Based on the relatively limited daily data published on the Hungarian pandemic website koronamonitor.gov.hu, Koronamonitor aims to point out correlations and information laying in hindsight that the Hungarian government fails to do themselves. Updated every morning, Koronamonitor is an ongoing project of Hungarian two-person data journalism team ATLO. First published days after the virus appeared in Hungary, it has gone through several changes, with diagrams added as the pandemic changed or new information became available. It includes not only informative charts, regional maps and international comparisons, but an interactive virus simulator developed specifically for the site, as well.
Since the Hungarian government’s pandemic-tracking website offers little to no analytical information, to many citizens, Koronamonitor became the number one source of daily data about the pandemic, offering descriptive and analytical charts based on the text-based data appearing on the governmental website each morning. Many of the changes on the site over time were based on the feedback of our active follower base. During the first wave of the pandemic, the need for understandable and easily-accessable data was vital. This was also visible on the numbers: the site reached one million downloads by the end of June 2020. Altogether, the site was accessed a total of 2245000 individual times, averaging at a daily 10-11 thousand visits.
Internationally the site was considered one of the ten most impactful and important data visualization project related to COVID-19 of 2020 by datajournalism.com. We have been honored to be mentioned among legendary newsrooms such as Financial Times, The New York TImes or The Washington Post.
The site itself is largely based on easily accessible and user-friendly online tools such as Flourish or Tableau. Many of the main charts are created in Flourish, utilizing the tool’s automatic data-updating system when connected to and external Google Sheet document. After the daily data is published on the governmental website, they need to be manually put into the Sheet document, that Flourish recognises and updates the charts accordingly.
There is also a more analytical, in-depth tool utilized at the beginning of the site (called “Explorer”), one based on the app by Vizzu. That chart offers an easy breakdown of the changes of infected, recovered patients and victims. Moreover, it is offers user interactivity, allowing changes to the chart such as addig or subtracting certain categories.
A bigger development on the site’s history was the addition of a custom-made interactive virus simulator, that is capable of predicting the actual peak of the virus based on complex mathematical calculations from the available data. It also offered user-interaction, allowing them to change parameters using the sliders, that can affect any variable such as number of victims based on the lethality ratio of hospitalized patients.
What was the hardest part of this project?
The site compiles data that is published on the official governmental website tracking the coronavirus pandemic (koronavirus.gov.hu). Unfortunately, the official data is infamous of being incomplete, not sharing data that was investigated multiple times to be available to governmental bodies but purposefully hidden from the public. The official site is thus incomparable to any of Hungary’s neighboring countries (such as Slovakia), where governments handle the pandemic with transparency, and share downloadable datasets presented on interactive charts.
Based on this problem, the hardest part of Koronamonitor is the amount of data available. Many of the calculations had to be made by our team in order to get a better understanding of the situation. Still, there are information that can never be calculated, simply because they are not accessible to the public. To mention one, the governmental site updates regional total cases (by counties), but does not do the same with either regional active cases or does not break it down to a more detailed level of cities and settlements. These data were gathered manually from locally shared data, which gave a partial picture on the situation, but later the magnitude of the second wave made it impossible to compile this data.
It is vital to mention that ATLO, the creator of Koronamonitor is a two-person project. ATLO being established by Attila Bátorfy in 2019, it is now run together with Krisztián Szabó, who is a data journalist. The minimalistic size of the data team is nevertheless very much influential in the Hungarian data scene, with high user interactivity and many collaborative projects with bigger companies (such as the Municipality of Budapest, the capital city).
What can others learn from this project?
From its easy-to-consume style to its critical thinking, Koronamonitor is a popular site among readers (based on the number of views), critically acclaimed (based on the datajournalism.com list we have been included in) and a personal achievement for the ATLO team as well. We learned a lot about reader interactivity, how to handle and incorporate user feedback, which most of the time was beneficial for the site. Thus, creating a sense of community. A critical acclaim was an elevating ending to an otherwise stressful year, giving us international feedback that the work we had done was very much so worth it. For the team personally, the daily task of updating charts and data taught us endurance and vigilance, as data was sometimes incorrect on the governmental site, and with the help of our community, we were able to shine light on these discrepancies. Our task was to be a beacon in the darkness, crated by the pandemic and worsened by the government’s resist of making data available.
Hungarian journalism can learn from the site, and see that data visualization stories can be told simply yet in a powerful way, be stylish while retaining a minimalistic approach. As this field of journalism is not as well developed as in the West (such as in the U.S.), we hope to be a good example to those newsrooms who are slowly incorporating charts to their data-based articles.