. We include
basic examples of workflows which might fall into that level, pros and cons of operating on that level, and
a list of training resources we recommend resources researchers completing on the DTI training environment
before starting their C3 allocations. This will ensure researchers will be able to use their allocation as
efficiently as possible.

Level 1: Use COVID-19 Datalake Only

For many researchers, they will simply want to leverage the C3 COVID-19 Federated Data Image.



Necessary Training:

Level 2: GUI based data analysis on C3

Level 3: Utilize C3 AI Suite and Jupyter notebook analysis

Level 4: State-of-the-art ML workflows requiring special ML models and/or GPUs

Accessing C3

C3 Allocation Management

Essential Concepts

C3 is quite different from traditional HPC resources.

C3 Types

Canonicals, Transforms, and Data Integration

Timeseries Analysis and Metrics

Machine Learning Pipelines


Help! This guide doesn't solve my problem!

No problem! You're not alone! Please send an email to help+c3ai@ncsa.illinois.edu with a description of your issue
and one of our team will work with you to resolve your issue.


If you feel aspects of this guide are incomplete or Inaccurate, please send an email to help+c3ai@ncsa.illinois.edu with the
issue or suggestion, and we will work to incorporate it to make the documentation better. We appreciate the new perspective
More eyes can bring to a software project!

Your DTI Team


Jay Roloff - Executive Director

Matthew Krafczyk - Data Analyst

Yifang Zhang - Data Analyst


Eric Fraser

Greg Merritt

Matt Podolsky