BBC Data Team on Missing and Confusing Data
All the analysis tools and techniques in the world cannot land you a story when the data is missing or so messy as to be incomprehensible. Data journalists from BBC News share insights on how to tackle missing and confusing data in two subject areas. They discuss how they created an original dataset on NHS dentistry, and how they combine disconnected datasets to investigate UK property ownership.
Harriet Agerholm
Harriet Agerholm is a data journalist at the BBC data team and has a special interest in social affairs, mainly working on housing and health stories. She uses programming language R for data analysis and visualisation, but dabbles in Python too.
Libby Rogers
Libby Rogers is a data scientist specialising in spatial data, automation and dealing with tricky data sets using R and Python. She also provides training, support and tools for the BBC data team. She has a particular interest in health and cost of living.
Will Dahlgreen
Will Dahlgreen is a senior data journalist in the BBC’s data team with an interest in investigations and financial crime. In recent years he has worked on international investigations, such as the Pandora Papers and Uber Files, and domestic investigations on property ownership and company secrecy.
- 28 June 2023 14.00–15.00
Location: MRB 05 Lecture Theatre. Media Research Building.