The Practical Guide to Designing with Data is a book which was really useful to look for a dashboard project. While the whole book is really interesting, there are some points I wanted to discuss. One of the book's first sections highlights the importance of removing “Chart Junk” which is any stylistic aspects that distract or cause visibility issues. I think this is really important for me to keep in mind for the project as I always have the desire to add stylistic elements, but keeping this in mind will help me find the balance between stylistic choices and clarity.
Another really interesting point in the book concerns mapping, which will be integral to my project considering the data I am looking at. The main point of this part is that understanding what you are mapping can help. What was really helpful to me here was how the book talks about metro or subway maps, and how they utilise inaccurate geography for the sake of clarity. Basically, these maps show you from location to location, rather than exactly how you get from location to location. It’s definitely something I want to explore as it could be a useful way of making my data more understandable.
In 1869, Russian chemist Dmitri Mendeleev sought to organise the known elements in a logical way. While many variations had been created before, Mendeleev's organisation method utilised the atomic number of the elements to arrange them, which also left space for undiscovered elements. As we know today, Mendeleev’s table is the definitive version due to how his data was organised. What’s important about Medeleev’s table is that he understood what part of the data should lead the organisation, which is something that will be incredibly important for me to understand in my project. For example, I’m currently trying to figure out how to map the locations in my data, and I initially attempted to draw a geographically accurate map for my data, however, this looked messy and was hard to track, so I redrew it to be less geographically accurate. This worked much better and made more sense because my data wasn’t about what streets I took, but about the distances and location. Researching the periodic table helped me understand this, as seeing how Mendeleev understood that his data was about the atomic number, made me realise how my data was about the locations and distances.
Otto Neurath was an Austrian sociologist and political economist who most notably created Isotype alongside Ger Arntz. Isotype is a pictorial language used to show social, technological, and biological connections and data. When researching Isotype, I realised I had seen this before when I was at the Pompidou Centre last summer. When I found the photos I had taken when there, I was somewhat annoyed with myself over not realising how relevant the things I was looking at then would be to me. Isotype is a brilliant way of showing data as it makes it so much more engaging than just numbers and helped you to understand the scale between figures. Along with this, the icons used are really nicely drawn by Arntz, who marries a bold clarity with a soft and friendliness which makes the documents much more approachable. While I initially thought Isotype would conflict with Brian Suda’s philosophy of Chart Junk, but I feel seeing how effective these charts are that there definitely is a middle group between simplicity and illustrative aspects which is something I could explore in my project.
Fritz Kahn is another whose work I saw in the Pompidou Centre and I was again utterly unaware of how I would later envy my past self for not paying it enough attention. Kahn was a physician whose most recognisable work was an industrial-style illustration of the inner workings of the human body. Creating this illustration using relatable imagery is a really effective way of making an easily understandable visualisation. It’s such an unorthodox type of chart as it’s so detailed and illustrative but instead of using detail for purely stylistic reasons, the detail is essential for making a relatable and understandable chart. While it probably won’t have much application in my project, it was interesting to see how a chart can utilise a lot of visual data and made me understand the importance of knowing the amount of data required for data visualisation.
This week has been really useful and has helped me a lot with my project work. Looking at different ways detail and style can be used has helped me understand what why certain stylistic choices are made depending on what the chart is for or who it is for. Also, looing at the periodic table and Brian Suda’s book has helped me understand how to identify the main point of data, which will be very important for my project.