It's December 24th and we at Journocode wish you a very merry Christmas and lovely holidays! Before we head off to have dinner with our families, we present to you a little overview of all the great people who contributed to our advent calendar this year – in data!
For the second year in a row, we are overwhelmed by the many amazing guest authors who volunteered to write a post for our advent calendar. A big shout-out and thank you to everybody who contributed! This year, we focused on behind-the-scenes reports of underrepresented stories, and we couldn't have wished for more interesting entries. Our authors talked about topics ranging from crowdsourcing election campaigns to scraping tennis players to analyzing satellite imagery. We heard what it's like to do data journalism as the only person in your newsroom, and about the state of data journalism in Ghana. We saw data-driven Christmas wallpaper and fancy visualizations of sunlight durations.
You might have noticed that we asked each author a couple of questions. We shared some of the funnier answers in the author boxes already. But we wouldn't be data journalists without looking at the data as a whole. Voila, this is our analysis:
25 people have contributed to this year's advent calendar. Eight of them are women, 17 are men (we still have to balance that one out a little). Most of the authors wrote on their own, but there are also two teams who collaborated on the post. Two posts have been co-authored by three people.
Only five of our 25 authors have not mentioned the word data in their author box bio. Four of them lead a data journalism team, one is the program manager of an NGO. One is a full-time student. The big majority, however, describe themselves as journalists.
One fact that we are particularly proud of: Our authors come from four continents (hello Australia — next year we're gonna find someone to make it five). The most common city amongst them is the German capital Berlin. What a coincidence ...
But — what is data journalism?
Good news up front: Three of our authors said they don't have to explain data journalism as often as they used to. Apparently, data journalism has become somewhat better-known. At Journocode, we appreciate this finding and hope it means that data journalism has, by now, gained a degree of normality within newsrooms.
Yet, almost all the people we asked said they need to explain data journalism at least once a week. And yes, some people still misunderstand what we do: Maximilian Zierer says he is often asked whether he works in data protection, while Simon Haas' workmates think he is in the Matrix again whenever they see him working on code.
The pie of pies
Yes, pie charts are somewhat old-fashioned and often not the best way to visualize information. It seems like that message has spread in the community: When we asked our authors how many pie charts they had built in their careers, no one said they are using them on a regular basis. Among the people who answered this question, five said they had never build one and six had built no more than ten. Four remarked in some way or other that they had built more pie charts than they cared to admit. And then there were three people who avoided the topic entirely: David Hilzendegen said he had built two raspberry pies and Paul Blickle had made a bar chart out of pie.
See here our delicious 3-D hand-drawn pie of pies visualizing the answers. Oops, we did it again.
The funniest file names
When it comes to file names, our authors are super creative. These are our top 5 funniest file names:
- doener-emoji-unicode-anschreiben-100 (2).pdf by Maximilian Zierer
- Vorvertragliche Information für außerhalb von Geschäftsräumen geschlossene Verträge und für Fernabsatzverträge zum Girovertrag.pdf by Simon Haas
- "لا شيء", which means "Nothing!" in Arabic by Islam Salahuddin
- Cartman by Abigail Larbi Odei
- Why_do_Pandas_and_Matplotlib_work_how_they_do?.ipynb by Marcel Pauly
So much caffeine
Apparently, data journalism requires a whole lot of caffeine: Each day, the 25 authors of our advent calendar consume 44 cups of coffee, 40 bottles of Club Mate, 13 cups of tea and five bottles of coke combined. That equals approximately 8.82g of caffeine! The caffeine queen is our very own Marie-Louise Timcke: She stated that she drinks 27 bottles of Mate per day!!
But enough caffeine for now! Close your laptop, put down your phone and go talk to your loved ones already! Have a very merry Christmas and see you next year!
Yours, the Journocode squirrels