1. Not Another Data Leak
What's that? Oh! It's leak data...got it...
Actually, it's flow data - the litres per second that pass through Distribution Management Areas (DMAs) across the region, covering homes, schools, businesses, etc. But it *could* help identify leaks. How much water passing through DMAs is actually being used rather than how much of it is caused by leaks on the network? Could analysing historical flow data reveal trends for days, months, seasons? If so, would a change in consistency point to a leak? The 'nightline' data - water flow during the night and early hours - is usually used to help find leaks as it is assumed that a lot of folk are asleep during the night. What events or factors can affect the nightline data?
2. In The Region Of...
We all love a bit of city-vs-city banter
We're sure Wakefield would love a chance to say that Leeds keeps wetting itself (or vice-versa!) so here's an opportunity to do just that - what are the regional differences for water consumption and leaks? In all seriousness, this kind of comparison can help manage the water network and find problems quicker based on what Yorkshire Water know about a region. For example, the water pressure in the main pipes does differ across Yorkshire due to the topography of the land. This creates different demands on the network depending on where you are. Which datasets could be combined to build a more complete picture of a place in relation to its water consumption? Where are the leaks most likely to develop? Will some areas use more water to cover seasonal events/work?
3. Define the what, why and how of leaks
They're not as simple as you might think
When you get a leak in a pipe at home, you can call out a plumber and (most of the time) it can be fixed quickly. Replacement parts are easy to come by and you might even get some advice about how to avoid the leak developing again. Now, imagine that process with much bigger pipes and higher water pressure. And those pipes are underneath buildings or roads. And it requires a team of plumbers. And the parts are huge...you get the picture. There are a number of different things that (literally) impact on water pipes so getting a better understanding of how leaks develop, what causes them, and how to assign resources so that leaks are tackled at challenging times of year. It will sound obvious but winter is always a busy time for repairs.
4. The Human Touch
Let's uncover the human stories behind the data
Humans are creatures of habit. We know that every time there is a bit of sunshine and warmth in the UK, we run to the nearest store to buy a fan (despite doing the same thing last year) and we buy as many disposable barbecues as we can carry. We know that snow = the end times, and panic buying of bread and milk. We know very little about our habits with water. Using other types of data - demographics, population density, employment, etc - can we identify patterns that will help Yorkshire Water understand their customers needs? Do shift workers tend to use more water at night or during the day? Do neighbourhoods that are, on average, 'younger' have different water consumption patterns to an 'older' neighbourhood? What happens during the school holidays - more water for paddling pools? What effect do religious celebrations have on water demand?
5. Data as Infrastructure
Make it solid now and build on it in the future
Yorkshire Water's aims to publish all of their operational data openly by 2020 is ambitious but if successful can provide a solid base on which to build other things. What challenges will they need to overcome? What could the current data releases help with?
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