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Use this guide to determine which what training resources 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

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

Pros:

• Easy to integrate into existing scientific workflows and run on existing scientific computational hardware
• Publicly available API means no credentials are needed to access the data
• Assuming you have access to your own computational resources, you don't have to worry about allocations
  on C3's platform.

Cons:

• All data used from the Datalake must be streamed to wherever you're processing data
• Performance benefits from working with the Datalake using C3 will not be available.

Necessary Training:

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• Existing COVID-19 API Documentation is excellent. Most users will find this information sufficient.
• Differences between public API Access and C3 Datalake access. Will help familiarize users with the
  limitations of public API access.

Level 2: GUI based data analysis on C3

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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.

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