Beware of the Bluetooth Gnomes and Other Stories from GISRUK 2017

Gorton Monastry, GISRUK 2017

The 2017 GIS Research UK (GISRUK) Conference took place last week in Manchester, and Pixalytics sponsored the Best Early-Career Researcher Prize.

I was looking forward to the event, but I nearly didn’t get there! I was planning to catch the train up from London on Wednesday. However, the trackside fire at Euston station put paid to that, as my train was cancelled. Instead I was at the station bright and early on Thursday morning.

The first presentation I saw was the inspiring keynote by Professor Andrew Hudson-Smith. He talked about ‘getting work out there and used’ and using the Internet of Things to create a ‘census of now’ i.e., rather than having census data a number of years out-of-date, collect it all of the time. Personally, I also enjoyed hearing about his Bluetooth gnomes in Queen Elizabeth Olympic Park, which talk to you about cyber security. A visit to his gnomes is definitely on my list for the next spare weekend in London!

I spent the rest of the afternoon in the Infrastructure stream of presentations where there were talks on spatially modelling the impact of hazards (such as flooding) on the National Grid network, human exposure to hydrocarbon pollution in Nigeria, deciding where to site, and what type of, renewable energy and investigating taxi journeys.

In the evening, the conference dinner was at ‘The Monastery’, also known as Gorton Monastery. Despite the name, it was actually a friary built by the Franciscan monks who travelled to Manchester in 1861 to serve the local Catholic community. It was one of the first churches to be completed by the Franciscans in England after the Reformation. It became derelict in the mid 1990’s and ended up on the World Monuments Fund Watch List of 100 Most Endangered Sites in the World. Since then it has been restored and is used as a spectacular community venue.

Friday started with the morning parallel sessions, and I picked ‘Visualisation’ followed by ‘Machine Learning’. Talks included ‘the Curse of Cartograms’ (and if you don’t know what these curses are, have a look here!), land-use mapping and tracking behaviour at music festivals using mobile phone generated data – which won the best spatial analysis paper. However, my favourite talk was given by Gary Priestnall on the projection augmented relief models, which use physical models of a location’s terrain that are then overlaid with imagery/videos shown using a projector. The effect was fantastic!

Our closing keynote, ‘The Great Age of Geography 2017’, was from Nick Crane, known to UK TV viewers as the ‘map man’. He reflected on the role of geographers throughout history and then into the future. He equated the breakthrough in printing, from wood blocks to copper plates that could be engraved in more detail and updated, to today’s transition from analogue to digital.

The conference finished with the awards. I was delighted to present Alyson Lloyd and James Cheshire with the Best Early-Career Researcher Prize for their presentation on ‘Challenges of Big Data for Social Science: Addressing Uncertainty in Loyalty Card Data’. Unfortunately, as it was on Wednesday afternoon, it wasn’t one I’d seen personally. However, I’ve downloaded the conference paper, available from here, and I’m look forward to reading it.

It was an excellent conference, and I was really enjoyed my time in Manchester. Looking forward to GISRUK 2018!

EO Applications and Visualisation

I’m concluding my trio of conference blogs by focussing on Earth Observation (EO) and visualisation.

Within the data visualization session at ESA’s Living Planet conference Planetary Visions Limited gave a great talk entitled ‘Presenting Data and Telling Stories’. They highlighted the importance of knowing the audience that you’re communicating with, particularly the difference between presenting data to the general public versus fellow scientists.

The key element of communication to remember is that it’s only complete when the recipient understands the message. Scientific figures are often presented using a colour palette, which is applying artificial colours to black and white images (the rainbow palette is shown below, going from low values being purple / dark blue to high values being red). These enables scientists to easily extract values and get a detailed view of the results. Fine for scientists who understand this principle, but for anyone who doesn’t they may not understand the data presented or even worse may draw incorrect conclusions.

Rainbow Colour Palette

Rainbow Colour Palette

To make data widely understood, it needs to be presented in a way that makes it immediately clear what is being shown. This means that sometimes you need to focus only on the overall message, and sacrifice elements of the detail that allow the extraction of values, differences and trends.

Infographics is the on-trend term for the visual representation of complex data in a chart or graphic, so it’s quickly understood. There’s recently been an explosion of software, and websites, offering to create infographics for you. However, infographics aren’t new. A long running example is the London Underground Map; it isn’t a precise map of the tunnels, but it gives everyone the information they need to use the underground.

The key to a good infographic, and other graphs and charts, is keeping it simple. Focus on the information that you want to convey, rather than graphical embellishments. Edward Tufte argued in ‘The Visual Display of Quantitative Information’ that graphics should be assessed in terms of the data-to-ink ratio, such that the data should be presented with the least amount of ink.

Look at your figures and ask yourself whether the axis, grid lines, legends, numbers, borders or any other of the fancy bits in PowerPoint add anything to the image; or do they make it more confusing and less understandable?
Next time you have present, don’t just pull out the presentation you gave to the other conference last month and think it will do. Think about who is going to be listening to you? Will they understand the data as you’ve presented it? If you don’t think they will change it!

Scientists need to think about visualisation of data, as well as the raw data, if it’s going to be understood by more than those who created it. Data becomes information when it’s presented in a context that makes is useful. Always turn your data into information; your audience will thank you!