7. Street data
We’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
8. Ratings and Reviews
There 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.
9. Mobile Content
In 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.
12. Navigation
Turn-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
13. Checking in
If we can translate a user’s location into something meaningful, we can add layers of
information on top.
14. Checking in
Lots of interesting apps are based around the idea of “checking in” at a location rather than
simply recording GPS tracklogs.
15. Place, not lat/long
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
16. Place, not lat/long
“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
27. Location brokers
As 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.
28. 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...
29. 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
30. Sensors
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
31. http://blogs.nokia.com/pushn900/
Sensors
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
32. Visualisation
We’re becoming a more information-literate culture, and information visual and data
exploration tools are becoming commonplace.
33. Visualisation
We’re becoming a more information-literate culture, and information visual and data
exploration tools are becoming commonplace.
34. Realtime
There’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
35.
36. The social graph(s)
bopuc
moia tominsam mattb
moleitau
See http://www.hackdiary.com/2010/02/10/algorithmic-recruitment-with-github/ for this
section
42. http://gephi.org/
http://measuringmeasures.com
http://jung.sourceforge.net/
There’s a lot of hard computer science around processing graphs. The Jung library makes this
a lot easier.
44. 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.
45. “scalable, Apache licensed machine learning libraries”
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.
47. Red dot fever
Schuyler 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.
