Tag Archives: Data Visualisation

Maps, Maps, Maps: good maps, bad maps and accessible maps

What do you do if you find QGIS too easy (and like pain) – you start mapping in R.

But what do people in the room do with mapping, and what data sets do they use?

Putting Open Data on Maps. A good thing?

In Birmingham they used Edubase to plot previous ‘catchment’ areas for schools. Some schools do it from the centre of schools, some from the school gates. And some schools have more than one gate… Some were basing it on distance to the nearest train station. It was about creating boundaries, and then you could set up a tool based on postcodes to see if people are within the boundaries are not.

Mapping challenges

Newer cross rails stations might positively benefit house prices – so it was an interesting thing to map. But what is a railway station? That matters if you are determining distances – is it the station or the platform or the car park? These things matter.

The Ordnance Survey released a green spaces map – which seems to have quite a few holes in it. There are some open tree and green spaces databases. There hasn’t been any analysis done on the relationship between house prices and green spaces. The research tends to focus on negative factors, not positive ones. There’s research about well-being and green spaces, but not house prices.

Tom Smith and the Data Science Campus have started using machine learning to identify areas – and then layer other data on top of that, like house price data. Scottish LiDAR is available, as is Northern Ireland, but it’s somewhat patchy. The centre of Belfast isn’t covered! It’s an issue with how the data was collected.

There’s been too much of companies just shoving data on a map. Often totally useless visualisations on a map are created, with too much data. Should it be four different maps? Or do we need to segment by seriousness. What’s the use case for the map? There are some cases where putting data on a map is actively unhelpful. Wales has such massive variations in population density that just putting data on a map is often not useful.

You need to ask yourself what the narrative is of the data you’re putting on a map.

Mapping disasters

All the Trafford Centre crime was moved to a nearby street having a huge impact on the perception of the crime. There have been other examples, where all the crime without a geo reference was assigned to the police station – which has a massive impact on the surrounding area, which was suddenly a massive crime blackspot, according to the figures.

In the 1920s the American petrol companies took all the railways off the maps they sold, changing people’s perceptions of travel.

A small GIS change can be done at a national level, that has a huge ramification at a local level – like school applications. And that creates real anger. One school deliberately changed their measurement point to the middle of their playing fields to exclude a council estate. It’s about more than points on maps, but special analysis – patterns and correlations might not be readily available.

Mapping Tools

Pub data from Open Street Map can be used for fun maps – like pub densities. The hotspot is in Islington. One person recommended ScapeToad to create cartograms.

There’s plenty of debate on the value of R in mapping. Some people (the Python fans) love it. Some really don’t. There’s options to integrate statistic and mapping stuff with Shiny. QGIS is great for special analysis, by R Shiny is great for pushing tools out that people can explore data with. It can have problems with scaling, though. Choose the context for use carefully.

R is good for learning to code – Jupiter with R is a great combination.

But what about paper maps?

There is an issue of access – 20% of people still aren’t digital connected, and you need paper to access them. And there’s a role for paper maps in exhibitions. People will screenshot Interactive tools to put them in reports – we’re not great at producing aesthetically pleasing maps for those uses. If they screenshot, things like dates and copyright statements are missing. We should make automatic “print this” options.

One attendee has a printed paper map of a count in the 17th century, used for writing. Big, printed maps have their uses. They’re great tools for community interaction in groups.

The French Open Street Maps community used Field Maps to engage with people, getting them to colour in where, for example, schools are.

Map accessibility

This raises the question: are pop-ups in an interactive map a bad thing? Paper maps appear to show everything. But they didn’t really – there’s a real art to what they leave out, to make sure nothing undermines the purpose of the map.

Maps really are the ultimate visualisation tool, but you have to ask what the map is for. But can you really guess what people are actually going to use maps for? Probably not – they will always surprise you.

Do you think about red/green colour blindness – it’s such a simple thing to miss, but it can destroy the usefulness of your map for a percentage of the population or, worse, lead to them misinterpreting them.

3D Maps? Depends on the context. You can do that in Excel 2016. It can be really effective. Physical maps are really useful for blind people – but consult with the people you’re targeting. Not all blind people are the same. Acuity Design are good at this. UCL are experimenting with soundscape for the blind.

Session Notes

Turning LiDAR Data into Actionable Insight

default rendering of DSM in QGIS
Default rendering of DSM in QGIS on top of OS StreetView

My pitch to Open Data Camp 3 is to demonstrate my work with LiDAR data showing how it can be used to provide insights which can improve efficiency in a variety of business sectors. Continue reading Turning LiDAR Data into Actionable Insight