where2.0 and wherecamp

Back in the UK now. Attended and wherefaired Geocodr.net and went to wherecamp too. Some highlights and notes:

  • Microsoft jaw dropping lovely (in browser) 3D rendering
  • Googles “hmm, what can we do with that” nothing-new StreetView
  • Poly9’s FreeEarth flash globe.
  • Experiencing Flickr going offline just when it was really needed! Realising how much a mashup can be dependant on a single link in a long chain.
  • Meeting new folk, hanging out with some of the nicest people in the geo.
  • Hearing openstreetmap mentioned loads of times, and Mikel begging for people not to mention GeoRSS any more!
  • Getting perspectives on data availability in the Middle East and comparing it to the USA and UK.
  • Rich Gibson’s “Story” – using technology to aggregate, filter and report back to hold a mirror to oneself “You seem to be playing too much WOW, why dont you pop round your neighbours”
  • Where mobile app development -on my list.
  • Maplets – on my list
  • Yahoo’s FireEagle – on my list
  • Playing WhereWolf at wherecamp and being lynched for no good reason, and waking up to the sound of the yahoo display case crashing mysteriously.
  • Amateur forensics later that morning…
  • Delving into ideas about how to grab softer information about neighbourhoods, gist of a place
  • Good session about locative arts.
  • At wherefaire, the sonar-coat, a coat with proximity sensors sewn in, and heart rate monitor.
  • Doubling the amount of t-shirts I own through schwag.

platial makes dream reality: lucky penny map

Way back in 1999, I had a free hosted website. (findapenny.crosswinds.net) with the idea of getting people to submit where they found a lucky penny, what happened that day, post pictures, trade and swap lucky pennies. All this depended on web mapping (remember back to 1999) and all I had was a manually made HTML imagemap, so of course nothing happened! Now thanks to Platial , I’m able to do most of this, well, at least allow people to add and share their locations and stories. They’ve featured it on their blog too.

Heres the link to the lucky penny map

Joined up to Platial last year soon after their launch but hadn’t really found something I wanted it to be used for. This way, it’s an “open” map, and so other people can add their experiences, finds, pictures – something that’s ideally suited to Platial.

Looking forward to seeing their mapkit integrate with wordpress better – a side bar is a bit too small for this blog, but would be nicer on a separate page.

edits: here’s a marvellous lucky penny website

Map of walking times between tube stations

Shortwalk have posted a great map of the time taken to walk between London tube maps (via we-make-money-not-art). Last time I was in London, I eschewed the tube, and went around by foot, and for longer journeys, or when it was raining, the Bus. Walking was so much better, you can see and smell the city, experience how the neighbourhoods change, the people differ, the architecture changes, its great! The tube is quite stressful, and quite expensive! Tube travel is like plane travel between cultures, you pop up into another world, without any real notion of the transitions between start and finish.

Its amazing how close everything is. When you are in the tube, the distances seem so much further. I remember a few years ago getting the tube between Leicester Square and Covent Garden! The tube map although great for planning journeys really does distort distances.

They write:

“Also, when you walk, you dont have to stick to someone else’s plan. Walking means you can pop in to a shop to pick up the newspaper, have a coffee, post a letter, get some loo roll, or buy that Valentine’s gift for your significant other you have been meaning to take care of!

Walking also means you can plan your own route to suit your needs on a given day– if you are late you can take a short cut If you have some time, stop off at the Tate on your way home, or for a drink at the pub with mates.

Walking is about flexibility, and thinking outside of the box!”

Whilst i was there in London, I went on a great free walk (run by a YHA volunteer) to see some famous pubs associated with pirates and smugglers. These were away from the tubes, you wouldn’t have come across these if you were staying to the beaten tube-path. Guided walks are recommended for anyone, resident, frequent visitor, or first time tourist.

Flickr Geocodr – k-means cluster enabled geocoder

Here’s a geocoder that finds places based on the combined knowledge – the tags, title or description of geotagged Flickr Photos. Example Application. Now that Flickr has 10 Million Geotagged pics, there’s a fair chance that people will add tags to them that describes the location. So searching for photos tagged with Manchester, will probably bring up a lot of photos that are located in Manchester. However, it will also bring up other groups of photos, and this is where clustering comes into play. geocodr.png

This work is inspired by Mikel Maron’s Flickr Geocoder, which grabs photos via the geoRSS feed, and uses the mean value of the locations. The Flickr GeoRSS feed Mikel used also includes photos that have no locational information – so we have to use an API call(flickr.photos.search) to grab more geotagged photos, and a simple mean value doesn’t take into account the clustering of photos that are found, for multiple areas.

I ported over and changed a Java k-means clustering algorithm into PHP. The clustering process seems to be very fast.

this screenshot shows a search for Manchester across the world, and shows the number of clusters. It picks out the cluster with the largest number of points within it.

You can get different results by changing a number of parameters both in the clustering and the flickr api call. I found that three or four clusters gave a good result, the number of points around 50 was sufficient, but a larger sample would give a better answer, searching by tag or text, using a bounding box etc, could improve or change results.

In the Example Application, and as default setting on the geocoder, it returns photos based on “interestingness” rather than “relevance” or date. This seemed to give a good spread of different authors, and photos.

This is clustering based on geographical proximity, but how about clustering based on other variables? The similarity of other tags? Colours in the photo? Date or time taken? A multi-variate clustering may be worth looking at. Dan Catt has talked about clustering recently too.

Possible things for the future:
Automatically search by text if no results are given by tags.
Make pure clustering webservice.
Return photo and cluster, points information back in response.

Edits: For the Ning users:
I made use of <xn:head> to insert the relevant OpenLayers javascript code, and marker code.
Since Ning uses dojo, I used that to communicate via javascript to the webservice:

var bindArgs = {
url: “Flickr/flickrgeocodr.php”,
method: “get”,
content: {“place”: place },
mimetype: “text/xml”,
load: function(type, data) {
doPlace(data, place)

Neogeography.net forum

Emptystreets.net have announced a new forum at neogeography.net for “the discussion of neogeographic theory and practice”

“Platial sees neogeography as encompassing urban exploration, site specific sculpture, land/earth art, geo-tagging, guided walks, ephemeral cities, imaginary urbanism, altered maps/radical cartography, travel writing, psychogeography, and place-based photo blogging, but even they wonder what connects all of these activities. neogeography.net would like to know what you think.”

Great stuff, all the types of things that excite and interest me, would be good to see new conversations taking place on the forums, in conjunction with the various mailing lists, blogs, and irc.

anxiety & happiness maps

Jeffrey has looked at Anxiety Maps some more and outlines a procedure to getting the data. The location of the blogger can also be captured, for example through Blogwise (Lebanon Bloggers) and through bloggers using geotags http://brainoff.com/geoblog/ shows a way to map blogs using http://www.weblogs.com/ and geotags.

I’m thinking there could be two outputs, a map showing where people are worried about, and a map showing where people are worrying.

Psychology researchers from the University of Leicester have produced “the first” World map of happiness (from metafilter and many other sources) which is a subjective mapping exercise about peoples happiness in the world. It looks like it uses variables such as health, education, prosperity and education. “Health is more important than wealth or education”.

Its main message seems to be that Capitalism leads to happier people, as opposed to the idea of” the happy savage”, and that the anxieties of modern life are not that important to a countries happiness. (Perhaps worrying about other countries, is in fact a luxury!)

Second on the list of happiest places is Switzerland, so I should be able to report back on their relative happiness compared to the UK’s miserable 41nd position!

anxiety maps

So in #geo, the talk went nicely off topic and discussing about favourite films, and then onto favourite apocalyptic films, and what with the increasing tensions and conflict between Israel and Lebanon, Korea etc, there seems to be an increasing fear of nuclear end of the world. I grew up in the 80s with many others with acute nuclear-war anxiety, Threads , the Day After, When the Wind Blows, etc all led to us feeling very anxious. Since anxiety is not good for the health, and it is used as propaganda to influence peoples behaviour (i.e. you may die, buy this assurance) how can we fight back, restore the balance using maps and geographical information?

anxiety culture is a favourite site for a quick anti-anxiety fix.

How about simply showing how peoples fear, get it out in the open, or how different places, peoples, ages, cultures have different responses? <roger> chippy: can you index your anxiety map by specific anxiety and date? – great idea.

Ive done some work capturing these fuzzy kinds of data with tagger and I know there’s the British Crime Survey results around that can show which areas have more “fear” of crime. More research would be needed to find some more data.

Another idea would be to compare time series with scraped “events” from BBC/google news to see if there’s some correlation. Edits: or maybe by scraping through some sections of the blogosphere, and seeing how they react from day to day, and place to place.