Reproducible Analytical Pipelines (RAPs) are automated statistical and analytical processes. They ensure that analysis is reproducible, efficient, and high quality. The Analysis Standards and Pipelines team have worked with teams across government to help them implement RAP. From our experiences …
We are launching a brand new, cross-government data event, running from 27 September to 1 October 2021, and you’re all invited.
Richard Laux outlines the 3 main reasons for collecting data about people’s ethnicity and identifies 6 principles for collecting these to meet all users’ needs.
The Data Science Accelerator mentoring programme is expanding to offer a new data visualisation branch. Applications for both open on 14 June.
Our diverse range of speakers at the Data Science Community of Interest shared what they think makes a good data science project.
We need your help setting a data standard to make public services more effective for UK citizens.
We want your help to identify and establish an Open Standard for beneficial ownership data.
We're borrowing software engineering tools to make analytical code more robust, and encouraging people to ditch spreadsheets for programming languages. Our aim is ease of reproducibility, quality assurance, auditability, adaptability and sustainability of our analysis.
The Data Standards Authority has published new data guidance to help teams publish their own reference data for use across government
The Data Standards Authority invites you to play a leading role in the future development of the Service Manual and service assessments, increasing the importance that data plays.
DWP statistician Catherine Hope leads the cross-government ‘Presentation Champions’ who share best practice for designing the best ways to present government data. In this blog she shares some tips on the best ways to make your information understandable.