4 Recommended Ways of Working

In addition to using suitable analytical IT tools, associated ways of working should include:

Data

• Complying with Analytical Platform information governance procedures - see the Analytical Platform User Guidance section on information governance.
• Utilising and updating centralised data source documentation (e.g. about data quality, quirks, descriptions of non-obvious fields). For curated Athena databases use the Data Discovery Tool ⁸. Knowledge about other data sources should be maintained by the relevant team in some kind of structured document or repository ⁹.

Code

• Implementing the Data and Analysis coding standards including using Git/GitHub repositories to store and share code.
• Taking steps to make your code as reproducible as possible - all MoJ coding projects should include at least the MoJ RAP manual level one components to be considered reproducible. For more information about reproducibility and Reproducible Analytical Pipelines see the MoJ RAP manual and the Analytical Function Quality assurance of code for analysis and research.

Getting assistance

• Using Slack to get and give assistance (better than alternative tools for code/error sharing, the Analytical Platform team use it exclusively and it integrates with GitHub). More information about this can be found in the Analytical Platform and related tools training guidance section on Slack.
• Utilising the Analytical Platform and related tools training guidance to be aware of and make use of suitable internal and external learning opportunities.
• Referring to the Analytical Platform User Guidance as appropriate.

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8. See the Analytical Platform User Guidance section on Data Discovery and Documentation and the Data Discovery GitHub page↩︎

9. E.g. at minimum a spreadsheet, and not just in the narrative documentation for the project↩︎