Week one: Doggiegraphics?

Today we started off the lesson by going over the homework that we had to do, which was writing about what stories we can extract from certain databases. We had quite a few examples, the ones we went over in class were the following: are MPs expenses, Wikileaks war diaries, Gapminder comparing income to life expectancy in different countries, and the one that I wrote about which was a scene by scene comparison of Hollywood films to their true-life events.

When talking about the one I wrote about, I discussed how I compared the site to fake news and how the data can help journalists stray away from it as well as how it can come in handy to journalists writing reviews. It gives them much more background information. These types of movies are supposed to teach those about historical events and if the movie is based off completely inaccurate facts then it gives people a whole different story compared to what really happened, making their historical knowledge mainly false.

We then moved onto discussing visualising data, we were given many different examples such as static infographics, standalone charts, scrolling stories and animation. We were given separate examples for each of these examples, thus website showing the type of data that was explained.

In relation to this we watched an animated video about the losses of WW2, which used data to comparing all the soldier’s deaths in separate countries as well as a comparison of all the civilian deaths. The use of data in this video gave a different outlook on the war, having already studied it white thoroughly, I knew most of the information however seeing it in bar graphs/ different infographics gave a very broad view. Showing how extreme the circumstances were.

An overview of different types of infographics. Taken from https://www.ft.com.

Going more thoroughly into infographics, discussing many different types. I learn that good ones to use for distribution are bubble and heat-maps and that ones I should never use in ranking are dot strip lines and bump. I also learnt that when it comes to spatial infographics, thus the use of maps, you shouldn’t immediately use maps when something is location/geographically based. There should be another reason for using the map such as population or correlation. The image above shows the types of infographics that we looked at, all having their own purposes for certain data.

Infographic on the ultimate data dog, taken from https://informationisbeautiful.net.

We took a look at some specific infographics on a website, which were all very interesting, however I took an interest in one in particular which was: ‘Best in Show: The Ultimate Data Dog’. Shown above. This compared all different dogs based on intelligence, costs, longevity, grooming, aliments and appetite. This was shown with the dogs facing different ways and the size and colour of the dogs. Although this was interesting to me because of my obsession for dogs (as well as making me sad for all the doggies that were ranked so low, they should all be in the ‘hot dogs’ section, in my opinion) the graph itself wasn’t that good, it was hard to understand, a bit messy.

Infographic on my weekly spending on the first week of September, by Georgina Blackwell.

We ended the day by creating our very own infographic, we could choose any one we liked from the table that we looked at (which I displayed earlier). We had to make it about anything in our lives that we though fit. In the end, I decided to make a pie chart about my weekly spending. Having always kept a record of the money I spend every week (as my money comes in weekly), which is split it into different categories, this was rather easy. I took the first week of September and used that as my guide. I came up with what is shown above.

Georgie x