BR Data is the data journalism team of the public german broadcaster Bayerischer Rundfunk. Since November 2018 we are part of the investigative editorial unit (BR Recherche / BR Data) and thus are not only working on conventional data journalism projects, but also on investigative stories that require strong programming or technical knowledge. The data-team consists of approximately eight members, which have a journalism, informatics, statistics or programming background. For the publication we usually team up with investigative journalists from our editorial unit that complement our work with classical investigative skills and bring the stories to TV and radio.
As projects for the DJA application we chose nine very different stories that show the broad approach we have in our work:
1. Increased risk: A crowd sourced investigation in one of the broadest used algorithms in Germany – the Schufa algorithm for credit scoring.
2. Gift im System (Poisoned System): A text analysis backed investigation about the admission of pesticides in the European Union.
3. Kein Spiegelbild der Gesellschaft (No Reflection of Society): A data analysis on the representativeness of the Bavarian parliament
4. Das verbaute Land (land loss country): A data analysis on land loss in Bavaria
5. Deutsche Honorarkonsuln im Offshore Business (German Honorary Consuls in the Offshore Business): A follow up to a data analysis story that showed, that many of the companies registered on the island of madeira are letterbox companies.
6. Bayer AG von Hackern ausgespaeht (German industry giant Bayer AG was hacked): By conducting a port scan on the biggest German companies we showed that the servers of the Bayer AG were infected with spyware.
7. Die kranke Rechnung (The Ill Calculation): A tap through story optimized for mobile presentation that explains why the German calculation, how many doctors are needed in each county, has nothing to do with reality.
8. Wahlplakat-Analyse (Election Posters Analysis): We crowd sourced the collection of photos of election posters to find patterns ahead of the Bavarian elections for parliament.
9. Datenleck bei VOI (Data Leak at VOI): We discovered a data leak at the Swedish E-Scooter start-up VOI with 460.00 users affected. The data leak was closed after we informed the company.
What makes this project innovative?
What was the impact of your project? How did you measure it?
Source and methodology