But there’s more: combined with other datasets, it can answer a wide variety of questions, be put to a wide variety of uses across many industries.
Most recently, we worked on a version for the Dolphin Square Foundation. Their remit requires them to find properties within a specific travel time from the centre of London, and with the best net yield—a perfect challenge for Mapumental. You can read what we did here.
You may see some similarities with our Mapumental Property, which combines house prices with transit time, so property hunters can see what’s available both within their budget and within a tolerable commute of their workplace.
We’ve used Mapumental for many a time-based travel conundrum, like our project with the Fire Protection Agency that drew on fire engine response times to calculate risk-based insurance premiums for any given postcode. Or the work we did for the Welsh Government, plotting accessibility of schools.
Like we said, Mapumental is flexible enough to work in all sorts of fields, for all sorts of purposes. Take a look at our Dolphin Square case study to find out more about its latest incarnation.
According to a postscript on that story, TfL have since commented:
This map was produced for engineering works planning and wasn’t designed for customer use, however we are happy to make any maps available which help our customers to travel in London. This map will therefore be added to our website.
Great result. We hope that thanks to Buzzfeed’s viral spread, from today, plenty more people understand the potential of FOI to change things for the benefit of many.
Not many people realise that we fund a proportion of our charitable work by carrying our commercial development and consultancy work for a wide range of clients.
Last year, we scoped, developed and delivered a real variety of digital tools and projects. Some of the projects were surprising. Some of them made us gnash our teeth, a bit, as we grappled with new problems. But all of them (and call us geeks if you like) got us very excited.
Here are just twelve of our personal high points from last year. If you have a project that you think we might be able to help you with in 2015, we’d love to hear from you!
1. We Changed the Way in Which Parliament Does Digital
This time last year, a small team from mySociety was poring over analytics, interview content and assorted evidence from Parliament projects dating back last 2-3 years, to help us put together a simple set of recommendations to conclude our review.
11 months later, Parliament have announced their first Head of Digital, fulfilling one of our key recommendations.
2. We helped the MAS and the FCA protect financial consumers
We built the Money Advice Service’s (MAS) first responsive web application, the Car Cost Calculator.
This tool takes one simple thing you know (the car you wish to buy) and tells you roughly how much it’ll cost to run that car against any others you might be interested in. It has been one of MAS’ most successful online tools in terms of traffic and conversion.
We also built the Financial Conduct Authority’s Scam Smart tool, aiming to prevent financial scams.
This tool helps users considering a financial investment to check a potential investment. Users enter information about the type of investment, how they heard about it and the details of the company offering it to them and get back tailored guidance and suggested next steps to help them ensure the investment is bona fide.
3. We Gave Power to the People of Panama (soon)
Working with the The National Authority for Transparency & Access to Information (ANTAI) and the Foreign & Commonwealth Office (FCO), we set up our first government-backed instance of our Freedom of Information platform, Alaveteli, in Panama.
This project will ensure that Panama’s FOI legislation is promoted and used, but it will also shine a light on ANTAI, who are responsible for ensuring ministries and organisations publish their information, and handling case appeals.
4. We Mapped All the Public Services in Wales
After we extended the Mapumental API to produce data output suitable for GIS (geographical information systems), the Welsh Government were able to map public services in Wales for their Index of Multiple Deprivation calculations.
Over the course of the year they have calculated travel times for over seventy thousand points of interest.
5. We Launched a New Organisation in Four Weeks
Simply Secure approached us in dire need of a brand, an identity and a website to accompany the launch of their new organisation to help the world build user-friendly security tools and technologies.
Cue four weeks of very intense work for mySociety’s designer, supported by members of the commercial team. And we did it.
6. We Printed Stuff BIG (and found people jobs)
Xerox will be using these with the DWP to help job seekers find work that is within reach by public transport. As a byproduct, Mapumental now handles high-fidelity print based outputs: get in touch if that is of interest.
7. We Opened Up Planning Applications
With Hampshire County Council we had the opportunity to build a new application to help assist members of the public and business better understand what was happening around them. For us, it was also the first application in which we worked closely with a provider of a linked data store, in this case Swirrl.
When Open Planning goes live, it will look to help improve social engagement and the economy of Hampshire through better understanding and transparency of planning data.
8. We Proved (Again) That FixMyStreet Isn’t All About Potholes
We launched Collideoscope on October the 7th with our first sponsor—Barts Charity, with the aim of generating data both on incidents involving cycles, and near misses.
9. We Helped Launch a Film
We built a tool for the British Museum, to go alongside the general release of Vikings Live. The Norse Names project brought a sense of context and personalisation to a dataset gathered by the University of Nottingham.
10. We Made Data More Exciting
This year, they asked us to build something similar for bus users. We’re entering the final week of development now, and the finished product should be launched in March.
The main aim of this site? To take data that could be considered pretty dry, and make it a lot more engaging.
11. We Fixed Yet More Potholes
That means that residents of those places can now make their reports direct from their council’s website, or via FixMyStreet, and either way they’ll have all the benefits of FixMyStreet’s smooth report-making interface.
12. We Showed Parliament the Way
And so, we end where we began. While Parliament were busy interviewing candidates for their new ‘Head of Digital’ position, we were commissioned to demonstrate what Hansard might look like were a platform like SayIt used instead of the largely print-based publishing mechanisms used today.
The result was shared internally. While SayIt may not be the end solution for Parliament, it’s great to have had some input into what that solution might be.
And in 2015…?
Got a project that you’d like us to be involved in?
So we wanted to build an app for FixMyStreet. Easy: we just had to make a cut-down version of the website, right?
Hmm, not quite.
Now he explains a little more about what informed the decisions he made during the apps’ development.
Moving the map, not the pin
When you use the desktop version of FixMyStreet, the first thing it asks for is your location, and there’s a good reason for that. It’s such a good reason that it needed to apply to the app as well.
On the desktop site we ask you to input your postcode or street name. With a mobile app, it’s much more likely that you’ll be reporting a problem that’s right in front of you, so we can usually skip that step and show you a map of your current location.
However, while the accuracy of geolocation technology is pretty good, it’s not perfect, so we wanted to let users fine-tune the location.
On the website you click on the map to drop a pin where the problem is, but we’ve found this isn’t the best solution on a small screen. Fingers are big and the end of a pin is small so it can take several clicks to correctly position the pin.
We quickly realised that having a central static crosshair, and moving the map to the location was a much easier and more accurate way to set a location.
Sending reports made offline
As we explained in the previous post, one of the benefits of the apps over the mobile site is that you can make reports even if you have no phone coverage. The app stores all the details until you get back within range and you’re ready to send it off.
One decision we made, which might seem initially puzzling, is that these offline reports don’t automatically get sent off to the council once you’re back within range of a phone or wifi signal.
There are two linked reasons for this, and they’re both related to the fact that FixMyStreet lets you report a problem even if you don’t know who to send it to.
Simply, before we can work out who to send the report to, we need to know exactly where you are – and that you are within FixMyStreet’s area of coverage (ie, within the UK).
Your location also dictates the categories that we show you. Each council has its own categories, and in areas covered by two tiers of government, each council will deal with different types of report. So for example, your county council might deal with potholes, while your district council handles dog fouling.
Once you’re back online we can check that the location is one we can accept a report about, and then fetch the list of categories for you to pick from.
In effect, this delay is also a second chance for you to check your report before you send it off, although that was never the reason for the decision!
The constant map
We initially designed it with the map only appearing when you needed it, but having the map underlying the reporting process provides a nice bit of continuity with the website, and seemed to make the app cohere better too. So, while there’s no particular reason for it to be there, we made the decision to keep things uniform.
If anything else about the app has got you wondering, do feel free to leave a comment below!
A commission from the Welsh Government has resulted in new functionality for Mapumental, which now has the capability to display multiple points and to produce RAW data compatible with GIS applications. Here’s how it happened.
How accessible is your nearest school, post office, or GP’s surgery? In Wales, that’s not always a simple question: the country’s mountainous landscapes, rural populations, and sometimes infrequent bus services can mean that those without cars are rather cut off from public service provision.
But of course, like any other authority, the Welsh Government has an obligation to quantify just how accessible their services are.
For many years, they have done so using a number of different methods. Some of these involve literally millions of point to point calculations – so, naturally, when Bill Oates, Head of Geography & Technology, Knowledge Services at the Welsh Government, approached Mapumental, he was keen to discover whether we could simplify things.
We were keen to try it, too – plotting multiple points would add a whole new slew of possibilities to Mapumental. Previously, Mapumental has been all about travel from a single point, and this functionality would bring new applications across all kinds of industries and users.
There’s only one way to find out
The sensible way forward was to pick a single service and see what we could do. One of the government’s open data sets showed positioning of all the secondary schools in the country, and would give us a very good indication of how manageable the task would be across all other provisions.
So we set ourselves this aim: to display the shortest transit time to get to any secondary school in Wales, from any point in that country.
This project was not like the map we made for the Fire Protection Association last year, with its postcode input and interactive sliders. It bore more relation to our static maps, but with the additional dimension that the single map would have multiple points plotted on it. Each point would display its own associated journey times, and where travel to one school was quicker than to another, it would have to override the data of the school that was further away.
And here’s the (very pretty) result
Transit times by public transport to secondary schools in Wales, with an arrival time of 9:00am.
Time bands are in 15-minute increments, with red areas being those where schools are accessible within a 15-minute journey (the centres of the red dots therefore also represent the positions of the schools).
Purple areas are those where journey time is between 1.75 and 2 hours, and the colours in between run in the order you see bottom right of the map. White areas (much of which are mountainous and sparsely-populated) are outside the two-hour transit time.
But there’s more – data for GIS
Plotting all the schools on a single map required quite a bit of modification to Mapumental, but there was another important part of the project that also had to be worked on, if the output was to meet all the needs of the Welsh Government.
They needed to be able to export the raw transit time data to their own GIS tools – the tools that they use to feed into official statistics. This allows the transit time data to be combined with other datasets, such as population density, for in-depth analysis.
We added a feature which allows Mapumental to produce what is known as a ‘raster grid’ output – basically, an enormous matrix that gives every pixel on the map a travel time value. To do this, we used the open source GRASS format.
Bill Oates is keen to see where this project can go:
“I’m really excited at the prospect of combining the power of Mapumental with our open data, and fully understanding how accessible Welsh public services are by public transport.”
To him, the benefits are clear:
“Mapumental’s approach is significantly quicker than our current methods, so this work will help save us time as well as providing a more engaging output.
“We hope that future work with mySociety will give us a sustainable approach to calculating the accessibility of local shops, hospitals, post offices and other services on an ongoing basis to help ensure that we’re meeting the needs of our citizens.”
We’re looking to build on our success, and offer this service to others – initially on request but via our API as soon as we can. We’ll keep you posted as to our progress.
You can see multiple-point mapping in action, on our Mapumental Property project – now the tool allows house-hunters to take more than one person’s commute into consideration when choosing where to live.
Who might use Mapumental?
Now that Mapumental can plot transit times from multiple points, and provide RAW data for GIS applications, we have great potential for use by anyone interested in travel and accessibility. That could be in central and local government strategy, town planning, architectural consultancy, transport provision, large enterprises looking to save on parking, or start-ups in the green transport space…to name but a few.
Could Mapumental help you with your mapping needs? If so, please do drop us a line at email@example.com.
Photo of Welsh school bus (bws ysgol) by Aqwis (CC)
Mapumental can turn vast datasets into visual tools that everyone understands. Faced with highly complex, yet crucial data from the Fire Protection Association, we had a chance to really put our technology through its paces.
Just how quickly could fire engines reach a given postcode in case of a fire? It’s a question that’s pivotal to decisions made by both the emergency services and the insurance industry.
But previously, it has been a challenge to present the data simply, because it involves so many variables.
Every region has its own factors, each of which will impact on fire engine response time. The number of vehicles at each station, the hours during which the station is manned, and the response policy of each individual fire authority will all play a part – and that’s before you even consider how geography might affect things.
Dr. Jim Glockling is Technical Director at the Fire Protection Association and Head of the Risk Insight, Strategy and Control Authority (RISCAuthority), an organisation for the advancement of risk management within the fire and security sectors. Jim approached mySociety with this question: how could we map this crucial, yet complicated data in a way that could be understood by RISCAuthority members at a glance?
It was clearly a job for Mapumental. Our transit-time mapping software was originally built to visualise public transport journey times, but its beauty is that ‘layers’ of data can be swapped out, allowing it to be used for all kinds of purposes.
Assessing a property or postcode
And here’s the result of our pilot project. The maps on the right answer the following questions (click each image to see it at full size):
How quickly could 4 fire engines get to AL10 0XR ?
How does that change if the severity of the fire just requires one fire engine?
A user inputs a postcode, and can assess exactly how quickly a fire could be tackled in that area. The different levels of severity are measured by how many response vehicles are required, and changes in this number are immediately reflected on the map.
Assessing the general area
Which areas can four fire engines get to within 9 minutes 30 seconds at midday on a Saturday?
It’s also possible to assess the region’s overall response capability, without inputting a postcode. The user sets severity levels (number of fire engines, or High Volume Pumping or Aerial Appliance (ladder) is needed), the time and day of the week.
Where can an aerial appliance get to within 15 minutes at 2am on a weekday?
The FPA tool immediately highlights the areas that are accessible within the chosen parameters, drawing on the underlying data of journey times and information such as vehicle numbers and hours of operation for each individual fire station in the region.
With RISCAuthority, we tested the concept using data from one fire authority – Hertfordshire. mySociety’s task was to create a usable, elegant web interface that was as simple as possible to use, while still giving insurers the key data they needed.
The project called on everything we knew about clean design, usability and data structures. A key part of what makes Mapumental’s data visualisation so intuitive are its sliders: this enables the user to quickly explore variables on a map.
A tool with purpose
Dr Glockling explains: “Whilst not necessarily used as a component of insurance pricing, this information helps insurers administer risk control and fire protection advice to their customers in the context of what the Fire and Rescue Services will be able to achieve on their behalf.”
The response time is just one factor that insurance surveyors will take into account when they are assessing a building. “Where response and arrival times are not coherent with protecting the viability of the business in the event of fire, additional forms of in-built protection and control might be recommended, such as the installation of sprinkler systems.”
“In the longer term it is hoped such information will impact beneficially on the annual cost of fire in the UK.”
The pilot tool was well received by the FPA community, and the plan is now to work with RISCAuthority to roll it out to more fire authorities shortly, and then nationwide.
Dr Glockling explains the pilot study helped them to understand two factors:
Would they get buy-in from both insurers and Fire and Rescue services on the viability and usefulness of the project?
Was it possible to present such a massive amount of data in a format that was readily palatable to the intended audience?
He says, “Mapumental’s team displayed an immediate understanding of our requirement. Delivery was to time and the result has perfectly satisfied the de-risking ambition. The working relationships were very good throughout and we intend now to extend the pilot to full UK rollout.”
During this phase, we will be inputting still more detail to the data, including information on the types of fire engine available to each region, and the plotting of fire stations on the map.
The tool will be a valuable resource for the FPA and the insurance industry, and we really look forward to the roll-out later this year.
Mapumental specialises in visualising complex geographic data sets on intuitive, easy to use map tools. If you have a data visualisation project that will benefit from Mapumental, just get in touch. Or read more about mySociety’s data visualisation services here.
Photo by William Murphy (CC)
If you’re searching for a new home, give Mapumental Property a try. lt narrows property results down, only showing you houses that fall within a decent commute time from the places you visit regularly – like work, school, or the shops. Here, have a go – it’s fun.
Irritation is the mother of invention
Several years ago, some of our colleagues were looking for a house to rent.
They weren’t set on a particular town. There were two important factors: that it was within a reasonable commute from central London, where they frequently attended meetings; and that the rent was affordable.
Faced with these requirements, most of us would sift through property sites and cross-reference the listings manually with public transport information. It’s rather time-consuming, and slightly irritating, but hey-ho, it has to be done.
But mySociety is in the business of building useful web tools, so when something irritates us like this, we look to see if we can solve the problem through the magic of code. In a stroke of good timing, it was at just around this time that the Department for Transport approached us to ask us to work with their public transport data – and Mapumental was conceived.
The key was to combine Ordnance Survey postcodes with the DfT’s data about journey times, NPTDR (National Public Transport Data Repository). This data set takes a ‘snapshot’ of every public transport journey in Great Britain for a selected week in October each year.
Sounds simple? The process was not without its challenges. Prime among them was the problem of displaying map tiles, plus the vast quantities of transport data, within a reasonable amount of time, no matter which postcode or zoom level the user chose. As we know, a ‘reasonable amount of time’ for a page to load is a metric which is forever shrinking.
By 2006, we had created Mapumental’s first iteration. Users could input a postcode and see all areas of the country that could be reached by public transport, divided into coloured travel-time bands. In 2009, Francis Irving, the mySociety coder behind Mapumental’s early endeavours, explained the technology he’d used. It was Flash-dependent, and a few years later, developer Duncan wrote about some of the technical hurdles he overcame replacing the Flash elements, in view of the rise of the iPhone, which famously doesn’t ‘do’ Flash.
Hoorah! Now our colleagues could type in a central London postcode and see everywhere that fell within a 40-minute journey from there. It wasn’t long before we added median house price data, too.
Beauty is in the eye of the crowd
We even added a ‘scenicness’ rating: if the beauty of your surroundings was important to you, you could rule out anywhere below a certain level of attractiveness.
How did we assess how scenic every area in the UK is? By crowdsourcing the information – our ScenicOrNot website displays a random photograph from every square mile of the British isles, inviting people to rate them. It is surprisingly compulsive.
A showcase tool
Mapumental may have been born from our own needs, but we knew from the beginning that it would have wider applications. It has always been the sort of project that got people excited, once they saw it in action.
We wanted to show how elegantly Mapumental can handle all kinds of data, starting with houses for sale and rent – so we developed Mapumental Property. It’s not intended as a serious competitor to the giant property websites out there. Rather, it’s an all-singing, all-dancing demonstration of Mapumental’s strengths.
In this case, the data is from the property website Zoopla, and you can narrow it down to show rental or sales property within your chosen price bands and commute distances. You can even add multiple destination points, so that households of two or more people can find their optimum location.
But Mapumental is not just about property: swap out that Zoopla layer, and you could put in anything else you can imagine – hospital locations, supermarkets, schools, job vacancies… you name it.
The beauty of Mapumental is that now we’ve done the really hard part, incorporating new data layers is relatively simple. Recent work for the Fire Protection Association and the Welsh Government, among others, has shown its versatility.
Now how about you?
We believe that Mapumental’s possibilities are pretty much endless. Have you got an unloved, difficult-to-navigate dataset that Mapumental could breathe new life into? Or would your stakeholders benefit from being able to see your data displayed on a map? Let us know.
I am Duncan Parkes, a developer for mySociety, a non-profit full of web geeks. One of the things we try to do well here is to take complicated data and turn it into really usable tools – tools which are attractive to people who aren’t web (or data) geeks.
For some considerable time I’ve been working on Mapumental – a project that is about turning public transport timetable data into pretty, interactive maps featuring isochrones, shapes that show people where they can live if they want to have a commute of a particular time. You can play with the new version we just launched here. That particular map shows the commuting options to where the Queen lives. Slide the slider for full effect.
There are a couple of hard problems that need solving if you want to build a service with an interactive journey times overlay like this. You need to be able to calculate a *huge* number of journeys extremely quickly, and you need to be able to make custom map layers so that it all looks nice. But what I think might be most interesting for you is the way in which the contours get rendered on top of the maps.
It all started about three years ago, when the first version of the app – co-developed with the geniuses at Stamen – used Flash/Flex to draw contours on the maps, and to let people play with them. You can still play with a couple of versions of that technology from way back in 2007, that is, unless you’re using an iPad or iPhone, which of course don’t do Flash.
What was going on inside this Flash app was as follows. We needed to show the user any one of hundreds of different combinations of journey times (5 minutes, 12 minutes, 56 minutes, etc) depending on where they set the slider. Sending each one from the server as a tiled map overlay would be dead slow. Even Google – who have chosen to send new tiles each time – end up with a service which is surprisingly slow (try choosing a different time on this map).
With some help from Stamen, we decided that the way of making it possible to show many different contours very quickly was send the client just one set of tiles, where each tile contained all the data for a variety of journey times. What does that mean? Simple: each colour in the tile represented a different number of minutes travelling on the map. So a batch of pixels that are colour X, all show places that are 15 minutes from the centre of the map.
So, in this old Flash system, when you slide the slider along, the Flash app makes some of the coloured pixels opaque, and the others transparent. It was, in short, a form of colour cycling, familiar to lovers of 8 and 16 bit computer games.
However, from about 2010 onwards, the march of iOS spelt the end of Flash. And that meant that we couldn’t launch a shiny new site based on this technology, as lovely as it was. We had to work out some approach that would use modern web standards instead.
The Death of Flash Makes Life Difficult – for a while
How do we replicate the experience of dragging a slider and seeing the map change like in the original Mapumental demo, but without Flash? One of the things that made the original Mapumental nice to use was how smooth the image changes were when you dragged the slider. Speed really matters to create that sort of organic effect that makes the demo so mesmerising.
So as we started to tackle the question “How do we make this work in a post-Flash world?”. And the first thought was “Let’s do away with those map tiles, filled with all that journey time data!”. After all – why send any tiles to a modern browser, if it can just render nice shapes on the fly?
So we had a go. Several goes. At first we tried rendering SVG circles around each public transport stop – but that was too slow, particularly when zoomed out. Then we tried rendering circles in Canvas, and whilst that was OK in sparsely populated places it sucked in the cities, where people would actually want to use it.
Back to Colour Cycling – Using Web Standards
So, I had a bit of a look at the waterfall. It seems to work by holding in memory a structure which has all the pixels which change and all the colours they should change to and when. This works beautifully for the waterfall picture, but only a limited number of the pixels in that image actually change colour, and the image is quite small. For a full screen web browser with a big map in, this didn’t seem promising, although I’d love to see someone try.
Unfortunately, there is no way to change the palette of an image that you’ve put on the canvas. In fact, there’s no way to change the palette of an HTML img element: all you can do is assign it a new src attribute.
But this gets back to the original problem – we don’t want to download new mapping for every different position on the time slider. We definitely can’t afford to have the client downloading a new image source for every tile whenever the slider is moved, so we had to find a way to make that src at the client end and get that into the src attribute.
The Breakthrough – Data URIs and Base64 encoding
So we started trying data URIs. For those of you not familiar, these allow you to put a whole object into your HTML or CSS, encoded in Base64. They’re commonly used to prevent pages having to make extra downloads for things like tiny icons.
My new plan was that the client, having downloaded each palette-based image, would make a Base64 encoded version of it, which it could then use to build a version with the right palette and assign this as a data URI of the tile.
So in summary, what we built does this:
- The server calculates the journey times and renders them to palette-based tiles.
- It sends these to the client, encoded in Base64, and with the initial bits up to the palette and transparency chunks removed.
- At the client end, we have a pre-prepared array of 255 ‘starts’ of PNGs that we combine with the later parts of the ’tiles’ from the tile server to make data URIs.
- When you drag the slider it combines the appropriate ‘start’ of a PNG with the bulk of the tile that has been downloaded from the server, and assigns that to the src attribute of the tile.
And that’s how the nice overlays on Mapumental work. But as so often in coding, the really interesting devil is in the detail – read on if you’re interested.
Diving into Base64 and the PNG file format – The Gnarly Bits
So – why are there 255 of these ‘starts’ of these PNGs, and what do I mean by a ‘start’ anyway?
PNG files are divided up into an 8 byte signature (the same for every PNG file) and a number of chunks, where each chunk consists of 4 bytes to tell you its length, 4 bytes of its name, some data, and 4 bytes of cyclic redundancy check. In this case, what I call a ‘start’ of a PNG is the 8 byte signature, the 25 byte of the IHDR chunk, and the PLTE (palette) and tRNS (transparency) chunks. The PLTE chunk has 12 bytes of overhead and 3 bytes per colour, and the tRNS chunk has 12 bytes of overhead and 1 byte per colour.
Base64 encoding is a way of representing binary data in text so that it can be used in places where you would normally expect text – like URIs. Without going into too much detail, it turns groups of 3 bytes of binary gumpf into 4 bytes of normal ASCII text without control characters in it, which can then be put into a URI.
Why do we have 255 colours, rather than the maximum 256 which are available in a palette? Because we need the break between the end of the tRNS chunk and the start of the IDAT chunk in the PNG file to align with a break between groups of three bytes in the Base64 encoded image. We need the length of these starts to be a multiple of 3 bytes in the original PNG format, which translates into a multiple of 4 bytes in the Base64 encoded version, so we can cut and shut the images without corruption.
Which just goes to show that even though web GIS technologies may feel like they are approaching a zenith of high level abstraction, there’s still some really gnarly work to be done to get the best out of current browsers.
However, we’ve never made public a simple, free, useful version of our slidy-swooshy Mapumental journey times technology. Until today.
Today we pull the wraps off Mapumental Property , a house-hunting service covering England, Scotland and Wales, designed to help you work out where you might live if you want a public transport commute of a particular maximum duration. Have a go, and we guarantee you’ll find it an oddly compelling experience.
We think it’s a genuinely useful tool – especially since unlike some of the other players in this space, we’ve got all the different kinds of public transport, right across the whole of Great Britain. We hope that some of you will find it helpful when deciding where to live.
However, this launch doesn’t mean mySociety is bent on taking over the property websites sector. Mapumental Property isn’t a challenger to the likes of Rightmove, it’s a calling card – an advertisement for our skills – which we hope will help mySociety to attract people and organisations who want beautiful, useful web tools built for them.
In particular we’d like people interested in Mapumental to note that:
- We like to build attractive, usable web tools for clients of all kinds.
- We know how to use complex data to make simple, lovely things.
- We can do some mapping technology that others haven’t worked out yet.
I’d like to thank quite a few people for helping with this launch. Duncan Parkes was the lead developer, Matthew Somerville ably assisted. Jedidiah Broadbent did the design. The idea originally came from the late Chris Lightfoot, and me, Tom Steinberg. Francis Irving built the first version, and Stamen came up with the awesome idea of using sliders in the first place (and built some early tech). Kristina Glushkova worked on business development, and Zoopla’s API provides the property data. I’m also grateful to Ed Parsons of Google for very kindly giving us a hat tip when they built some technology that was inspired by Mapumental. Thanks to everyone – this has been a long time coming.
We’ll follow up soon with a post about the technology – and in particular how we got away from using Flash. It has been an interesting journey.
When you report a problem on FixMyStreet.com, the site displays a map for you to click on to indicate its exact location. Of course, you can zoom in and out of that map, but when it is first displayed, FixMyStreet needs to use an initial ‘default’ zoom level. Ideally, this is a zoom level that reduces the number of clicks required before a user can pinpoint the location of their problem.
And here’s where we encounter a tricky problem. The world is a varied place – some towns are very dense with buildings and streets crammed close together. In these areas you need to default to a zoom that’s quite ‘close in’, otherwise it can be hard to locate your problem.
But out in the countryside, we have the opposite problem. You can have huge areas where there’s nothing but blank fields or moorlands. If the default map zoom is ‘close in’ here then users are likely to see a big map full of nothingness, or maybe just a single stretch of unidentifiable road.
So, what is to be done?
The answer is this – every time you search for a location in FixMyStreet the website does a check to see whether the location you typed is in an area where a lot of people live, or very few people live.
mySociety has been storing this population density data in a webservice which we call Gaze. If the area you searched for is in a densely populated area we assume that it must be an urban location, and the map starts with a helpfully zoomed-in map. But if you’re in a sparsely populated area then it’s probably rural, so FixMyStreet starts zoomed out, making it easier to get an overview of the whole area.
Where do we get the data from? Our late colleague Chris discusses this in a blog post from 2005 — the short answer is NASA SEDAC and LandScan. It’s an interesting example of how unexpected things can happen when data is made public — if population density wasn’t available to us, we wouldn’t have been able to put this small but clever detail into FixMyStreet’s interface.