2022
Germany’s election results in charts and maps
Country/area: United Kingdom
Organisation: Financial Times
Organisation size: Big
Publication date: 27/09/2021
Credit: Martin Stabe, Oli Elliott, Rob Davidson, Claire Buchan
Biography:
- Martin Stabe is the FT’s Data Editor, leading the newsroom on data-led digital storytelling formats.
- Oli Elliott is the FT’s newsroom Data Scientist.
- Claire Buchan was a Google News Initiative Fellow in the Visual and Data Journalism team.
- Rob Davidson was a Q-Step intern from the Department of Political Science at University College London
Project description:
This submission is for an overnight election analysis of the 2021 German federal election results. The election itself was on September 26 – this analysis was published at midday the following day, deep and insighftul scrutiny of the results and what they meant for Germany going forward, including coalition options
Content in the piece included interactive maps, charts and visual explanations of the new shape of the German parliament and how much that had changed since the previous election.
Impact reached:
With an international audience, the goal of this piece was to explain the results to readers who were not necessarily experts on German politics. It worked, reader feedback was tremendously positive, with comments like this typical:
“Excellent graphics and charts what an amazing resource. I’ll bet there’s nothing like this in the German media. I’ll be referring back to it a lot in the coming weeks and months.“
The piece was widely read and shared, attracting considerable traffic from search (reflecting its timeliness)
Techniques/technologies used:
The innovative part of being able to turn this analysis around so quickly was to quickly repurpose content and data pipelines that had been developed for collecting german election data, including polling data leading up to the pools.
Data pipelines were meticulously created using R and GitHub. CSV outputs from this process were dynamically fed into Flourish graphics with copy then written around these outputs.
What was the hardest part of this project?
As so often with data journalism projects, the hardest part of this was in managing and maintaining the data feeds to makes sure they were available to create the graphics needed for the piece as soon as possible.
What can others learn from this project?
Explaining election results with visuals is what audiences now expect – but we should not assume they know everything about how an electoral system works. Also – with so much coverage elections in news organisations, it pays to focus on where your own coverage can make a difference – in terms on both content, and timing.
