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Sylvain Carle People Suck At Naming Places (version with notes)


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The world of precise coordinates is easy to interact with using software. The problem is humans don't use precise coordinates to represent places. They don't even agree on place names. I will try to give an overview of the current existing services/APIs that you can use to find a precise coordinate with a place name. And then demonstrate why we are not there yet.

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Sylvain Carle People Suck At Naming Places (version with notes)

  1. 1. People Suck at Naming Places Ignite Where San Jose 2010/03/30 1 Wednesday, March 31, 2010 This talk is born form my obsessions at Praized, a local/social platform/api. I was going to be a French Literature Major at Université du Québec à Montréal but the internet came along... Might scorch your ears. Not native english speaker. I now say “third” but use to say “turd”. Oh shit, I know... suck-at-naming-places/
  2. 2. If a search falls on a map... and nobody is around to map coordinates does it exist? “To be is to be perceived” Awareness. 2 Wednesday, March 31, 2010 Georges Berkeley - places are all about what we say/do... What is the difference between what something is, and how it appears? If you have ever attempted to develop a system to parse location from unstructured text, you know that even structured location data is not that well structured, quality varies a lot.
  3. 3. Places names are... ๏ Relative ๏ Fuzzy ๏ Temporal ๏ Variable ๏ All about Perception 3 Wednesday, March 31, 2010 Relative: Eastside LA? Where does that start? Fuzzy: I’m at Where 2.0 at the Marriot. If I’m on the grass in front, I’m I still “there”? Variable: Meet me at the snow castle (during Carnival in Québec) Perception: Meet me at the unicorn... (Bristol Council House)
  4. 4. Places names are... ๏ Historical ๏ Cultural ๏ Personal ๏ Based on convention 4 Wednesday, March 31, 2010 Historical: history traces geography - city, streets, change names. But people like the old ones, that’s what they grew up with. Cultural: Depends on whom ask. Eastern Canada might be Ontario for someone from BC. It’s most likely the maritimes if you are from Québec. Personal: Maine and Vermont might be North to you. It’s South to me most of the time. Also people attach events/metaphor to places “where we first kissed” is hard to precisely pin on a map... Based on social conventions - agreements of many, shared meaning
  5. 5. Humans define places Humans are imperfect, “namespace” of places is really, really, messy. Add politics, religion, ownership, language... #l10n #i18n #hard 5 Wednesday, March 31, 2010 Messy. Context switch. Local, international, names are shortcuts... %C3%A9kin&sll=39.873912,116.408386&sspn=1.566119,1.930847&g=Beijing, +China&ie=UTF8&hq=&hnear=Beijing, +China&ll=39.814865,117.193909&spn=1.751028,3.501892&z=9
  6. 6. Language and approximation ๏ J’ai quitté mon domicile qui se situe à la frontière des quartiers Outremont et Mile-End à Montéal. ๏ Vers l’aéroport de Montréal, nommé Pierre-Elliot Trudeau, situé à Dorval, code YUL, au Québec. ๏ Direction de la côte ouest américaine, plus précisément vers SJ qui est ma destination finale. ๏ De plus, cette fin de semaine, je serais au WhereCamp chez Google. 6 Wednesday, March 31, 2010 Having fun here. En français... can you spot how many places are “named” here? 14. Fuzzy. In French. Imagine in Glyphs you can’t decode...
  7. 7. The Cathedral and the Bazaar ๏ Smart data structures and dumb code works a lot better than the other way around. ๏ Often, the most striking and innovative solutions come from realizing that your concept of the problem was wrong. 7 Wednesday, March 31, 2010 Smart Data, dumb code. Your concept is wrong. KISS.
  8. 8. One ID to Rule Them All ๏ Three IDs for the WEB kings under the MS, AOL & Y! ๏ Seven for the LBS lords in their halls of stone, ๏ Nine for GIS Men doomed to die, ๏ One for the G Lord on his “non-evil” throne ๏ In the Land of the Internets where the Shadows lie. ๏ One ID to rule them all, One ID to find them, ๏ One ID to bring them all and in the darkness bind them (under a restrictive license). WRONG! 8 Wednesday, March 31, 2010 I won’t read this to you... but let’s just say, centralization might seem a good idea, but it’s not (it’s also a choke point, not really in the spirit of the internet). We don’t want this (for a certain value of “we”) (re-interpreted)
  9. 9. TIMTOWTDI ๏ Find by... ๏ Lat/Long (duh) ๏ Name ๏ Nickname ๏ Neighbourhood ๏ Proximity ๏ Activity 9 Wednesday, March 31, 2010 Many facets. As many as human interests... There is more than one way to do it. To parse from language, you usually need 2-3 hints/axis to match, more context always help (from user previous actions, social graph, profile).
  10. 10. TIMTOWTDIBSCINABTE ๏ Lightweight Identifiers ๏ As simple as possible ๏ Distributed (webwide) 10 Wednesday, March 31, 2010 But then again... Tim Toady Bicarbonate! “consistency is not a bad thing either”'s_more_than_one_way_to_do_it
  11. 11. Name Repositories ๏ GeoNames ๏ Geocommons ๏ Placemaker Others? Tweet ๏ Wikipedia/DBpedia Text suggestions to @afrognthevalley ๏ Freebase with #ignitewhere 11 Wednesday, March 31, 2010 So there’s a few good sources of “names”... mostly in english. Please Intl folks, chime in with your APIs...
  12. 12. Geographic Indexes ๏ OpenStreetMaps ๏ Maps API (you know them) ๏ Open Data Repos Others? Tweet suggestions to ๏ @afrognthevalley with #ignitewhere 12 Wednesday, March 31, 2010 Also good sources of coordinates. That you can map to names. You get the idea.
  13. 13. Linked Data & IDs schemas ๏ WOEID (Twitter) ๏ Flickr place_id ๏ Google place URL ๏ Freebase GUID ๏ Geohash ๏ Not 4SQ/GW (yet) Others? Tweet suggestions ๏ but machine tags to @afrognthevalley with #ignitewhere 13 Wednesday, March 31, 2010 Anchor points. Passing references between systems. Still emerging. We (Praized) are working on this. SimpleGeo is another known source.
  14. 14. Activity Streams Mining ๏ Status updates ๏ RSS/ATOM feeds ๏ ๏ Explicit ๏ Implicit ๏ Derived ๏ 14 Wednesday, March 31, 2010 Explicit, implicit and derived “places data”. From unstructured to structured (with a little help from our friends - Localeze and YPG).
  15. 15. Most Data Licenses Suck 15 Wednesday, March 31, 2010 We had to work a lot to have “api friendly” licenses. One thing I want to fix is with “rel- licenses” within microformatted data, for different entries.
  16. 16. Be a Data Hippie 16 Wednesday, March 31, 2010 Peace, love and machine tags. And rainbows. Pandas optional. I think this approach wins at the “simple as possible but not simpler” contest. But then again, if it looks like RDF, many “web” folks don’t like it. You can express this as XML or JSON too if you really need to. namespace:predicate=value - that’s it! Simple bootstrap.
  17. 17. The World is Messy I like it like that It’s more work It’s more fun 17 Wednesday, March 31, 2010 The world is messy, any data derived from it shall be. This is a slide with less text, it’s a buffer slide for the speaker.
  18. 18. Bootstrapping ๏ BOF on matching location in unstructured text anyone? ๏ WhereCamp session on Places in Activity Streams... ๏ Machine Tag Exchange? 18 Wednesday, March 31, 2010 Let’s move this forward... BOFs tomorrow. WhereCamp session Saturday. Let’s Swap.
  19. 19. Places are Social Containers 19 Wednesday, March 31, 2010 “Places” is the natural/intiutive way to sort/filter social activities. (the other two axis are time and friends). I could have given you 20 examples of bad places names. Check out the “Fascinating Names” blog for that -
  20. 20. Thanks! ๏ (activity stream) ๏ (blog) ๏ @afrognthevalley on twitter ๏ ๏ Wednesday, March 31, 2010 suck-at-naming-places/