I knew there was a core of London OSMers who were deciding to go to SOTMEU, and not to Denver. I felt it might be important to be in Denver as a representative, to meet, explain, and be an ambassador for the heart and soul of OpenStreetMap. The “OpenStreetMap way” as I see it. This is what I tried to do with my talk: “Blossoms, weeds and blades of grass: Growing the map”

The following is all the slides and a transcript of roughly what I said (or intended to say) It’s a bit of a whopper. Sorry if your RSS reader just blew a fuse. Alternatively you can watch this as a video showing slides and good quality audio, or a live action video from the front (but not so good audio). You can also see the slides on slideshare, download for OpenOffice, or powerpoint (32 MB).

Slide 1

I’m Harry and I’m from England… and I thought I’d compare OpenStreetMap to an english country garden.

It sort of blossoms with a wondrous variety of shades and colours. I’ll show you what I mean.

Photo CC BY-SA 2.0 Katy Walters: http://www.geograph.org.uk/photo/231339

Slide 2

As we started the map in the beginning…

http://wiki.openstreetmap.org/wiki/London_mapping_party_Jan_2007

Slide 3

…it was like crocuses pushing up their heads in the early spring.

Photo: Frühlingsblumen Krokus by Benjamin Gimmel, CCBYSA 2 etc on wikimedia commons: http://commons.wikimedia.org/wiki/File:Fr%C3%BChlingsblumen_Krokus.jpg

Slide 4

Somebody mapped the whole of Cambridge…

http://wiki.openstreetmap.org/wiki/File:Cambridge-2007-01-18.jpg

Slide 5

…the towering foxgloves of Cambridge

Photo: CC BY 2.0 psd on flickr: http://flic.kr/p/2uUoQ

Slide 6

All of Hull was mapped by one person in glorious detail…

http://osm.org/go/evq1M0z

Slide 7

…blossoming like beautiful marigolds

Photo CC BY-SA 2.0 mariosp on flickr: http://flic.kr/p/8A1DsY

Slide 8

The collaborative mapping of Birmingham…

http://osm.org/go/euzMLWEF–

Slide 9

..is like a bunch of forget-me-nots

Photo GFDL/CCBYSA3 Quadell on wikimedia commons: http://commons.wikimedia.org/wiki/File:Wald_Vergissmeinnicht.jpg

Slide 10

Sometimes I like to imagine I’m managing to keep a watchful eye on the map, and seeing how it develops worldwide.

This is nonsense, because the map is big, and the community of mappers is big. I really love it when I look around the map and come across things which surprise me.

Image from the flyer by Frederik Ramm: http://svn.openstreetmap.org/misc/pr_material/english_flyer_2010_10/marble_new_shadow.png

Slide 11

A couple of weeks ago I was just casually panning around somewhere in South England and I came across this glorious patch of detailed countryside mapping.

http://osm.org/go/eui0@lO

Slide 12

And what’s this pink thing with circular footpaths around it? I dont know. I have never been there! It’s a wonderful and surprising patch of detail to encounter. Somebody clearly feels passionate about the map of this area.

http://osm.org/go/eui1hOwQ–

Slide 13

So these blossoms appear by surprise. Perhaps it’s more like blossoms in the desert, appearing from barren desert floor, when the conditions are right.

Photo CC BY 2.0 Slideshow Bruce on flickr: http://flic.kr/p/7YGuns

Slide 14

Or like splats of ink

Image by Kamikaze Stoat CC BY 2.0 on flickr http://flic.kr/p/rMHgf

Slide 15

….or perhaps like bombs dropping. But mappers dont drop bombs of destruction, they’re dropping map bombs. An explosion leaving behind a circular areas of map coverage near where they live or work.

I think the way the community builds the map is a glorious and fascinating thing to behold, and utterly unique to OpenStreetMap.

Slide 16

We see a similar thing within an area like London, where we have a backdrop of "complete" coverage in terms of having all the roads and basic features in place, but now we get these patches of mega-detail blossoming with every building drawn in., and lots of POI detail added.

This is all good fun, and part of the same wonderful blossoming of map detail, but I am going to come back to talk about problems particularly related this kind of example, a little later on.

http://osm.org/go/euum1g1E–

Slide 17

I want to compare that situation with another type of map growth, which is more relevant to the U.S. Here we see a lot of data imports. In particular we see TIGER data across the whole US which has really shaped and characterised OpenStreetMap here ever since it was imported

http://wiki.openstreetmap.org/wiki/TIGER

Slide 18

TIGER gives us even coverage. Perhaps like a nice flat garden lawn.

Photo CC BY-SA 2.0 AdamKR on flickr http://flic.kr/p/7SkGUP

Slide 19

And then there’s more detailed imports in some areas of the U.S. This Is MassGIS

http://osm.org/go/ZfI4vQRE–

http://wiki.openstreetmap.org/wiki/MassGIS

Slide 20

Perhaps more like a field of corn. There’s even coverage but none of the exciting blossoms of coverage coming from passionate local mappers

Photo CC BY-SA 2.0 Lilli2de on flickr http://flic.kr/p/8jGXZC

Slide 21

It would be unfair to say there are no blossoms in the U.S. In fact here in Denver we see some great details appearing, and as I keep an eye progress here I’m seeing more and more of this kind of mapping starting to pick up in the U.S.

http://osm.org/go/T2JiaQpF-

Slide 22

Before TIGER was imported there really wasn’t very much data in the U.S. and the community wasn’t progressing well, but there was always a lot of talk about the TIGER data, and perhaps the community was in some sense waiting for TIGER. Perhaps the proactive tech-savvy folks who we need as community leaders, were aware of the pre-existing free data

http://random.dev.openstreetmap.org/progress/?region=northamerica

Slide 23

But after the tiger import, with all this new data in place, the growth of the U.S. community was still slow, and this caused people to start speculating and theorising about the negative effects of imports.

There was an imports panel at the Vienna conference a few months ago. I’m going borrow s slides and quotes from this.

Slide 24

“The best imports are those we avoid” was Frederik Ramm’s summary. Matt Amos said “Imports bad. Surveying good” Actually that’s not really a quote. That was his suggestion for my entire slideshow.

So some fairly strong anti-import opinions.

Slide 25

This is also from Matt. A few years ago he ran some simulations showing how the map completeness progresses, taking into account new users arriving, and running out of areas to map as it gets more complete.

It shows that if we start from nothing, but build up momentum and growth we actually end up getting better map coverage quicker than if we start with a certain amount of imported data.

Obviously it’s just a simulation, and with different parameters it would follow a different line. Also it doesn’t take account of this effect of people waiting for an import when they know the data’s available.

Slide 26

Frederik showed this example of an area of rural france where there’s been an landuse import. As you can see the map looks quite rich with data, but if we count up the number of users editing, there have been 20 users editing in this area since the import, and only four in the past year.

Slide 27

He compared this with an area of the same size and the same population in rural Austria. Here we see a much more active community. 81 users editing, and 27 users in the past year. And the map is an expression of local interest and passion.

Slide 28

But why would an import stifle the community in this way. The usual theory is that a blank area of the map entices and excites people. It feels like exploration to go and map an empty area.

But here’s a different theory. Often imported data is just not very beginner friendly.

Slide 29

I thought I’d show you what I mean with an example in Atlanta. [Demo] Atlanta has imported TIGER data, but also an import of some landuse data. There’s been a little bit of mapping activity in the city centre, but if we zoom in here http://osm.org/go/ZQqo7cqLm- a little way out from the centre, there’s a patch of woodland. I can bring in the bing imagery and just straighten this out a little bit.

As an experience user I know that this is imported data with limited accuracy, and I have the confidence to plough in and make some improvements. For new users this is difficult, and that’s before you consider that we’re dealing with ways on top of ways which are fiddly and technically difficult to make sense of.

I can also see some NHD data which has many nodes, but clearly isn’t very accurate.

Slide 30

So for new users this is less like a field of corn and more like a thorny patch of weeds or brambles.

Photo CC BY SA 2 Richard Webb on geograph http://www.geograph.org.uk/photo/640790

Slide 31

Here’s another quote from Frederik. I think this is a great way of putting it.

“It’s not enough to just make sure you’re leaving the map in a better state…” If you’re running an import you may imagine that you’re doing a good thing provided the map ends up being better.

But “You should make sure you are you’re leaving the community in a better shape”

Slide 32

Here’s some more analysis form Matt. This shows the growth in number of different users editing POIs normalised to population.

Germany and Austrla rank highly. We know they have very strong mapping communities.

The U.S. comes in last.

Interestingly the Netherlands scores quite well. They imported the whole country , but it seems they’ve still managed to build a strong mapping community.

Slide 33

I’m going to talk about fixup. I dont want to give the wrong idea. If you’re doing an import you should not be dependant upon users manually fixing up the mess you’ve made afterwards. Or if you do need a manual fixup phase, this should be planned and discussed before during and after the import.

Slide 34

But with existing imports, particularly the massive TIGER dataset, there’s no point dwelling on whether or not the import was a good idea. We need to move on and think about fixup now. This is the big challenge in the U.S.

There’s been a lot of talk at the conference about ideas for encouraging more mapping. When it comes to doing this in the U.S. we’re talking about encouraging fixup.

Slide 35

While we had our team at Cloudmade in 2009, we set up the “250 cities” project which looked at encouraging fixup with a focus on basic routing in the US.

http://wiki.openstreetmap.org/wiki/TIGER_fixup/250_cities

Slide 36

Most routing disconnects are actually caused by duplicate nodes. Nodes sat directly on top of eachother. These need fixing all across the U.S., and the duplicate nodes map lets us see the progress with this.

There’s some confusion around this. Let me be clear: Yes, we should fix the duplicate nodes, and no, we shouldn’t do it automatically

http://matt.dev.openstreetmap.org/dupe_nodes/

(Note this is broken/unreliable at the moment due to problems with OWL)

Slide 37

Also a widespread problem with TIGER data is the general positional accuracy. This is a display we created as a tutorial resource. I can flick between before…

Slide 38

…and after. To show the kind of corrections we need people to make. Just simply dragging the roads into the right positions using the aerial imagery. It varies from one patch to another, but there are a lot of patches of TIGER data which are wildly inaccurate in this way.

Slide 39

I can show you a quick example of this in Cleveland (Tennessee) where this kind of fixup is needed and hasn’t happened yet.

Note: I skipped over this demo to save time. At time of writing there is still some good juicy TIGER alignment fixup to do here: http://osm.org/go/ZQ6IJ2qF- I would expect this example to get fixed some time soon, but there will be other similar pockets for some time to come.

Slide 40

To measure the progress of this we have the TIGER edited map, showing in red any areas which have never been edited since the TIGER import, and green for those which have.

This kind of thing really should receive more attention from the U.S. Mapping community, and perhaps also from developers working to make improvements (it doesn’t work perfectly).

http://open.mapquestapi.com/tigerviewer/

Slide 41

Likewise the keepright tool has an excellent array of automated checks built into it. It discovers all sorts of problems with the TIGER data. Again this should be brought to the attention of U.S. mappers more, but I think there’s various ways the tool could be developed to make it more compelling for mappers.

Slide 42

So it’s fair to say that in the U.S. we’ve got a bit of weeding to do, to tidy up the TIGER data.

Photo CCBYSA2 Gordon Joly : http://flic.kr/p/aoj2ij

Slide 43

But if we look back at the situation in countries like the U.K, where we have grown our map organically, I want to talk about a different set of problems in relation to this.

Local passionate map coverage appearing in blossoms is wonderful, but we often have a problem of uneven map coverage. This is an acute problem for map users.

Slide 44

My favourite example of this is my jigsaw puzzle. I got a jigsaw puzzle printed with the map of London on it. I wanted this to be a good clear complete map image from OpenStreetMap.

But the London map has patches of building coverage, some arranged logically in the centre working outwards, but many patches sporadically appearing as blossoms of passionate building mapping around the outskirts.

Building coverage is quite prominent in the default rendering. This illogically arranged data actually makes the map of London quite ugly and not good for map users. Knowing how to do so, I was able to use a rendering with the buildings switched off, but in general sporadic blossoms of detail can make the map uneven and difficult to use.

Slide 45

I think this points to a deeper problem. Perhaps one of the trickiest problems facing OpenStreetMap as we work towards a “complete” map.

Mappers are working on their blossoms of mega-detail near home and work, and applying different ideas of what “complete” means. The level of detail we go to is a tricky question.

Slide 46

There’s no real limit to the level of detail, because of the way we’ve framed our mapping process with the opportunity to flexibly invent new tags.

Tagging ideas are open to progressively more insane levels of detail. It’s a sliding scale. I regard things like mapping sidewalks and roads as areas, as rather crazy, but people are seriously talking about more and more detail.

Soon we’ll be talking about mapping every blade of grass

Slide 47

Of course this is taking things to silly extremes, but where do we draw the line?

The usual response to these kinds of concern, is to say “why is it a problem?”. People map crazy levels of detail, and we all have a good laugh about it. It’s a problem because its a waste of time and energy of the mappers doing it, but It becomes more a problem too when people encourage others (including confused new mappers) to follow their lead. This happens within the tagging proposals and documentation, and also blogs and other communication channels. More mappers mapping more and more crazy levels of detail.

Image: CCBY2 meddygarnet: http://flic.kr/p/7YZzim

Slide 48

I dont have a solution to this problem, and as I say, I do think it’s a big problem we’ll be facing more and more.

This runs quite contrary to the way we’ve celebrated detailed mapping in the past, but perhaps we need to think about a new message. Among our pro-mappers perhaps the message should be: “consider the levels of detail around you”. Dont go crazy with the levels of detail within your blossom of map coverage. Keep a cap on this and map further afield instead. Go to a level of detail which is realistically attainable by you, or with the help of other mappers, across a wider area.

It’s almost like we’re trying to make our coverage more like an even field of corn…

Slide 49

So we’ve got problems. Two sets of problems really.

Here in the U.S. we want to see more blossoms of detail created by passionate local people. We’ve got a lot of a fixup work to do, and we need to attract a community behind the data to take on this task

But where we’ve grown our map organically, it can be like blossoms in the desert. We need to find ways of creating a map with more even coverage between the blossoms.

We need to work towards something more balanced, more gentle and serene. Something more like…

Slide 50

…an English country garden.

Thank-you very much!

Bottom image: Summer Garden, Munstead Wood CCBY2 sarah from gardenvisit.com :http://flic.kr/p/6zbGiw & http://www.gardenvisit.com/garden/munstead_wood_garden

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I came across a strange new breed of people who knew all about making maps using only adobe illustrator. That’s a side of “cartography” which rarely surfaces at the geo events I’ve been to before (and I’ve been to quite a few now), but this seems like a rather interesting artistic end of a map-making spectrum. I didn’t come across anyone who had tried out OpenStreetMaps options for exporting to Illustrator. This probably needs to be made easier, but I suspect Maperative might be a kick ass tool in this arena. I don’t have illustrator myself, so I’d be interested to know how well it works.

I gave a talk on a blend of topics to do with transport and open data and some of my experience of mobile geo development. I talked through some stuff I’ve been working on at placr.co.uk: The UK Travel Options iPhone app, and the more recent placr.mobi mobile website. Then I gave a few more nice bits of bus route related technology (and cartography) coming out of OpenStreetMap.

The slides and notes (approximately what I said in the talk) are included with the presentation on slideshare, or OpenOffice download, or PowerPoint download …or here it all is in good old pictures & text:

Slide 0

I’ve got four different things I want to talk about.

I want to talk about Open Data, and specifically Open Transport Data. And I want to talk about the work I’ve been doing at placr.co.uk, and finally my hobby and passion OpenStreetMap.

Lots to cover, but fortunately they’re all wonderfully interrelated, so it’s really just one big topic.

Slide 1

So there’s this open data revolution going on, and I believe it can be a revolution.

Data owners are resistant. I think there’s two main reasons. Either they are very directly protecting revenue they get from selling data, or they’re just scared the data (or even just the manner in which they publish it) will make them look bad. But happily Open Data is a political hot topic at the moment so data owners are coming under pressure.

One of the main political arguments for open data, is about transparency and accountability, which we see with datasets such as local council expenses. This is important of course, but I think there’s something quite negative about it. It’s almost like we’re saying “give us your data so we can sit here and more easily complain and criticise”

The second reason is to fuel innovation

Slide 2

Innovations can be enabled by open data, but there’s an awful lot of datasets being published because of this new political pressure. Some of them are quite uninspiring. Some are just a front onto a set of less open more high value data. The more exciting innovations, really useful applications which change our lives for the better, are only enabled by what you might call “high value datasets”.

Transport is an area with great potential for really useful apps. 51 billion passenger kilometres by train in a year. This a big number, although contrast it with 700 billion passenger kilometres by car. We can help change that. I like to think of it on a more personal level. How much of my life have I spent on trains and buses? If we can build apps that make this even a little bit better/easier, then that’s something quite powerful and transformative.

Slide 3

The reason we can talk about innovation coming from small companies and even bedroom coders, is of course that’s it’s very easy to put out applications on the web, and more recently apps for mobile phones.

It’s easy & cheap. This is deceptive though. It’s not that easy or cheap, but there are no up front costs, and people who have the the skills and the time to do it, can produce wonderful results on zero budget. The best results come from people with technical skills but also design flair and a deep understanding of user experience.

Obviously for transport, if we can easily develop for mobile platforms, this lets us put our app in the hands of travellers while they are travelling.

There’s a thriving community of developers and all of this drives demand for useful data.

Slide 4

I’m going to show you a mobile web app which we’ve been developing called placr.mobi

Let me say straight away, when it comes to talented app design and useability, I like to to think we’re somewhere on that spectrum, but I appreciate that this isn’t the greatest ever showcase.

We’re very much following the “release early release often approach“, and there’s quite a few glitches we still need iron out in this app, but it is available to have a play with at http://placr.mobi and interestingly one of the test areas we have data for is here in Plymouth!

Slide 5

But actually we’re not just in the game of trying build a great consumer oriented mobile app. It’s one of three areas we’re looking at.

We want to help other developers create mobile apps and web services for Transport. Some transport datasets are very awkward to work with in their raw form (I’ll explain more in a moment) We are offering a transport api which makes life easier for developers.

We’re also talking to transport operators and they are showing some interest in the analytics we can do with their data, and the channel we have to developers and end users.

So we’re looking at building apps, and it might allow us to earn some revenue with ads or through charging for a premium version. But it also feeds into the other two strands.

Slide 6

While I’m explaining placr, let’s take a further step back. Placr is an “open data services company”. We work with organisations who need help with releasing datasets.

We’re working with Pearson, the global publishing firm, reformatting their data, developing RESTful APIs, to help them engage the developer community (developer.pearson.com)

Along the way we also do a lot of open data campaigning, particularly my boss Professor Jonathan Raper who campaigns for open data in the highest levels of government.

Slide 7

For now though we need to work with what we’ve got. These datasets were particularly of interest to us.

TfL (Transport For London) has departure board displays as HTML, which we’ve scraped, but we were also one of the first people to test out their new API for this.

We’ve parsed their TransXchange files for static timetables.

There’s a brand new countdown display for live bus information released this past week. We will be taking a look at that.

NaPTAN is a dataset of bus stops with locations. This is useful alongside other bus data.

We’d love to do more with train timetable/live data, but this is an area where we’re actively campaigning, because the data isn’t open. ATOC are the open data villains here.

Slide 8

So the first dataset I mentioned was departures. This is data as displayed on the dot matrix screens on tube platforms, showing a train coming in 4 minutes and another train in 7 minutes for example.

We take this and run statistical calculations and averaging to let us create performance stats and displays. You can see these at http://tube-radar.com

Slide 9

Here’s the first bit of “cartography” I can show you. I can’t really take credit for this. It’s a wonderful map display engine created by a company called Faster Imaging, and available as a free iPhone app “UK Travel Options”. The screenshots don’t do it justice actually. You have to try out the fluidity of the interface and finger gestures for manipulating the map, to fully appreciate this. The map data is OpenStreetMap.

On the left though we see traffic light indicators on the tube stations, based on the performance statistics from placr.

Slide 10

And here’s those same traffic light indicators again on a more basic web map. http://apps.placr.co.uk/transportapi/tube/dashboard

Slide 11

We looked at the dataset for bus timetables from TfL which was in TranXchange format. This is a rather complex XML format which feels rather hairy and bloated for people trying to do rapid development. So I spent a few days trawling through big XML files.

Slide 12

I came up with this diagram of the objects and their links within the file. It seems to be suited to loading into a database, to make sense of these linkages.

Slide 13

The desired outcome which took an awful lot of data wrangling to achieve… was of course something which looks like a normal timetable.

Once we’d figured out how to get a timetable grid like this, we made some quick progress, loading that data into a database and then into ruby on rails to produce some new outputs. For example here’s a little web display of a bus-stop, showing when the next few buses are departing from the current time.

Slide 14

So this is that same content presented within the placr.mobi mobile web app. So we’re parsing the transXchange and providing a content API. This can be easily consumed by mobile app developers.

For placr.mobi we use a javascript library called jQuery mobile, which very quickly and easily makes a website look like an iPhone app. It’s quite nice, but we’re encountering a few gotchas with it.

Slide 15

We start to see a geo element to this app when we tie into bus stop location data. So the app lets you find nearby bus stops. We use the web browser location features, which result in this prompt. This will be familiar to iPhone users. Essentially the user has to say that they’re happy for placr.mobi to know their location.

…and then we can list the five nearest bus stops.

When designing simple geo apps, I think its really interesting to think about foursquare. Dont worry. I think it’s a pretty silly game too, but it’s a poster-child of location based mobile apps, and what’s really interesting is that it doesn’t show any maps in it’s interface. It’s a terrible thing to say at a cartography conference, but you can build exciting geo-apps, without showing any maps, and maybe this can help keep things simple and appeal to a wide demographic.

Slide 16

But don’t worry. I love maps just like the rest of you, and in fact I couldn’t resist putting some maps into the app.

This is an easy thing to do. If you’re developing a web or mobile app and you have a lat/lon in your database, just drop in a link to OpenStreetMap.org You can pass the lat/lon as parameters. Use the ‘permalink’ feature to see how the URL should look, but then you can also add a marker by changing the url parameters to mlat and mlon.

This is an iPhone screenshot, and you can see that the map fits nicely in the browser due to some custom mobile css. However the OpenLayers library used, doesn’t allow pinch zooming

Slide 17

So I’ve started looking at using another javascript library called ‘leaflet’ from CloudMade. It’s free and open source, and you don’t have to use it with CloudMade tile servers, so they’re not trying to create any lock in, which is cool.

And this does allow pinch zooming.

Slide 18

But here’s another simplification to think about. Static map image APIs allow you to just use a plain old img tag in your HTML. This is perhaps the ultimate map display solution for cross-browser mobile compatibility.

The src URL of the img tag has all the location and size parameters. One thing to watch out for with this is that you’re very dependant upon another server somewhere generating these images.

Slide 19

So we’re working with transport related open data and building a transport API at transportapi.com. We’re doing some JSON/XML stuff, but also content APIs, so formatted HTML fragments which are then taken by placr.mobi and other app developers to be displayed.

Looking at placr.mobi you’ll also see some stuff to do with activity streams, and a short URL service pla.cr I won’t talk much about that now, but essentially we’re doing some experiments with social networks and social engagement with and between bus travellers.

Slide 20

NaPTAN is the bus stops dataset. It’s quite well organised in that every bus stop in the country has an atcocode. It does include a lot of closed/discontinued bus stop locations which you have to watch out for, and the locations are a little inaccurate.

OpenStreetMap has imported NaPTAN bus stops in some parts of the country.

Slide 21

This might amuse you. I sometimes manipulate or view geo datasets by converting them to .osm files and then opening them in JOSM, the Java OpenStreetMap Editor. This is what happens when OpenStreetMap people try to be GIS people.

I can do various comparisons this way, but what we see here is the OpenStreetMap bus stops in the south west, and highlighting in red those which have been imported from NaPTAN.

Slide 22

The interesting thing about taking this data from OpenStreetMap, is that OpenStreetMap contributors can make improvements, so in particular it could be good to encourage people to refine the accuracy of bus stop locations.

It is possible to develop editing functionality within mobile apps. Users can “authorise with OpenStreetMap” via the oauth mechanism of the API. This is complex in terms of development, and also in terms of user experience.

Another way which I think lots of mobile app developers could think about, is to follow a triage approach. There’s a database of map bugs called “OpenStreetBugs”. Users can very easily (with a simple interface) report problems, but OSMers need to make the actual edits later

In a simple mobile app it may be a challenge to explain that OpenStreetMap data should not be copied. Also smartphone GPS accuracy is not good enough for placing OSM nodes

Slide 23

We haven’t delved into this much with our placr work so far, but OpenStreetMap does have bus routes data. It’s not complete but the more people use the data, the more motivation there is for the community to fill it in. A great thing about working with OpenStreetMap, is that your service has the potential to be worldwide. If you get something working well in the UK, it can work just as well in New Zealand, or even in the developing world. Wherever local people have filled in bus routes data.

Slide 24

When I’m introducing OpenStreetMap I generally explain how the data is made up of Nodes and Ways, and these have tags on them. And this data model is wonderfully simple.

Slide 25

However for working with bus routes I need to introduce another datatype: “Relations”. Basically these things relate different nodes and ways in some way, and they also have tags. But they can make things a bit complicated

But we can use them to represent a bus route with a relation made of roads, with the tags type=route, route=bus.

Slide 26

And we can render these bus routes on a map. Here we are in Plymouth. We can see that there’s quite a few missing bus routes here. Maybe we should do a mapping party later!

This is öpnvkarte.de, a very german website with an umlaut in the domain name, but you can also reach it via openbusmap.org It’s been around for a while, and it’s one of the nicest examples of OpenStreetMap custom map styles. It looks great at the higher zoom levels too. And there’s some interesting dynamic clickable bus-stop features on this site too.

This site was having some some server instability, and wasn’t showing OpenStreetMap updates. This thing of bringing in updates is really important as a way of spurring the OpenStreetMap community to add in more. Happily the site is now working well

Slide 27

But during a period when it was failing to update, I was motivated to come up with my own attempt. I wanted to see how the london bus routes coverage was progressing. So here’s my mapnik rendering, which I did as a one-day “hack” at a rewiredstate event.

Slide 28

But this was quickly redundant because shortly after I did it, Andy Allan launched this transport map.

I believe Andy presented at the Society of Cartographers last year. This is his new transport map. Again some really nice cartographic styles. He’s gone for simple thin streets and dropped a lot of detail to highlight the bus routes.

You can see this on http://opencyclemap.org if you flip to this alternative layer in the top right.

Slide 29

I didn’t make it along to the OpenStreetMap conference in Vienna unfortunately, but you can see video of the talks. There was an interesting presentation from Dr Bartosz Fabianowski of dobini.com http://sotm-eu.org/talk?62

He’s done some interesting work, again using Mapnik, but just rendering small images alongside strip diagrams for print display at bus stops. He has an emphasis on automation, so this whole display is generated automatically from the raw data.

Slide 30

And of course I have to mention our sponsors at this conference. Itoworld are doing some good looking stuff around bus timetables and maps, also creating print output. It’s a little bit hidden behind the scenes, but the sample images on there site look impressive.

Slide 31

Thankyou for listening. Here are my contact details, and you can try out the app I’ve been describing by browsing to http://placr.mobi on a smartphone, or just on a desktop P.C.

And of course… check out http://OpenStreetMap.org

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I’m going to talk about mapping as in creating maps, and the not-for-profit mass-collaboration project “OpenStreetMap”. I’ll show various examples of how OpenStreetMap has helped in disaster response and developing world situations.

But first let me explain what OpenStreetMap is…

OpenStreetMap.org is a website which displays a map. Here is a map of where we are right now for example. The site lets you zoom in and pan around the map, much like google maps. But you can already see some interesting details which you wouldn’t get with google maps.

OpenStreetMap is much more than just a map…

Openstreetmap’s mission is to release map data for free.

This means free as in zero cost

And free as in freedom

Access to the raw data with an open license, means developers have the freedom and flexibility to use map data in new and exciting ways.

This is a rare thing for geo-data. Map data is generally owned by somebody, and raw map data is normally expensive.

So how do we get raw data to release with an open license? We do a crazy thing. We pretend there are no existing maps. We go out and build a new map from scratch.

We do this by being openly editable.

The map editing software is designed to be quite simple, although it does involve editing vector data, which is inherently a little bit complex. This editor is JOSM. It looks a but like autoCAD, so hopefully familiar to architects and engineers

But in general we’re trying to keep it very simple because we want to attract large numbers of volunteers to help make the map.

And we’re having some success with attracting contributors. We recently passed 400,000 registered users, and the we’re seeing more and more editing activity all the time.

To build maps, we often need to do on-the-ground surveying

This can involve GPS and other gadgets.

…Or a more simple pen and paper approach.

We can trace maps from aerial imagery of course

It’s important to realise though, that companies making maps would normally buy an expensive license from imagery providers, giving them the right to derive vector maps. A lot of money changes hands for something you might imagine to be free.

Generally OpenStreetMap can’t afford licensing costs, but we have agreements with Yahoo! and more recently Bing imagery which covers some parts of the world. Here in London it has excellent resolution.

Like the editing software, the underlying Data model is kept very simple.

The map is composed of nodes and ways. And these elements have tags attached to them, to describe what real world feature we are representing.

This low level vector data is rendered into a maps with various style choices. This flexibility is rather like the having many layers of vector data in autocad, and select the layers and styles to print out.

So OpenStreetMap is not particularly a humanitarian project. It originated with this open data purpose in mind for developed countries (it originated here in London in fact)

But we have this simple map making framework in place, and the map is editable worldwide. All of the same mapping techniques can be applied anywhere in the world. This makes it a mapping platform with huge potential for developing countries, and for aid agencies operating there.

When the earthquake struck in Haiti a few people people in the community very quickly went and looked to see if there were improvements to be made to OpenStreetMap there.

The stricken cities of Port-au-Prince and Carrefour have yahoo imagery coverage. So straight away a handful of people set to work tracing in roads to create a street map. As you can see, this imagery is a bit fuzzy, but good enough to see the streets.

Because of the severity of the disaster and the international attention it received, aerial imagery providers GeoEye released an area of imagery for free.

This was post-quake imagery so you can see some collapsed buildings, and people camping out in the streets.

More people started getting involved in tracing the imagery. We also found old military maps which we could use as a source of some street names.

There’s some clever technical people in the OpenStreetMap community. They were able to marshal the large imagery datasets into tiles which could appear within the openstreetmap editors.

Other imagery sources became available with varying resolution and updated-ness. This shows a patchwork of different sources brought together in one place, and set up as tiles which can be brought into the OpenStreetMap editors.

So the community mapping by remote was able to go from this…

…to this

The campsites here are the positions where people were visbly camping out in the streets.

So we produced a good detailed streetmap of these cities, and we did it quite quickly.

This is the map as it appears now on OpenStreetMap, but we had created the important street map in place within 48 hours.

This was appearing very publicly in a useful display on OpenStreetMap.org

But let’s look beyond displaying the map on our website…

 

 

With OpenStreetMap you can do the classic google maps style mash-up thing, so embedding a map on your website with OpenStreetMap as a layer and push-pins or other information on top.

People launched all sorts of other initiatives around the web to help with disaster management, some more successful than others. A lot of them used maps to try to track things happening on-the-ground in Haiti.

This site is called “ushahidi”. It does aggregating and tracking of reports coming in on various communication channels, all plotted on a timeline, and on a map. So they’ve followed this mashup approach, and switched from using google maps to OpenStreetMap as the background map.

 

 

But more exciting than that, aid agencies on the ground were finding out about OpenStreetMap

In fact we had by far the best map, of these cities. Printouts of OpenStreetMap were pinned up in the control rooms and tents of aid organisations.

 

 

OpenStreetMap offers raw data downloads and also downloads of formats converted to work on various devices.

Garmin downloads are particularly popular, and search and rescue workers found our garmin downloads useful. Allowing them to find their way through the chaos without needing to be online.

In fact we received an impassioned message of thanks. That was was very gratifying for everyone involved. That’s when we knew we had made a difference.

 

 

Here are some other quotes

One from a MapAction coordinator. One from UNOSAT technical staff

So that is the story of how OpenStreetMap helped with the Haiti earthquake response

 

 

Watch ITOworld haiti OpenStreetMap animation video

This video shows a white flash for every edit taking place on the map data. Each one represents some work, perhaps 10 minutes, perhaps a hour, by an individual contributor.
You can sit back get a sense for all this mapping work going on, and the buzz and activity of the community as they pounce on the aerial imagery and respond to the disaster. The blue glowing bits are campsites

 

 

So that was a disaster mapping situation. OpenStreetMap is also of interest to aid organisations working on more long term development goals.

A guy called Mikel Maron spearheaded a lot of the humanitarian work with OpenStreetMap. He spent a long time out in Nairobi Kenya, and went to the largest slum in Africa, a place called Kibera.

He received some funding from aid organisations to do this as a project called MapKibera (MapKibera.org). They used OpenStreetMap to make a map of the slum including water supply fountains, and medical facilities.

 

 

So they managed to create this map, but they did it by training local people to contribute to OpenStreetMap, using the simple editing tools. Using OpenStreetMap as a mapping platform, locals could take ownership of their own map. The project involved teaching them to collect data, but also teaching them how to make use of it.

Official maps of nairobi didn’t acknowledge the existence of Kibera. This new map gives them the knowledge and the power to enter into informed discussions with the authorities about their plans for bulldozing areas of the slums.

 

 

There was a project to map the gaza strip, again engaging with the local community. On this early project the OSM community held a fund-raiser to buy an area of aerial imagery from a satellite company.

 

 

We thought the Pakistan floods would be the next big example of the power of OpenStreetMap to make a difference in disaster response, but in comparison with Haiti, the disaster struck area was collosal. Floods spread up and down the length of Pakistan.

The dark blue area is imagery specially provided to us by SPOT. Quite a large area, but fairly limited resolution, so this limited what we could achieve during the flooding.

 

 

Similarly there was quite wide scale descruction all along the coast in Honshu part of northern Japan when the tsunami struck.

We were able to see some good imagery in Sendai for example. Bing merged in some useful imagery into their standard offering. You can see some patches here are showing post disaster destruction and flooded areas on the sea front.

 

 

Now clearly in a developed country like this there are sure to be good maps available already, but we can create maps which reflect these kinds of situational update. Edits to the map data are shown within minutes.

While superior maps may be available if you know where to look, our maps are openly and easily available. If this can save time for a few disaster responders, then it’s worth doing.

 

 

And this map is available to embed in other websites which may be providing services to aid in disaster response. Here (on sinsai.info) we see the “ushahidi” system deployed again to allow temporary situational reports, and requests for help coming in various communications channels. With a better basemap, this data can layered on top in a clearer and more acurate way

 

 

This summer a team have travelled around Indonesia running a series of workshops to get local people involved in detailed mapping. This has been the latest HOT project, just coming to an end. It’s the first time we’ve looked at doing a targetted disaster mitigation exercise, aiming to better map an area identified as at risk of seismic activity. This project has also seen a focus on building mapping, with a competition between univerisites to make a game of the process of adding buildings in.

(For more on this see ‘indonesia’ category on the hot blog)

 

 

This is a new slide. I’m not sure if it really belongs in a slide deck about humanitarian mapping. When you think that 300,000 died in the Haiti disaster, London isn’t really facing a “disaster” right now, no matter how much the media builds it up.

Even so, there is an interesting need to filter and tame the information overload. Maps privide a way of doing this. Here we see a validated list of riot incidents layed out on a map.

And of course it’s our map. Me and my friends have walked these streets to create a detailed map. It’s always gratifying to have it used (and frustrating when people use boring old google maps)

Perhaps we’ll aim to add some new contruction areas after the riots …and remove a few shops.

 

 

After haiti we formed a new organisation: the Humanitarian OpenStreetMap team (HOT) . This is an attempt rally some the openstreetmap community around the humanitarian mapping cause, and to put a more organised face on the community, which can seem chaotic and anarchistic for outsiders.

In particular we’d like to engage with aid organisations and get more funding, and deploy people to do humanitarian mapping on-the-ground.

 

 

So that’s OpenStreetMap.org and the Humanitarian OpenStreetMap Team.

You can find out more at these sites (openstreetmap.org, hot.openstreetmap.org) You can donate to OpenStreetMap directly. We’ve also got some fund raising more direcly related to hot on the hot site, but I hope you’ll also be inspired to learn how the OpenStreetMap editors work, and have a go at contributing to some mapping.

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These slides are (of course) freely re-usable under the Creative Commons Attribution-ShareAlike 2.0 License

Credit to Schuyler Erle and David Dean for some slide images and slide inspiration

Map images are CC-BY-SA OpenStreetMap

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