Brief Risk Assessment Guide.
project governance
A suggested format for risk assessing data science projects.
An appropriate table format for a risk log:
| Risk | Consequences | Impact | Likelihood | Exposure | Risk | Mitigations | Impact | Likelihood | Exposure | Risk |
|---|---|---|---|---|---|---|---|---|---|---|
| Description of risk | What could go wrong | Impact score | Likelihood Score | Likelihood x Impact | Risk assessment (high/medium/low) | A list of things you could do to reduce the risk | Revised impact score | Revised likelihood score | Revised exposure | Revised risk |
Along with this risk exposure diagram to help you assess the impact, likelihood and exposure scores:
Important things to consider in your risk assessment - follow the reference link to a helpful NHS checklist template [1]:
- How will you ensure no passwords, data or other sensitive information is shared by making your repo public?
- How will you safeguard against people accidentally pushing this information in the future after the repo is made public?
- How will you manage users expectations of quality and on-going maintenance?
- How will you use licencing to protect any proprietary rights and set limitations on liability from others using your code?