Sometimes we provide vizzes that are part of a newspaper article or a blog, other times they are just vizzes. This week the viz to be made over was an interactive world map about Nike factories. There was contextual information available on the website, but the viz itself didn’t have any commentary with it.
It’s always interesting to see how people tackle those challenges. Some choose to add additional data, others look for articles about the topic, others stick with what’s provided. All of these are valid approaches, because Makeover Monday as a learning exercise can be what you want it to be.
So well done to everyone who participated this week. I hope you had fun with the data and learned something new. There were a couple of key themes emerging during Viz Review which I’ll pick up again and wrap them into the lessons learned.
LESSON 1: MAPS
Maps are, or can be, a great, beautiful, useful, and a fun way to engage your audience. I say “can be” because sometimes maps are superfluous to the information presented or they are designed in a way that isn’t engaging.
This week we expected and saw a lot of submissions featuring maps. Logical and perfectly fine.
There are a few things to consider when designing a map. Consider this list of questions when (or before) putting a map on a viz or dashboard:
- Do you need the map? Is there an easier way to display the information?
This is especially important when you show measures on a map via symbol size or color gradient. - What is the purpose of the map?
If you think there is a good reason for using a map, what is its purpose?- Does it simply provide contextual information?
- Is it interactive and does it provide additional information for the user, e.g., in tooltips?
- Is it intended to be used as a filter? If so, are people able to click on every possible location (e.g., country, city, etc.) or make their selections in another way quite easily (e.g., lasso a region)?
- How does the map fit into the overall story?
The map should not feel like it is there just for the sake of having a map. Once you’re sure it is necessary and has a purpose, it should then also become a part of the overall story flow and design. - Have you formatted the map well?
- If your map is at the country level, you need to decide whether or not to show country labels, borders, etc. – what’s most appropriate for the data and the story you’re trying to tell?
- If your map is at a lower level of detail, for example, state, county or city, you should consider including streets, possibly waterways, and some county or postcode boundaries to help people put the data points into perspective and find their way around the viz.
- Step away from your screen, walk a couple of steps back and evaluate whether the map overall ‘looks good’. Is it part of the story? Does it blend in with the remaining colors, style and is it easy to use?
Most of you know that I’m a huge fan of maps. I have them hanging as pictures in almost every room of my apartment and love looking at them. A carefully and thoughtfully designed map is a joy to look at and it is very obvious when maps make a viz go from good to great. We can all use every geospatial dataset to practice and get better. So keep at it and see if the above list helps you make maps a better part of a viz.
We ran a webinar with our friends from Mapbox in December last year, talking about using maps in data visualization. If you haven’t seen it yet, check it out here. And if you’d like us to run another webinar with them and maybe even have specific topic suggestions, let us know and we’ll set something up.
LESSON 2: SIMPLICITY
Sometimes I’m tempted to come up with rules, but that idea quickly vanishes because there shouldn’t be rules. We really want you to direct your own learning and we’re all adults here, so I shouldn’t be telling people what they can and can’t do in data viz.
Why do I have these weak moments? Typically it’s because in recent weeks we have seen a significant increase in vizzes that are unnecessarily busy, complicated or ’embellished’ with icons to the point of becoming less effective than the original vizzes we asked the community to make over.
Aside from the fun of experimentation, there is also the thought that everything we produce and publish here has the potential to make an impact by telling a story about a topic in a way that resonates. And without wanting to stifle people’s creativity, I do also think that as analysts we have some responsibility for the data and for representing it in a way that is, at the very minimum, accurate.
Simplicity helps to bring out the key messages from a dataset. How can we achieve simplicity? From a visual perspective, the following come to mind:
- Simple color palettes
- Make sure color has meaning. If you’re not using it to highlight something or create a certain mood or emotion relating to your viz, then do you really need it?
- Consider using a neutral color like grey for anything that doesn’t need highlighting instead of using another bright color.
- Use color palettes that work with your dataset and that have few, easy to distinguish colors.
- Avoid bright background colors; they hardly ever work.
- Ensure colors have good contrast and nothing is difficult to read. If you or someone else is squinting when looking at your viz, something needs to change.
- Simple message
- Your analysis and findings don’t need to be basic, they can be elaborate and complex, but your message to your audience should be simple. Not dumbed-down, just explained in plain English (or your language of choice) and in a way that can be easily understood.
- Short, concise sentences, titles and descriptions are a winner.
- Precision in your language is important to make sure that your audience does not misunderstand you.
- Simple vizzes
- Again, your viz can be complex and technically difficult to create behind the scenes, but it should be uncluttered and easy to comprehend for the viewer.
- Unnecessary components should be removed. These often include grid lines, some labels, headers, etc., dividers and borders and shading for titles or vizzes.
- A visualization that has a clear flow and is easy to follow from top to bottom, left to right is a joy to look at. You want your audience to be able to scan the viz and get some insights straight away. Enough to encourage them to further engage with your work and explore, read details, think about your message, and maybe even take action.
These are not exhaustive lists but I hope they’re a good starting point or reminder for you and something that you can use for guidance in furture data viz projects and challenges. So let’s get to this week’s favorites…
