Real World Data Science

Defining Purposes and Uses to Support the Development of Statistical Products in a 21^st Century Census Curated Data Enterprise Environment

Learn about researchers’ plans to develop the Curated Data Enterprise through a use case research program.

Welcome to Real World Data Science, a new project from the Royal Statistical Society, in partnership with the American Statistical Association. We bring together data science students, practitioners, leaders, and educators to share knowledge, learn from, and be inspired by real-world applications of data science.

Latest content

Translating the Curated Data Model into Practice - Climate resiliency of skilled nursing facilities

How does the Curated Data Enterprise Framework work? Take a look at our demonstration use case on the resilience of skilled nursing facilities.

Vicki Lancaster, Stephanie Shipp, Sallie Keller, Henning Mortveit, Samarth Swarup, Aaron Schroeder, and Dawen Xie
University of Virginia, Biocomplexity Institute

Nov 19, 2024

Advancing Data Science in Official Statistics – What is the Curated Data Enterprise?

The US Census Bureau faces the challenge of addressing complex questions requiring novel datasets and sources to answer. Official statistical agencies and public- and…

Sallie Keller, Stephanie Shipp, Vicki Lancaster, and Joseph Salvo
University of Virginia

Nov 8, 2024

Advancing Data Science in Official Statistics – The Policy Problem

In this article, we introduce a new approach for the US Census Bureau to produce statistical products using survey, administrative, procedural and opportunity data. This is…

Sallie Keller, Stephanie Shipp, Vicki Lancaster and Joseph Salvo
University of Virginia

Nov 1, 2024

Is data science a new and exciting set of skills, necessary for analyzing 21st century data? Or is it (as some have claimed) a rebranding of statistics, which has carefully developed time-honored methods for data analysis over the past century? In this article, we use two popular data science algorithms to examine the difference between data science, statistics, and other occupations.

Jonathan Auerbach, David Kepplinger, and Nicholas Rios ask, ‘What is data science?’

Read their analysis

Viewpoints

Democratizing Data: Using natural language processing and machine learning to capture dataset usage

Real World Data Science speaks with Julia Lane, professor at the NYU Wagner Graduate School of Public Service and visiting fellow at RTI International, about an initiative…

Brian Tarran

Mar 11, 2024

£10m for UK regulators to ‘jumpstart’ AI capabilities, as government commits to white paper approach

It’s been a busy seven days for AI news in the UK as two major government reports were published, millions of pounds of new investments were announced, and warnings rang out…

Brian Tarran

Feb 8, 2024

UK government sets out 10 principles for use of generative AI

Government says staff need to understand what generative AI is, its limitations, and how to deploy the technology lawfully, ethically and securely.

Brian Tarran

Jan 22, 2024

Case Studies

Forecasting the Health Needs of a Changing Population

Taking NHS usage of the 1 million people in and around Bristol, then combining with population forecasts into a modelling framework has created a sophisticated but…

Luke Shaw (BNSSG ICB), Rich Wood (BNSSG ICB, University of Bath), Christos Vasilakis (University of Bath), Zehra Onen Dumlu (University of Bath)

May 8, 2024

Deduplicating and linking large datasets using Splink

Robin Linacre introduces an open source tool, developed by the UK Ministry of Justice, which uses probabilistic record linkage to improve the quality of justice system data.

Robin Linacre

Nov 22, 2023

Learning from failure: ‘Red flags’ in body-worn camera data

When body-worn cameras were rolled out to juvenile correctional officers in Texas in 2018, senior leaders hoped proactive analysis of camera metadata could be used to…

Noah Wright

Nov 16, 2023

Generative AI is based on neural networks, which are so-called ‘black boxes’. This makes it difficult or impossible to explain the inner workings of the model which has potential implications if in the future you are challenged to justify decisioning or guidance based on the model.

Excerpt from the UK government’s framework for the use of generative AI

Read our key takeaways

Ideas

Careers

Data science and AI in the public sector: An interview with ONS’s Penny Holborn

Penny Holborn, head of faculty for the Office for National Statistics Data Science Campus, talks to Jonathan Gillard about keeping up with new developments, the value of…

Jonathan Gillard

Mar 27, 2024

Data science and AI in financial services: An interview with Nationwide’s Matthew Jones

Matthew Jones, head of decision science and analytical innovation at building society Nationwide, talks career path, data science tools and skills, and the role of AI in…

Jonathan Gillard

Mar 21, 2024

‘I fell in love with math, really, and fell into data science because of that’

A passion for solving mathematical problems led Niclas Thomas to a PhD in machine learning and then a career in data science in the retail sphere. Now head of data science…

Brian Tarran

Oct 4, 2023

Defining Purposes and Uses to Support the Development of Statistical Products in a 21^st Century Census Curated Data Enterprise Environment

Latest content

Translating the Curated Data Model into Practice - Climate resiliency of skilled nursing facilities

Advancing Data Science in Official Statistics – What is the Curated Data Enterprise?

Advancing Data Science in Official Statistics – The Policy Problem

Viewpoints

Democratizing Data: Using natural language processing and machine learning to capture dataset usage

£10m for UK regulators to ‘jumpstart’ AI capabilities, as government commits to white paper approach

UK government sets out 10 principles for use of generative AI

Case Studies

Forecasting the Health Needs of a Changing Population

Deduplicating and linking large datasets using Splink

Learning from failure: ‘Red flags’ in body-worn camera data

Generative AI is based on neural networks, which are so-called ‘black boxes’. This makes it difficult or impossible to explain the inner workings of the model which has potential implications if in the future you are challenged to justify decisioning or guidance based on the model.

Ideas

Nowcasting upgrade for better real time estimation of GDP and inflation

AI series: Ensuring new AI technologies help everyone thrive

AI series: What is “best practice” when working with AI in the real world?

Careers

Data science and AI in the public sector: An interview with ONS’s Penny Holborn

Data science and AI in financial services: An interview with Nationwide’s Matthew Jones

‘I fell in love with math, really, and fell into data science because of that’

Published by

Our partners

With support from

About us

Contribute

Defining Purposes and Uses to Support the Development of Statistical Products in a 21st Century Census Curated Data Enterprise Environment

Latest content

Translating the Curated Data Model into Practice - Climate resiliency of skilled nursing facilities

Advancing Data Science in Official Statistics – What is the Curated Data Enterprise?

Advancing Data Science in Official Statistics – The Policy Problem

Viewpoints

Democratizing Data: Using natural language processing and machine learning to capture dataset usage

£10m for UK regulators to ‘jumpstart’ AI capabilities, as government commits to white paper approach

UK government sets out 10 principles for use of generative AI

Case Studies

Forecasting the Health Needs of a Changing Population

Deduplicating and linking large datasets using Splink

Learning from failure: ‘Red flags’ in body-worn camera data

Generative AI is based on neural networks, which are so-called ‘black boxes’. This makes it difficult or impossible to explain the inner workings of the model which has potential implications if in the future you are challenged to justify decisioning or guidance based on the model.

Ideas

Nowcasting upgrade for better real time estimation of GDP and inflation

AI series: Ensuring new AI technologies help everyone thrive

AI series: What is “best practice” when working with AI in the real world?

Careers

Data science and AI in the public sector: An interview with ONS’s Penny Holborn

Data science and AI in financial services: An interview with Nationwide’s Matthew Jones

‘I fell in love with math, really, and fell into data science because of that’

Published by

Our partners

With support from

About us

Contribute

Defining Purposes and Uses to Support the Development of Statistical Products in a 21^st Century Census Curated Data Enterprise Environment