This week we looked at spending on Research & Development in different countries around the world with data from the UNESCO Institute of Statistics.
The original visualization was a very poor representation of the data and made it very difficult to get any insights and a deeper understanding of the information. However, that’s what this project is all about, to create better visual representations of datasets to improve people’s understanding of information.
This week it was great to see many new participants joining Makeover Monday. Some also participated in this week’s Viz Review.
Welcome to everyone who just joined our project!
— Mansoor Adenwala (@MansoorAdenwala) August 9, 2018
And some people continue to partake even when they’re on holiday…
— Reinhard Tockner (@r_tockner) August 9, 2018
Great job, Reinhard!
Andy and I also noticed a lot of vizzes that at first seemed questionably ‘creative’ (i.e., the viz was even harder to understand than the original), but it turned out that most of them were intentional recreations of the chart – to see how it could be done – while others were experiments with new chart types.
We welcome these just as much as we welcome bar charts and line charts. My suggestion is the following: Makeover Monday at its core is a project that wants to improve on the original charts. That is what most people have in mind when they participate. If you create a chart as an experiment and you are aware that it isn’t more effective than the original, that is perfectly fine. If so, it’s a good idea to include a short note in your tweet or on data.world that clarifies this.
Why? Because creating a viz that doesn’t improve on the original could make people think you didn’t understand the purpose of Makeover Monday. For clarity sake, consider pointing out your intentions when the intent of your viz is not a makeover.
LESSON 1: COLORS
This week was very colorful and we reviewed several vizzes that featured A LOT of colors. Keep it simple and keep it meaningful. Too many colors confuse and distract your audience. Every color you use should be meaningful and intentional.
This week, many submissions focused on the dominance of the US and China in R&D spending compared to other countries. If you want to highlight specific countries, I recommend you pick a color for each of those, but limit the colors to four or five. If you then include all other countries, give those countries a subdued color like grey or light blue. This way, the data from the other countries is available for context, while the highlighted countries ‘pop’.
Color can help you bring that focus, so use it sparingly for greater effect.
A great example comes from Sarah Bartlett who used a bright purple to highlight those countries that are the focus of her findings.
LESSON 2: A PRE-PUBLISHING CHECKLIST
I notice the same minor mistakes and things overlooked every week, so I thought it would be useful to produce a checklist you can use before publishing your visualization. Keep in mind that ticking all these boxes doesn’t guarantee a great viz. Your story and design still need to be developed by YOU. This list, while not exhaustive, can help you do some sanity checks for completeness.
- Does your viz have a clear title that draws the attention of your audience and sets the scene for the information presented?
- Have you included the data source(s) and your details (name, Twitter handle, etc.)
- Have you removed unnecessary ‘data ink’, such as gridlines, borders, shading, axis lines? This will typically result in a cleaner looking visualization that is more visually appealing and easier to read.
- Does your dashboard have the appropriate size? Making it too large means it will display with scroll bars on various screens. Making it too small means it will be very hard for users to see and interact with information.
- Have you added annotations with your insights and findings? These are not always required because sometimes the visualization communicates everything easily. The more complex the topic and dataset, the more I’d recommend to include explanations, small call outs, or annotate individual data points to guide your audience.
- Have you formatted your tooltips? Depending on the tool you use, this may not be necessary, but don’t neglect the design of your tooltips. They can be a great way to add an additional layer of information to your visualization when used effectively.
- Does your interactivity work? Have you tested the interactive elements of your visualization to make sure they result in the right behaviors? Be sure to test the interactivity after you publish your work as well.
- Have you checked spelling?
- Check the basic formatting. Are the objects in the visualization aligned well?
I hope you will find this checklist useful for your future visualizations and Makeover Monday submissions.
Now here are this week’s favorites.