Tips, tricks and tools for data visualisation: plot your data with maps

In my previous two articles I discussed the importance of ensuring that your data is clean and processed before attempting any form of data visualisation before going on to share some really awesome tools that you can use to create mind-blowing representations of the facts and figures.

In this, the final article in the series, I talk about how maps and timelines can help take your data visualisation efforts to the next level.

Maps can be used for a lot more than identifying latitude and longitude — they are also a great way to represent data. Here are some tools you could find useful when wanting to use maps as part of your data visualisations that aren’t directly about the location-ness of a map. A thought worth pondering, but most definitely possible!

1. Open Heat Map
Heat maps are typically derived so as to show how often an event occurs in the area. This could be applied to things like temperature, price or even density. To accurately show this, traditionally heat maps have required loads of mathematical knowledge and the ability to render your own map tiles and add them to existing maps. Quite complicated.

Open Heat Map eases the process in that it simply takes a spreadsheet and overlays it with the mathematics and heat map tile rendering for you. It is a great way to show off your data visualisation skills with minimal effort. Not so complicated!

2. Color Brewer
When using maps, or any other visualisation techniques for that matter, to represent data, it’s important that the colours are right. There are a number of things to take into consideration — how the user will be consuming the data, which colours work well in print, on black and white devices, on an LCD screen, are acceptable for people with low vision or colour blindness or simply with enough contrast for everyone to be able to distinguish a difference. Can get quite tricky.

Color Brewer eases your pain in that it allows you to set parameters specific to your project where you can then choose from a series of pre-selected colour palettes that meet the criteria.

Timelines
A great way to visualise event data is by using a timeline. This helps identify which events happened when and for what duration. From scheduling to investigative journalism, visually seeing records of the events along a timeline can be extremely helpful and add value to your data visualization. Here are a few tools that you can use to create scrollable and zoomable timelines simply and easily.

1. Timeline
An established platform, Timeline allows you to input data in JSON and XML formats where it then plots all types of events from just about any time format. From dinosaurs to daily planners, this is an easy visualization tool to get up and running. Timeline is fully customisable, so you can add multiple timelines that are interconnected and scroll as each is swiped individually.

2. Here is Today
Timelines are a good way to show vast scales and differences in time. Here is Today is a great example of an interactive timeline which continues to zoom out to give relative times all based on ‘today’.

It is interactive, which allows the user to consume the data as they wish, at their own pace, but also only shows the data relative to each step. It compares today with a month, then a year, then century, etc. The value added here is that presenting data in this format doesn’t overwhelm the reader with all the data at once, or forces the person to choose only one interpretation.

3. TimeFlow
A tool often used by journalists, TimeFlow allows you to create time-based diagrams to show a variety of data and help the user understand any underlying trends. The project hasn’t been touched in a few years, but it is still available for anyone willing to give it a try.

Up-skill yourself
Besides just being able to use and understand the various tools, one needs to keep abreast with the trends and changes happening in the world of data visualisation.

As you become more and more immersed in large data sets, you’ll need to understand much more than just visual display. You need to understand the tools to help you clean up the data, prune the data to a smaller segment and understand what the reader needs to know.

Once you’ve don’t that you can begin to use these different tools to create a visual representation of the data. This might be circles, maps or other charts and graphs. All of which takes time, understanding and practice.