When somebody has a heart attack, the first thing you do is make them comfortable. After calling an ambulance, you locate a defibrillator.
Finding a defibrillator can spell the difference between life and death. It’s essential they’re located in easy-to-reach places, and using open data can make sure that they’re positioned in areas where people are most at risk of heart attacks.
Last October, Trafford Innovation and Intelligence Lab helped the mayor of Trafford to decide where to place defibrillators around the city by analysing open data.
A group formed comprised of consultants in public health, a data specialist, a paramedic, and local organisations. Together they looked at open-data indicators that would help them to decide where to place 15 defibrillators: mortality rates, obesity levels, rates of cardiovascular disease, and levels of physical activity in the area.
Jamie Whyte, head of the Trafford Innovation and Intelligence Lab and a member of Trafford Council, said the group was able to help save lives by using purely open data to analyse the best places to locate the new defibrillators. They crowdmapped the locations of existing units, in GP surgeries, schools, and sports centres, drew up a list of places with no defibrillators, and merged the two datasets.
Nigel Shadbolt, the chairman of the Open Data Institute, says open data can be vital in life-threatening situations. He explains how Ushahidi, a data management system, gathers information from a crowd and transforms it into easy visualisations that can show what happened during an incident. It came to prominence during the 2013 Kenyan general elections, when it helped to expose killings during the campaign.
Ushahidi has since been used in emergency relief campaigns, including during the Nepal earthquake. It allows emergency servicesto make decisions based on facts rather than guesswork, something that’s especially important when resources are scarce.
Shadbolt explains how collecting the data relies on the power of the crowd. “There’s a basic information layer, which is then supplemented by people adding more data into it. For example over 48 hours 4000 volunteers worked in Kathmandu to map roads that had been destroyed during the earthquake.” This helped emergency services reach victims.
The most interesting thing with providing raw data, says Shadbolt, is that you provide the information and the apps “think” about it when a situation arises. “The whole genius of the web is that you don’t even know how the data you put up will be used. For this reason it’s best to collect more information than you think you might ever need.”
Emma Thwaites, a spokesperson for the Open Data Institute, explains that data layering is where open data can have the most impact. “That’s when you can really see where the black spots are. Overlay air pollution, crime stats, and fuse the data together, and you can see the likelihood of the most dangerous things. From this you can work out where to position your ambulances, or fire stations. Data helps you to find the epicentre.”
As well as benefiting the local community, open data can also be used to help individuals. Samuel Diserens is moving from Camberwell in south east London to Barnes, in west London. The move is prompted partly by the high crime stats in Lambeth. “I used data from Police.uk to research somewhere where gun crime, drug dealing, and stabbings weren’t so common, and by sifting through the raw data happened upon Barnes. He found out that in just one month 186 crimes were reported in Camberwell, whereas in Barnes there were just 72.
Amy Jones has used open data to keep her as safe as possible. She’s a cyclist who regularly relies on accident data to avoid blackspots, and she credits open data provided by TfL for helping her to become aware of the worst spots for cycling deaths. The data showed every bike accident that happened in London between August 2010 and July 2011. From this she learned that the junction just before Blackfriars Bridge was the most dangerous location on her route, and that most bike accidents occurred at 8am.
Jones decided to make her commute two minutes longer by taking side streets, and left home slightly earlier each morning to avoid the big crush of cyclists, buses, and cars. “Changing my route has potentially saved my life. I breathe in less pollution from main roads and I’m less at risk from crashing, thanks to the the data provided by TfL.”
Whyte is currently working on a project that targets areas in Trafford that have a low uptake of cervical cancer smear tests. He’s using a mixture of open and closed data (from GPs and open census data) and as a result has seen a 10% uptake of screening. He says: “[The] public sector needs to use open data – it’s own and national stuff – to help inform how it delivers services. And if in doing that it can generate more data and release that as open data then great. I don’t know whether this will save lives: I wouldn’t want to make that kind of bold claim, but it’s definitely a good thing!”
Shadbolt, is certain that open data can save lives. “Absolutely it can, and in ways we don’t recognise all the time. All the accident data, traffic blackspots, emergency situations? That’s us using data to save lives.”
This article first appeared on The Guardian.
