My personal year review: cleaning out ALL read-later lists

„This 1936 advice manual on living alone is smart, witty, and still helpful today“, says Vox. It’s entertaining at least, says me.

In my email conversations with English natives always wondering what’s the most reasonable thing to write, I was glad to find varieties of the crucial element „sign off lineexplained.

Once upon a time, developing new formats was part of my job, so I’m always curious about what ideas turn reality in other newsrooms. Nieman Lab on WaPo’s experiments.

In the same context: We all consume more and more media on mobile, so I’m always excited to see fully mobile-shot documentaries, even if it is more traditional ones compared to this and this one.

My first ever New Year’s resolution: writing a success diary. Usually I’m more of a crossing-of-to-do-list-person, but maybe the other way round is also an interesting approach. More tips on „more success“ in literally every area of life offers this blog post by Ms. Moneypenny (in German). Usually I avoid anything labelled „for women“, but these tips are equally valuable for men.

Breaking the usual patterns is something I believe we learn most from, to start an investigative team in the context of Buzzfeed seems like such a project. Poynter on it’s start.

„The Algorithm is an Editor“, writes the WSJ. But is it, really?

Currently, I’m trying to find more dataviz-design related blogs and people to read and follow and during this endeavour, I came across this worthwile post by Lena Groeger.

I love to learn new stuff, but I struggle to keep up with all the things I want to read. For years I’m working on finding a perfect method to read, store, read later, and make use of all what I (would like to) read. Will let you know if I found the key. If you have ideas, please let me know in the comments!

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Dataviz redesign: NYT graphic on handgun ownership

On Twitter I came across this tweet by the New York Times Graphic Desk, featuring an article about a new, yet unpublished survey of 4,000 people on gun-ownership.

A couple of users already mentioned concern that this visual representation might be misleading. For one, because it doesn’t put the data into relation with the overall population demographics. And secondly, because with a stacked bar graph, you’d expect figures to add up to 100% which they mostly don’t.

gun-ownership-demographics-edit

Now, this might be due to rounding, and usually a small note on that front can solve confusion.

But it might also be due to a misunderstanding on my side how to read the graphic. Unfortunately it cites figures that are not publicly available, so I can’t check back with the original source and look for hints.

Possible misreadings

As I understand it, the graphic is meant to read „Of female gun owners, 42% possess one handgun, 17% possess a long gun, and another 42% possess both types of weapons“.

Of course there is a chance that people of the „both“ group are also within one of the previous groups, but then the sum of percentage shares would most likely be a lot greater than 100 percent and not only a few percentage points.

The other point of criticism relates more to the racial breakdown of gun ownership, as black people make up a smaller share of the overall population. Right now it looks as if there are far more „armed black people“ than there are „armed white people“.

That’s misleading, because in fact the visual doesn’t show that a black person is more likely to have a handgun than a white person. Instead, it shows that — among gun owners — the majority of black people only owns one handgun; whereas the majority of white gun owners has both a hand gun and a long gun.

Contextualization: Gun owners vs non-gun owners

Moreover, as a non-US-citizen, I do only have a rough idea, how many people at all have guns vs those who don’t. At least the number of gun owners is mentioned in the article „Today, about 55 million Americans own 265 million guns.“ So approximately 17% of Americans own a gun.

Some twitter users suggested to improve the second graphic by visualizing it as a mosaic/marimekko chart visualize the gun-ownership-demographics in context.

To do that thoroughly, you’d also need a racial breakdown of the overall gun owners.

For the redesign, I used data from the US Census Bureau, Pew Research Center and the data in New York Times article, as the primary source is not yet available.

gun_ownership_version2

 

Of course this can’t solve the uneven add-up of the gun owner-breakdown into categories, to fix that you’d need the original source. Also, I’m not 100% happy with the color scheme, but I hope it’s at least a little less misleading.

Would be glad to hear about your thoughts how to further improve this graphic!

Next on: Learn programming (Ruby on Rails)

(Deutsche Version untenstehend)

I’ve been flirting with the idea to learn programming for quite a while, but did not really find the right point from where to start – as I was just overwhelmed by the various possibilities. For all the impatient people around: I just started learning Ruby on Rails today, will keep you updated on this blog and you can follow my cheat sheet, if you want.

For those of you who have a little more time to read and are being curious why I started with Ruby, please follow along my descision making and the great resources I came across.

Weiterlesen

Tools to test (3): Tableau

I wrote an English version of this as well, here, on DW’s onMedia blog.

Für alle, die nach einer Alternative zum Datawrapper suchen, könnte Tableau die Software der Wahl sein

 

Tableau ist zwar nicht so intuitiv wie der Datawrapper, dass man direkt loslegen kann, aber dafür bietet das Programm mehr Visualisierungsmöglichkeiten und die Ergebnispräsentation ist anspruchsvoller.

Worum geht es?

Tableau ist ein Tool, mit dem sich Daten in vielen Wegen visualisieren – als Karten, mit Diagrammen oder Grafiken – und auf einem Blatt zusammenfassen lassen – inklusive interaktiver Filter. Alles wird in einer offline-Desktop-Version des Programms erstellt und abschließend online gespeichert. Das Ergebnis kann auf Websites eingebettet und via Social Media geteilt werden.

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Tools to test (2): infogr.am

Everyone certainly came across at least one of these astonishing infographics with nice charts, highlighting the important numbers and delivering one astonishing fact after one another so that you really do scroll down all the way to the end of the graphic.

You actually don’t need to be a great designer yourself to do it – there are free tools around the web, that help you to create such infographics. Weiterlesen

Infographic redesign (2): Water price of selected cities

On Twitter I came across this infographic by Nicolas Rapp showing water prices in selected cities:

I find this a very interesting topic, but struggeled to reasily read through the graphic and compare different cities with one another or to derive any patterns from it.

  • at first you have to find city A > follow the line to the water prize bubble > then memorize the water price >find city B  on the map > follow the line to the water price bubble > look at it’s water price, hopefully remember the one from A…if I try that I have to look from one back to the other several times
  • that almost leads to my next problem: there are too many bubbles – I think it would have helped to not mark location of cities with bubbles as well, but with a square or whatever. Additionally, it would also help, if the city-location-bubble (or -square) had another colour than the water prize bubbles (which might be because of corporate design issues, but it’s really not helpful at all)
  • and last, I’d like to question the whole bubble thing at all. I know they are quite famous, I know, it look kind of nice – but it doesn’t make comparisons easier, as we’re used to compare heighths – not surface areas. Especially as the range of all values is not that big and water prices differentiate by very accurate amounts – look at Berlin and Copenhagen for example. The price differs by almost one dollar, but the bubbles „appear“ to have more or less almost the same size.

For these reasons I decided to have my own try. However, I couldn’t find the data source Rapp was using (if anyone came across that or such data, please let me know in the comments!), which is why I then extracted it from his graphic and put in into a spreadsheet (also in case anyone else want to have a go on it). Weiterlesen