Reproducible Analytical Pipeline (RAP) champions
RAP champions support the implementation of reproducible analytical pipelines across government.
This means promoting reproducible analysis (i.e. analysis with a clear audit trail that explains how and why it was carried out) and the use of reproducible analytical pipelines (i.e. the software methods used to make analysis reproducible).
Champions are expected to share their knowledge and provide advice and support to members of the analytical community who want to learn about and implement reproducible analysis and reproducible analytical pipelines.
Want to be a RAP champion?
Each government department can nominate a RAP champion (or several champions) to work with the network of RAP champions across government. The network is not restricted to the production of official statistics, it is open to anyone in government who is working on, or considering, reproducible analytical pipelines.
If you would like to be a RAP champion please email: firstname.lastname@example.org
The RAP champion network has been set up to support the effective implementation of reproducible analysis across government. By promoting reproducible analysis, champions support the Government Analysis Function and enable efficiencies.
Role of a champion
RAP champions are expected to:
- help others understand why and how they implemented RAP in their department and why it worked for them
- share code via platforms like GitHub so that others can learn from and adapt what has been done
- make time to respond to feedback
- allow others to shadow their team as they work through a RAP implementation, ideally supporting at least two shadowing opportunities a year
- quantify the benefits of their RAP implementation by keeping track of the time and resources saved by the implementation
- help others understand how to pick a suitable project for RAP development (the RAP Companion has some useful guidance on this)
- promote the work they have done by seeking out opportunities to present their RAP project at events (particularly those RAP projects that are actively delivering efficiencies)
- mentor people new to RAP by giving advice and being a critical friend – champions can get help setting this up by emailing email@example.com
- peer review at least one RAP project a year
- support the RAP champion community by attending RAP champion meetings, sharing findings and joining in the discussion on the #rap_collaboration channel on the Gov Data Science Slack workspace
- build their RAP champion role into their personal objectives
- plan for a replacement if they cannot continue their RAP champion role
- keep the contact list of RAP champions up to date
- help to build and promote RAP guidance
The RAP champion network is open to anyone in government who is working on, or considering, reproducible analytical pipelines.
To be a RAP champion, you need to commit to the role outlined on this page. This may require you to get permission from your line manager or Head of Profession.
The network also accepts members who are interested in RAP work, but are not champions. However, wherever possible we would encourage full champion membership in order to grow the community and support reproducible analysis.
The RAP champions network is a vibrant, cross-government community. It provides a space for analysts to share their experience, learn from others and support the wider analysis community.
On a personal level, being a RAP champion is a great corporate objective as it is an important ‘big picture’ contribution to the civil service and a significant development opportunity.
All work on reproducible analysis in government is in scope. Lots of work to date has been done in the context of automating the production of official statistics, but other analysts using reproducible analysis are welcome to join and share their experience.
Meet up three: October 2019
The third RAP meetup took place on Thursday 10 October 2019 at the Office for National Statistics in Pimlico. Presentations from the event can be accessed by emailing firstname.lastname@example.org.
Revisiting RAP levels
Joshua Halls and Alexander Newton discussed if there additional products we need to communicate the level of RAP. The network agreed that they would comment further on the ideas presented.
The Department for Education Quality Assurance Framework: re-platforming models into R
Nicky Brassington gave a presentation about how we perform and communicate quality assurance when re-platforming models.
Quality Assurance (QA) of data science projects
Martin Ralphs presented the results from the QA of Data Science survey.
QA of code guidance
Joshua Halls presented his work on developing quality assurance guidance for coding, including a link to the GitHub repository for this work (email: email@example.com if you’d like to know more about this).
What do we do now workshop
In this discussion, we revisited the objectives of the network and discussed how we should work together and coordinate. We recommended that a steering group be set up, drawn from the main network, and that we use the model of Task and Finish groups to address specific requirements. Draft terms of reference and a draft work plan to develop the network can be accessed by emailing firstname.lastname@example.org.
Meet up two: May 2019
The second RAP meetup took place on Tuesday 28 May 2019 at the Office for National Statistics in Pimlico, London.
RAP perspectives from NHS Services Scotland
Anna Price – Reproducible Analytical Pipelines in NHS Scotland
David Caldwell – NHS Scotland’s first RAP project
Jack Hannah – Scaling RAP in NHS Scotland
If you would like to know more about any of these, please email: email@example.com
Networking and show and tell
Matt Kerlogue talked about using govdown to make a map of civil servants.
Workshop session: towards a minimum viable product for RAP
In this workshop we looked at four themes: workflow, tools, standards and skills. For each, we listed elements that we thought were essential, nice to have and the pinnacle of good practice.
Champions have already thought a lot about what makes a RAP workflow, and what must be in it.
The results of the discussion and papers setting out our thinking to date can be accessed by emailing firstname.lastname@example.org.
Titles of the papers available to access:
- NHS Services Scotland paper on RAP levels
- Duncan Garmonsway – Levels of RAP and getting started
- Levels of RAP discussion on the RAP development website
- ONS Data Access Platform team RAP Good Practices cheat sheet
The RAP web presence and how to use it effectively
This discussion focused on the RAP web presence on github.
Duncan Garmonsway from the Government Digital Service talked about using testing in RAP (email: email@example.com if you’d like to know more about this).
Theodore Manassis from the Office for National Statistics presented on comparing civil services around the world: using RAP principles to process and model messy data (paper available on request by emailing firstname.lastname@example.org)
Meet up one: October 2018
RAP champions got together for the first time on 16 October 2018 at the Office for National Statistics in Pimlico, London. Papers from these sessions can be accessed by emailing email@example.com.
RAP blockers and solutions: workshop session
Matt Dray and Matt Gregory from the Government Digital Service delivered this session.
RAP in the Department for Education: discovery and how we scale
Laura Selby delivered this session.
Package review via ROpenSci
Seb Fox from Public Health England delivered this session.
Spreadsheet munging strategies
Duncan Garmonsway, Government Digital Service
Max Unsted, Department for Digital, Culture, Media and Sport
If you do not know who the RAP champion is in your department and you are not sure how to find out, email firstname.lastname@example.org.
Examples of RAP projects from UK government organisations are listed below. We have included links to the publications they produce and the pipeline code where these are publicly available.
|Department, agency or body||Date added||Description||What document elements are included in your example?||Which coding languages were used in this example?||Web link to the publication if there is one||Web link for the code if it is public|
|Cabinet Office||October 2018||International Civil Service Effectiveness (InCiSE)||Tables, Plots, Interactive elements||R||International Civil Service Effectiveness||International Civil Service Effectiveness Github repository|
|Cabinet Office||February 2019||Analysis of A B tests of processed Google BigQuery user journey data||Tables, Plots, Descriptive text||Python||Analysis of A B tests of processed BigQuery user journeys Github repository|
|Department for Digital, Culture, Media and Sport||October 2018||Analytics projects Github repositories||Tables, Plots, Interactive elements, Descriptive text||Python||Analytics projects Github repositories|
|Department for Education||October 2018||Official Statistics for the School Census||Plots, Interactive elements, Descriptive text, Open data||R, SQL||Official Statistics for the School Census|
|Department for Education||October 2018||Secondary Analysis Internal and External||Tables, Plots, Interactive elements, Descriptive text||R||Secondary Analysis Internal and External||Secondary Analysis Internal and External Github repository|
|Department for Education||October 2018||Exclusion statistics for pupils in England||Plots, Descriptive text||R||Exclusion statistics for pupils in England|
|Department for Environment, Food and Rural Affairs||October 2018||Moving a Stats Release from Genstat and Excel fully into R||Tables, Plots, Descriptive text||R|
|Department for International Development||October 2018||Modelling project complexity against financial performance||Tables, Plots, Descriptive text||R|
|Department for Transport||October 2018||Quarterly statistics tables for helicopter search and rescue||Tables||R||Quarterly statistics tables for helicopter search and rescue||Quarterly statistics release tables Github repository|
|Department for Work and Pensions||October 2018||Analysis of data from the annual People Survey||Plots, Interactive elements||R||Analysis of data from the annual People Survey Github repository|
|Department for Work and Pensions||October 2018||Official statistics - national insurance numbers||Tables, Plots, Descriptive text||R, Hypertext Markup Language and Cascading Style Sheets|
|Department of Health and Social Care||October 2018||Descriptive summary table of whole genome sequencing clusters of gastrointestinal pathogens||Tables||R|
|HM Revenue and Customs||February 2019||National Statistics - Annual Employment Allowance take-up||Tables, Plots, Interactive elements, Descriptive text||R||National Statistics - Annual Employment Allowance take-up||National Statistics - Annual Employment Allowance take-up Github repository|
|HM Revenue and Customs||February 2019||Trial Monthly UK Property Transaction Statistics||Tables, Plots, Interactive elements, Descriptive text||R||Trial Monthly UK Property Transaction Statistics||Trial Monthly UK Property Transaction Statistics Github repository|
|Ministry of Defence||October 2018||Monthly publication of economic forecasts||Tables, Plots, Descriptive text||R|
|Ministry of Defence||February 2020||RAF short term forecast and dashboard||Tables, Plots, Interactive elements||R, SQL|
|Ministry of Housing, Communities and Local Government||March 2020||Official Statistics: - Rough sleeping snapshot in England||Tables, Plots, Interactive elements||R, SQL, PowerBI||Official Statistics: - Rough sleeping snapshot in England|
|Ministry of Justice||October 2019||Cost of reoffending calculator||Tables, Plots||R||Cost of reoffending calculator||Cost of reoffending calculator Github repository|
|Ministry of Justice||October 2019||Analytical services data pipelines||Python, SQL||Analytical services data pipelines Github repository|
|Office of Rail and Road||October 2019||Index of price changes for rail fares||Tables||Python, SQL||Index of price changes for rail fares|
|Office of Rail and Road||October 2019||Webscraping prices data from the Network Rail public website||Tables, Raw data to be analysed by economists||Python|
|Office of Rail and Road||October 2019||Extraction of railway station information from a website using an application programming interface||Tables||Python|
|Office of Qualifications and Examinations Regulation||October 2018||Ofqual analytics interactive visualisation website||Tables, Plots, Interactive elements||R||Ofqual analytics interactive visualisation|
|Office for National Statistics||October 2018||bumblebee: a text mining functions / pipelines package||Plots, Descriptive text||Python||bumblebee: a text mining functions and pipelines package Github repository|
|Office for National Statistics||September 2020||Automation of crime statistics theme tables||Tables||Python, R||Our blog about the work||ONS Centre for Crime and Justice Github repository|
|Public Health England||October 2018||Local authority-specific health "at a glance" documents||Tables, Plots, Descriptive text||R||Local authority-specific health "at a glance" documents|
|Public Health England||October 2018||Published R packages to help R community to develop RAPs||Package||R||Fingertips tool||Fingertips tool Github repository|
|Public Health Scotland||February 2019||National Statistics Publication - Acute Hospital Activity & NHS Beds||Tables, Plots, Interactive elements||R||National Statistics Publication - Acute Hospital Activity & NHS Beds||Acute Hospital Activity & NHS Beds Github repository|
|Public Health Scotland||February 2019||National Statistics Publication - Psychiatric Inpatient Activity||Tables, Plots, Interactive elements||R||National Statistics Publication - Psychiatric Inpatient Activity||Psychiatric Inpatient Activity Github repository|
|Public Health Scotland||August 2019||National Statistics Publication - Quarterly Hospital Standardised Mortality Ratios (HSMR)||Tables, Plots, Descriptive text||R, SQL||National Statistics Publication - Quarterly Hospital Standardised Mortality Ratios (HSMR)||Quarterly Hospital Standardised Mortality Ratios Github repository|
|Public Health Scotland||August 2019||National Statistics Publication (Scottish Bowel Screening Programme)||Tables, Plots, Descriptive text||R||Scottish Bowel Cancer screening|
Best Practice and Impact division