Friday, August 17, 2012

Crowdsourced Map Experiment

As reader's of this blog know, I am supervising a PhD student, Craig Allison (@theRedSorcerer).  He's investigating whether point collation techniques or heat maps can be understood by users or not. (previous post about the project)


examples of point collation and heat maps

We'd like to see which one is better from a usabilty point of view and we'll publish the results. With this in mind Craig has created a 10 minute test and questionnaire that would help us answer this question, it can be found at

Please have a go and pass onto others.

Wednesday, August 8, 2012

GoogleIO Map Design Talk Response

Below you'll see a session on map design (called 'master class in map styling') featured at Google IO this year discussing Google Maps.

I think they make some excellent points and explain how to put their ideas into practise code via js code examples in Google maps.  In the introductory section they discuss the map design process as being one where you;
  • Think about what data to remove
  • Refine the data that's left (e.g. adding selective emphasis)
  • Test the map for multiple zooms
which I think is very sensible.  I've blogged about the value of removing data myself.

These are the points they make in the rest of the talk that I particularly liked;
  • Lowest Zoom first design the lowest zoom first then edit other levels afterwards by stripping out data as you zoom out higher.
  • Roads as Landmarks its handy to leave roads in for orientation (at 27:00).  
  • Width Editing The ability to edit the width of elements is a new API feature and they show how it can be used effectively at 27:25.
However, I differ with their opinions on a couple of points:
  • Ocean = White  At 25:54 they change the color of the ocean and harbour water from blue to white saying this has less visual impact.  A desaturated blue is better IMHO because it blends into the background better than white and people naturally associate blue with water.
  • Parks = Gray  Similarly at 26:01 they change the color of parks from green to gray.  Again, people naturally associate green with a park and a desaturated green would fade into the background sufficiently while being easily interpreted IMHO.
Data Density and Keys What I think they could have usefully added to their talk beyond the 3 major points they use above is discussion about coping with data density, i.e. the difference between a map mashup showing a few points and a map with hundreds of points.  At 28:46 they show a map mashup with some circles representing who likes cats or dogs at certain locations in San Francisco and at 29:00 they go on to dismiss the idea of using animal icons such as the ones in the image below (showing eagles and wolves from this post discussing icons) as being 'cheesy'.

They are quite right that A cat/dog icon could be naff but map icons have an inherent advantage over simple circles: you can work out what they mean without looking at a key.  You need extra information to work out that their red circle symbol = number of dog lovers.

That's not to say that simple icons like circles shouldn't be used, in fact they're very useful when there are hundreds of data points to plot (see above showing the location of Boris bike stations, further detail here), lots of icons on a map leads to the 'flock of sheep' problem (see below, the same Boris bike example)

So its worth using simplified icons when you need to show many data points even though they need a key to provide interpretation.