The hacker community came to MediaCity for the Greater Manchester Big Data Dive on Tues 22nd July 2014. Coders, data monkeys and other techie enthusiasts gathered to respond to social challenges set for them.

Our project asked a big data team to paint an alternative data portrait of Ordsall (the Salford district where we are researching cultural activities).  Policy direction and language about the area tend towards identifying problems and issues (see the Ordsall Ward Profile) rather than looking at the good and interesting activities going on. Our challenge at the event therefore asked participants to:

  • Present an ‘objective’ portrait of statistics
  • Characterise the area in a way that challenges stereotypes (about demography, built environment)
  • Frame ‘absences’ (certain types of provision against national averages etc)

Here was my presentation for this event: bigdata_surf

The results

Our team came second!  What a great result. We should have come first really 😉 The data helped us:

We challenged perceptions of crime in Ordsall by creating a map of hotspots across the city region (see below).

burglarieshotspots

Hotspots in Burglaries data for Manchester city region, 2000-2014. Note how parts of Manchester are white hot with crime while Ordsall is darker with only a few pale patches.

violentcrimehotspots

Hotspots in Violent Crime data for Manchester city region, 2000-2014. Again, note how parts of Manchester are white hot with crime while Ordsall is darker with only a few pale patches.

caraccidents

Car accidents near Ordsall Park area, 2000-2014. Note how residents within ‘the triangle’ are trapped on all sides by dangerous roads.

caraccidentschapelst02-13

Hotspots of car accidents in Ordsall area, 2002-2013. Note how Chapel St is red with accidents.

caraccidentschapelst11-13

Hotspots of car accidents in Ordsall area, 2011-2013 (after traffic calming measures). Note the difference between Chapel St before and after traffic calming.

tweets

Tracking positive and negative tweets about Ordsall in Twitter, 2014. Note that 60% of tweets are positive. The negative ones were complaining about litter and graffiti.

Thanks to the Team5 for making it happen. We met for the first time that day and yet worked together really well. 🙂 While we all walked away with Amazon vouchers for coming 2nd, the real prize was learning about what was possible to do with data.

If just one day with open data helped us learn a lot about the area, what would regular and unrestricted access to the data and a talented techie team help us do?

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