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: gsshelp@statistics.gov.uk
Purpose
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 gsshelp@statistics.gov.uk
- 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
Membership
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.
Benefits
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.
Scope
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 gsshelp@statistics.gov.uk.
Items
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: gsshelp@statistics.gov.uk 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 gsshelp@statistics.gov.uk.
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.
Items
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: gsshelp@statistics.gov.uk
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 gsshelp@statistics.gov.uk.
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: gsshelp@statistics.gov.uk 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 gsshelp@statistics.gov.uk)
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 gsshelp@statistics.gov.uk.
Items
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
Python RAP
Max Unsted, Department for Digital, Culture, Media and Sport
Department acronym | Department | Name |
---|---|---|
GDS | Government Digital Service | Matt Gregory |
GDS | Government Digital Service | Matt Dray |
GDS | Government Digital Service | Duncan Garmonsway |
GDS | Government Digital Service | Sarah Dean |
BEIS | Department for Business, Energy and Industrial Strategy | Steve Aherne |
BEIS | Department for Business, Energy and Industrial Strategy | Emma Oldfield |
BEIS | Department for Business, Energy and Industrial Strategy | Paul Olsson |
CO | Cabinet Office | Matt Kerlogue |
CQC | Care Quality Commission | Warwick Everett-Rimmer |
CQC | Care Quality Commission | Michael Cheetham |
DCMS | Department of Culture, Media and Sport | Max Unsted |
DEFRA | Department for Environment, Food and Rural Affairs | Sam Finlayson |
DEFRA | Department for Environment, Food and Rural Affairs | Francesca Parrott |
DEFRA | Department for Environment, Food and Rural Affairs | Rachel Dunne |
DfE | Department for Education | Cameron Race |
DfE | Department for Education | Adam Robinson |
DfE | Department for Education | Laura Selby |
DfE | Department for Education | Suzanne Wallace |
DfID | Department for International Development | Calum Campbell |
DfID | Department for International Development | Alice Marshall |
DfID | Department for International Development | Tom Wilkinson |
DfID | Department for International Development | Rebecca Brown |
DfID | Department for International Development | Alistair Inglis |
DfT | Department for Transport | Hannah Bougdah |
DfT | Department for Transport | Tamsin Forbes |
DfT | Department for Transport | Nayim Ahmed |
DfT | Department for Transport | Alex Ma |
DHSC | Department for Health and Social Care | Edward Beake |
DHSC | Department for Health and Social Care | Katie Davidson |
DHSC | Department for Health and Social Care | Matthew Malcher |
DIT | Department for International Trade | Weichao Wang |
DWP | Department for Work and Pensions | Aoife O'Neill |
DWP | Department for Work and Pensions | Dan Foley |
DWP | Department for Work and Pensions | Georgios Tzelepis |
HMRC | HM Revenue and Customs | Stephanie Hotchkiss |
HMRC | HM Revenue and Customs | Neil Wilson |
HSE | Health and Safety Executive | Ian Polanowski |
MHCLG | Ministry of Housing, Communities and Local Government | Ben Waterfield |
MHCLG | Ministry of Housing, Communities and Local Government | Duncan Cook |
MoD | Ministry of Defence | Charles Wills |
MoD | Ministry of Defence | Tomas Westlake |
MoD | Ministry of Defence | Luke Heley |
MoD | Ministry of Defence | Tony Carter |
MoJ | Ministry of Justice | Aidan Mews |
Norfolk | Norfolk County Council | Victoria Leigh |
Nisra | Northern Ireland Statistics and Research Agency | Brian Green |
Nisra | Northern Ireland Statistics and Research Agency | Katie Barbour |
Nisra | Northern Ireland Statistics and Research Agency | Carmel Colohan |
OFQUAL | Office of Qualifications and Examinations Regulation | Stephen Rhead |
OFQUAL | Office of Qualifications and Examinations Regulation | Duncan Robertson |
ONS | Office for National Statistics | Martin Ralphs |
ONS | Office for National Statistics | Alexander Newton |
ONS | Office for National Statistics | Joshua Halls |
ONS | Office for National Statistics | David Foster |
ONS | Office for National Statistics | Jack Sim |
ONS | Office for National Statistics | Anthony Edwards |
ONS | Office for National Statistics | Dan Lewis |
ONS | Office for National Statistics | Jonathan Digby-North |
ONS | Office for National Statistics | Matthew Price |
ONS | Office for National Statistics | Mitchell Edmunds |
ONS | Office for National Statistics | Tibor Mezzei |
MoJ | Ministry of Justice | Theodore Manassis |
ORR | Office for Rail and Road | Lucy Charlton |
PHE | Public Health England | Sebastian Fox |
PHE | Public Health England | Stephen Spreadborough |
PHE | Public Health England | Georgina Anderson |
SG | Scottish Government | Jeremy Darot |
SG | Scottish Government | Richard Haigh |
SG | Scottish Government | Thomas Crines |
OSR | Office for Statistics Regulation | Anna Price |
NHS Scotland | NHS Scotland | Jack Hannah |
NHS Scotland | NHS Scotland | David Caldwell |
NHS Scotland | NHS Scotland | Ciara Gribben |
NRS | National Registers of Scotland | Graham Galloway |
VOA | Valuation Office Agency | Jim Nixon |
VOA | Valuation Office Agency | David Webster |
HO | Home Office | Stephen Gordon |
HO | Home Office | Rhidian Thomas |
WG | Welsh Government | Bruce Anderson |
WG | Welsh Government | John Fuery |
WG | Welsh Government | Dave Jones |
dstl | Defence Science and Technology Laboratory | Jamie Lendrum |
dstl | Defence Science and Technology Laboratory | Karen Walker |
MMO | Marine Management Organisation | Rebecca Cavanagh |
PHW | Public Health Wales | Hugo Cosh |
Blog posts
The Government Digital Service have published two very useful blog posts about RAP:
Reproducible Analytical Pipelines
Transforming the process of producing official statistics
The Office for Statistics Regulation have also blogged about RAP: A robot by any name?
Alex Hayes has a blog, with a good post about testing statistical software.
Guides and courses
RAP Companion: a guide to building a reproducible analytical pipeline.
Reproducible Analytical Pipelines (RAP) using R: an online course that goes alongside the RAP Companion. It introduces the key ideas in reproducible analysis and provides links to other resources to support you in implementing RAP.
Choose tools and infrastructure to make better use of your data: Government Digital Service guidance about choosing tools and infrastructure that are flexible, scalable, sustainable and secure.
Communication across the network
Slack channel for RAP champions (#rap_collaboration). You will need to sign up to the government data science workspace on Slack to join this channel. The best way to make use of this channel is to change the channel notification settings to receive notifications for “all new messages”.
GSS RAP resources
Access the RAP articles and guidance originally hosted on GitHub.
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 | October 2018 | Ethnicity Facts and Figures website | Tables, Charts | Python, Javascript | Ethnicity Facts and Figures website | Ethnicity Facts and Figures website 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 |
Contact
Best Practice and Impact division
Email: gsshelp@statistics.gov.uk