2022
Covid Dashboard
Country/area: Germany
Organisation: Zeit Online
Organisation size: Big
Publication date: 22/11/2021

Credit: Paul Blickle, Fabian Dinklage, Christian Endt, Rene Engmann, Elena Erdmann, Carla Grefe-Huge, Moritz Klack, Matthias Kreienbrink, Andreas Loos, Valentin Peter, Christopher Pietsch, David Schach, Julian Stahnke, Julius Troeger, Sascha Venohr
Biography: Paul Blickle: Interaction Designer, Fabian Dinklage: Interaction Designer, Christian Endt: Data Journalist, Rene Engmann: Data Analyst, Elena Erdmann: Data Journalist, Carla Grefe-Huge: Data Journalist, Moritz Klack: Developer, Matthias Kreienbrink: Data Analyst, Andreas Loos: Data Scientist, Valentin Peter: Developer, Christopher Pietsch: Interaction Designer, David Schach: Developer, Julian Stahnke: Interaction Designer, Julius Troeger: Team Lead, Sascha Venohr: Data Journalist
Project description:
For almost two years, millions of readers have been informing themselves daily about the current Corona situation directly on the front page of ZEIT ONLINE. They don’t need to specific articles, but get all the information from local Covid cases to international vaccination rights at first glance in one tool.
Impact reached:
2020 and 2021 are the years in which data journalism became systemically relevant. Never have numbers and their presentation been as important as during the Corona pandemic, never have decisions with such great social relevance been made on the basis of key figures, data and maps. ZEIT ONLINE has found
Also ZEIT ONLINE is not content with data at the end of the reporting chain. Since delays, sometimes lasting several days, occur from the health offices via the federal states to the RKI, a team collects the latest figures directly from the websites of the districts. The team provides near-institutional services in the process – and in the process has become a primary source of Covid data.
Techniques/technologies used:
We store the now almost unmanageable amount of data, from confirmed cases to global vaccination rates, in a so-called Postgres database, which enables very short loading times and more flexible work for data analyses, for example, via a GraphQL interface. In addition to manual input, so-called web scrapers automatically read in figures from various websites and merge them into the database. We program these scrapers in Javascript and Python and execute them by so-called cronjobs every minute. We process geo data such as the map of Germany with the open source software QGIS. We analyze data with the statistical software R or Jupyter Notebook. We develop the designs together with the software Figma, often we build the first version of our graphics with the tool Datawrapper. The interactive graphics on the website consist of the Javascript library D3 and React components. To keep the overview we organize ourselves with the browser tool Trello and communicate via Slack and Zoom.
The Dashboard started on February 26nd 2020. But it got its latest major relaunch on on November 22nd 2021.
What was the hardest part of this project?
The pandemic has gone through various phases during this time, which is why our Covid dashboard has also changed again and again. What started as a basic map with some figures has become a comprehensive dashboard with all the key figures on the pandemic, from seven-day incidence to vaccination rates.
In the background, our team collects data almost around the clock. The figures from the national health department and the federal states are now supplied automatically by software.
In addition, we visit hundreds of websites of the district offices several times a day. The reason: In the reporting chain from the health offices via the federal states to the RKI, there are sometimes delays of several days. In order to be able to show the most up-to-date figures possible, a team of therefore visits the websites of the federal states every day. The team that manages the dashboard has been working entirely from their home office for almost a year – in shifts from 7 a.m. to 10 p.m., during the week and on weekends.
What can others learn from this project?
Our readers are a great support in this process. Never before have we received so much and such regular feedback for a project as for the Corona data. Over the course of the years, thousands of comments were posted concerning the Dashboard. Among them, a lot of praise, but also criticism. If there is a mistake or the figures differ particularly strongly from those of the local authorities, someone usually notices it immediately. We even discuss new features in the comments section before we publish them.