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Mobile Social Location (Web 2.0 NYC edition)

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Mobile Social Location Matt Biddulph, Nokia Web 2.0 NYC 2009 icons by http://www.famfamfam.com/lab/icons/silk/
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Page 1: Mobile Social Location (Web 2.0 NYC edition)

Mobile Social LocationMatt Biddulph, Nokia

Web 2.0 NYC 2009

icons by http://www.famfamfam.com/lab/icons/silk/

Page 2: Mobile Social Location (Web 2.0 NYC edition)

Where We Are Now

Page 3: Mobile Social Location (Web 2.0 NYC edition)

Street dataWe’ve always had static information in public space that’s designed to be interpreted by users of that space.

photo: http://flic.kr/p/9CKCw

Page 4: Mobile Social Location (Web 2.0 NYC edition)

Mobile ContentIn the early days of small mobile devices, apps like Vindigo delivered static content by syncing to an internet-connected computer. The device is blind - it doesn’t know where its user is or anything about the environment in which it’s used. It has to be told.

The interfaces on these apps are usually very simple and fast, partly due to the low power devices, but also because they’re designed to be used in a hurry in public space.

Page 5: Mobile Social Location (Web 2.0 NYC edition)

Ratings and ReviewsThere have always been websites that let users rate and review places - sites like TripAdvisor have a huge amount of data collected over years.

And yes, Beijing has an official star-rating committee for toilets.

Page 6: Mobile Social Location (Web 2.0 NYC edition)

Maps

Traditional symbolic representations of space ...

Page 7: Mobile Social Location (Web 2.0 NYC edition)

Maps

... are now widely available online to build into apps

Page 8: Mobile Social Location (Web 2.0 NYC edition)

Sat NavTurn-by-turn navigation - usually provided by Navteq, Teleatlas and Google - is the hot topic in online maps right now.

Photo by Perfesser - http://flic.kr/p/4cbfmj

Page 9: Mobile Social Location (Web 2.0 NYC edition)

Street screens

Static street content is slowly becoming dynamic ...

Page 10: Mobile Social Location (Web 2.0 NYC edition)

Street screens

... but the interactions, when they exist, are not always smooth experiences.

http://anti-mega.com/antimega/2009/09/30/screens-in-context

Page 11: Mobile Social Location (Web 2.0 NYC edition)

Snap To Grid

A simple lat/long coordinate is not enough for most people-oriented apps. We need a way to turn a GPS read into a human-meaningful place such as a cafe, office or home. APIs and datasets to do this are starting to appear.

Photo by paalia - http://flic.kr/p/6sAzuf

Page 12: Mobile Social Location (Web 2.0 NYC edition)

Snap To Grid

“electronic acquisition pays no attention to geography”—Chris Heathcote, 2004

A simple lat/long coordinate is not enough for most people-oriented apps. We need a way to turn a GPS read into a human-meaningful place such as a cafe, office or home. APIs and datasets to do this are starting to appear.

Photo by paalia - http://flic.kr/p/6sAzuf

Page 13: Mobile Social Location (Web 2.0 NYC edition)

The CheckinIf we can translate a user’s location into something meaningful, we can add layers of information on top.

Page 14: Mobile Social Location (Web 2.0 NYC edition)

The CheckinLots of interesting apps are based around the idea of “checking in” at a location rather than simply recording GPS tracklogs.

Page 15: Mobile Social Location (Web 2.0 NYC edition)

Location brokersAs location information becomes a core part of many apps, we’re seeing services such as Yahoo Fire Eagle, Google Latitude and Twitter provide a way to selectively share your location with other applications. This can provide a quick bootstrap for a new app, and separate the problem of location acquisition (via many possible devices and channels) from application concerns.

Page 16: Mobile Social Location (Web 2.0 NYC edition)

Journaling

Social location isn’t just about what’s happening right now. There’s a lot of value in building a personal dataset of meaningful location history.

Photo by littlevanities - http://flic.kr/p/6Kt6Rt

Page 17: Mobile Social Location (Web 2.0 NYC edition)

Intention sharingAt Dopplr we’ve tried to delight people with historical data, showing them the patterns in their travel history.

Intrinsic to Dopplr is another important trait, the sharing of future location plans.

Page 18: Mobile Social Location (Web 2.0 NYC edition)

GamesGames like Foursquare and Noticings build on location technology and place APIs to create a playful layer over cities.

Page 19: Mobile Social Location (Web 2.0 NYC edition)

Games

“Players are awarded points for things like spotting the first thing in a neighbourhood,

or noticing something every day for a week.”

Games like Foursquare and Noticings build on location technology and place APIs to create a playful layer over cities.

Page 20: Mobile Social Location (Web 2.0 NYC edition)

Where We Are Going

Page 21: Mobile Social Location (Web 2.0 NYC edition)

Compass

We’ve had GPS for a long time and it’s been in affordable devices for a couple of years. Manufacturers appear to have only recently recognised that an electronic compass adds a lot to the picture that the “blind” phone sees by GPS...

Page 22: Mobile Social Location (Web 2.0 NYC edition)

Augmented Reality... in particular, knowing which way a user is oriented allows more effective overlaying of information onto their local context.

Photo by Marc Wathieu - http://flic.kr/p/5ZwuhQ

Page 23: Mobile Social Location (Web 2.0 NYC edition)

RealtimeThere’s growing interest in apps that can communicate in both directions between client and server - the return of Push. Protocols like XMPP and Pubsubhubbub are providing a way for an app to push information to users in realtime based on their preferences or their current context.

Photo by Hugo! - http://flic.kr/p/2yr85

Page 24: Mobile Social Location (Web 2.0 NYC edition)

The social graph(s)Social networks are now mainstream thanks to Facebook, Flickr, Twitter and friends. The smartest location apps today are using context from the user’s social graph to influence how they display, rank and filter information.

Photo by Porter Novelli Global - http://flic.kr/p/5J95ED

Page 25: Mobile Social Location (Web 2.0 NYC edition)

SensorsThe process of making devices less blind doesn’t have to stop at GPS and compass. Projects like Nokia’s Push N900 are encouraging users to augment their devices with new sensors and capabilities using platforms like Arduino.

Photo by Rain Rabbit - http://flic.kr/p/6Y8ejj

Page 26: Mobile Social Location (Web 2.0 NYC edition)

Sensors

http://blogs.nokia.com/pushn900/

The process of making devices less blind doesn’t have to stop at GPS and compass. Projects like Nokia’s Push N900 are encouraging users to augment their devices with new sensors and capabilities using platforms like Arduino.

Photo by Rain Rabbit - http://flic.kr/p/6Y8ejj

Page 27: Mobile Social Location (Web 2.0 NYC edition)

Infoviz

We’re becoming a more information-literate culture, and information visual and data exploration tools are becoming commonplace.

Page 28: Mobile Social Location (Web 2.0 NYC edition)

Infoviz

We’re becoming a more information-literate culture, and information visual and data exploration tools are becoming commonplace.

Page 29: Mobile Social Location (Web 2.0 NYC edition)

ConcordanceA major problem when you work with disparate large datasets is mapping information from dataset to dataset. A concordance between two datasets (e.g. mapping from Yahoo’s WOE place IDs to Geonames IDs) allows us to combine data in interesting new ways.

Flickr is implicitly building sets of concordances through their machine tag integrations. A photo of a restaurant in San Francisco may have tags indicating its IDs both in Foursquare and in Dopplr. Hopefully they’ll open up this concordance data through their API eventually.

Page 30: Mobile Social Location (Web 2.0 NYC edition)

ConcordanceA major problem when you work with disparate large datasets is mapping information from dataset to dataset. A concordance between two datasets (e.g. mapping from Yahoo’s WOE place IDs to Geonames IDs) allows us to combine data in interesting new ways.

Flickr is implicitly building sets of concordances through their machine tag integrations. A photo of a restaurant in San Francisco may have tags indicating its IDs both in Foursquare and in Dopplr. Hopefully they’ll open up this concordance data through their API eventually.

Page 31: Mobile Social Location (Web 2.0 NYC edition)

PaperPaper is still a big enabler in recording and communicating data. Aaron Straup Cope is building all sorts of interesting bridges between the internet and print. http://www.aaronland.info/papernet/

Page 32: Mobile Social Location (Web 2.0 NYC edition)

Paper

The Internet has rightly been called an "architectures of participation". Paper, though, remains the most succesful and robust architecture of shared histories to date.

—Aaron Straup Cope

Paper is still a big enabler in recording and communicating data. Aaron Straup Cope is building all sorts of interesting bridges between the internet and print. http://www.aaronland.info/papernet/

Page 33: Mobile Social Location (Web 2.0 NYC edition)

Walking Papers Help improve OpenStreetMap by drawing on this map, then visithttp://walking-papers.org/print.php?id=r6vt6v3h

Map data ©2009 CC-BY-SAOpenStreetMap.org contributors

PaperMike Migurski of Stamen Studios built Walking Papers to help people annotate streets with extra detail for uploading to OpenStreetMap. After printing and recording data on this document, the 2D barcode links the map back to its original source when scanned.

Page 34: Mobile Social Location (Web 2.0 NYC edition)

Walking Papers Help improve OpenStreetMap by drawing on this map, then visithttp://walking-papers.org/print.php?id=r6vt6v3h

Map data ©2009 CC-BY-SAOpenStreetMap.org contributors

Paper

“Print maps, draw on them, scan them back in and help OpenStreetMap improve its coverage of local points of interests and street detail.”

Mike Migurski of Stamen Studios built Walking Papers to help people annotate streets with extra detail for uploading to OpenStreetMap. After printing and recording data on this document, the 2D barcode links the map back to its original source when scanned.

Page 35: Mobile Social Location (Web 2.0 NYC edition)

Careful Where You Go

Page 36: Mobile Social Location (Web 2.0 NYC edition)

OutdoorsIt’s important to be humble as a mobile developer. Never forget that your application may be used in the street, in parallel with another app or activity, and for less than 30 seconds at a time. Your app may be the irritation standing in the way of someone getting the information they need right now.

Photo by JanneM - http://flic.kr/p/6sjM3e

Page 37: Mobile Social Location (Web 2.0 NYC edition)

Data entryPhones are usually not great data entry devices. When we built the Dopplr Social Atlas mobile application, we allow users to record places they like with a minimal interaction - only two taps are required. We upload these pings to the Dopplr website and complete the data gathering through the website at a later time. This allows us to use large widgets such as maps and autocomplete that would not be practical on the small screen.

Page 38: Mobile Social Location (Web 2.0 NYC edition)

Red dot feverSchuyler Erle coined the term “red dot fever” - the naive tendency to plot datapoints on maps without thinking through the design implications. It’s very easy to fire up a map API and add markers to a map without realising how unclear the representation can become. Information can often be processed by clustering or filtering before being mapped. Indeed, maps aren’t always the best representation of place data.

Page 39: Mobile Social Location (Web 2.0 NYC edition)

RoamingBe aware that (particularly outside North America) many apps are used outside their phone’s home country. Roaming data charges are still disturbingly high and not everyone is organised enough to swap SIM cards at the airport when they travel. Be conservative with your use of data.

Page 40: Mobile Social Location (Web 2.0 NYC edition)

“35 ways to find your location”

There’s a great set of slides from Chris Heathcote reminding us that GPS isn’t the only way to find your location. There are many other technical and cultural approaches.

http://conferences.oreillynet.com/cs/et2004/view/e_sess/4657

Page 41: Mobile Social Location (Web 2.0 NYC edition)

“35 ways to find your location”

Chris Heathcote, Etech 2004

There’s a great set of slides from Chris Heathcote reminding us that GPS isn’t the only way to find your location. There are many other technical and cultural approaches.

http://conferences.oreillynet.com/cs/et2004/view/e_sess/4657

Page 42: Mobile Social Location (Web 2.0 NYC edition)

What Will Get Us There

Page 43: Mobile Social Location (Web 2.0 NYC edition)

http://www.geonames.org/

Open datasets such as GeoNames can be the backbone of a city-based app. It has millions of lat/long points for cities all over the world. We couldn’t have built Dopplr without Geonames.

Page 44: Mobile Social Location (Web 2.0 NYC edition)

OpenStreetMapThe collaboratively-produced OpenStreetMap project is now an amazingly rich source of street levels maps.

Page 45: Mobile Social Location (Web 2.0 NYC edition)

Maps From Scratch

http://www.mapsfromscratch.com/ provides Amazon EC2 images that boot into a precompiled environment designed for processing geo data. Hard to compile libraries are preconfigured and immediately available.

Page 46: Mobile Social Location (Web 2.0 NYC edition)

clustrFlickr’s opensource clustr tool can turn any set of lat/long points into regions. It was created to turn collections of tagged photo locations into neighbourhoods. As an experiment I clustered all the places in London that my network on Dopplr has visited. The resulting regions show the shape of “our” London.

http://code.flickr.com/blog/tag/clustr/

Page 47: Mobile Social Location (Web 2.0 NYC edition)

http://jung.sourceforge.net/

There’s a lot of hard computer science around processing graphs. The Jung library makes this a lot easier.

Page 48: Mobile Social Location (Web 2.0 NYC edition)

http://lucene.apache.org/mahout/

There’s also a lot of hard computer science around machine learning. Mahout is building scalable Hadoop-based libraries for recommendation, clustering, collaborative filter and auto-classification.

Page 49: Mobile Social Location (Web 2.0 NYC edition)

http://lucene.apache.org/mahout/

“scalable, Apache licensed machine learning libraries”

There’s also a lot of hard computer science around machine learning. Mahout is building scalable Hadoop-based libraries for recommendation, clustering, collaborative filter and auto-classification.

Page 50: Mobile Social Location (Web 2.0 NYC edition)

Thank YouMatt Biddulph, Nokia

Web 2.0 NYC 2009


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