Suddenly it is all so clear: The next big corporate race is going to be getting the biggest mobile crowdsourcing network.
It’s been obvious for a little while that mobile location-aware communications devices like the Nokia N95 will be ubiquitous five years from now — they’re the Star Trek Tricorder meme made real (though the UI will look more like the iPhone’s, I hope). What wasn’t so obvious (at least to me, until this week) is that these devices will make great georeferenced information collection networks, perfect for data-mining. The corporate challenge: Building, buying or otherwise gaining access to such a network.
The evidence (and a blind alley):
There have been two acquisitions that have been widely reported in the GIS-o-sphere this past week: GPS device maker TomTom’s planned acquisition of digital mapping company Tele Atlas and Google’s acquisition of aerial imagery provider ImageAmerica.
(Google’s purchase has generated a lot of press but is the least relevant to this story: The company has been renting the services of aerial digital imagery providers (in the US and also in Australia) and I suspect it is just cheaper to own the planes and cameras if you plan on updating the most viewed regions more often. It’s a logical next step in Google’s mapping mission: it increases their ability to generate new imagery quickly without having to depend on a third party to allocate resources as they see fit. (That, and Google Earth CTO Michael Jones loves gigapixel cameras:-) )
The TomTom-Tele Atlas merger presages the coming of such geospatial collection networks, and newly minted Googler Ed Parsons sees its implications right away:
Without community generated content, in a online future it will not be possible to provide the expected level of currency of data – Strong stuff but hard to argue with.
Daily Wireless excerpts a Newsweek article that struck me: Both Tele Atlas and competitor NAVTEQ already employ hundreds of “road warriors” in the field to gather data that satellites can’t catch: traffic signs, one-way streets, points of interest…
“At the end of the day, there’s no substitute for going out there and capturing the real world ourselves,” says Navteq CEO Judson Green.
How to scale that? Build a crowdsourcing network, so that others can capture the real world for you — using devices that companies like TomTom (and Garmin, and Nokia) can build.
Geospatial crowdsourcing already has a impressive working example: OpenStreetMap.org, where you can (manually) upload your own GPS tracks to create a collective world road map or edit existing data. And now it turns out that Google has been piloting something similar in India, as explained by Michael Jones last week at a conference. Dan Karran has transcribed the relevant bit of Michael Jones’s talk:
We have a pilot program running in India. We’ve done about 50 cities now, in their completeness, with driving directions and everything – completely done by having locals use some software we haven’t released publicly to draw their city on top of our photo imagery.
From static to live
So far we’ve only been looking at collecting data with a long half life, such as the locations of gas stations and roundabouts. But when there are enough human “sensors” in the network, Michael Jones explains,
[…] it has the advantage of, when the road is closed, you can click on that road and say it’s closed today. If you’re having a block party, you can say the block is closed this day. Traffic data that’s up to date every day.”
Google’s solution doesn’t (yet) involve the use of a mobile gadget to contribute live data, but such solutions already exist elsewhere. Already in 2006, new Honda Civics driving on Japan’s roads could wirelessly upload live telematics data to a central server to calculate road congestion. For a fee, you can get that information delivered to your car dashboard.
Getting location-aware mobile devices to contribute data to such networks means less work for humans, as there is no need to manually georeference the data. The easiest milestone on this road (pardon the pun) is live traffic reporting, as it doesn’t require the active participation of a human beyond driving. In the future, if TomsTom get the ability to transmit live telemetrics on busy highways via wireless data networks, you might start saving lives if a traffic accident in dense fog involving a TomTom-equipped car is reported in time to those following soon after.
Traffic monitoring may be a special case — cars are nearly always in the line of sight of GPS devices, whereas humans are more often than not inside, or in a concrete city canyon. So how to get humans to actively contribute to a georeferenced crowdsourcing network, other than by paying them, which isn’t scalable? You could appeal to their nobler selves (the open source model), you could make it fun (Google Earth Community), or you could appeal to baser motives — let the contributor get something out of it, such as access to the collective wisdom of the network (for example, to find the rooms with the best views in hotels as reported by previous visitors). But above all, it should be easy for the contributor.
This is where this week’s under-reported acquisition plays a part: Nokia bought Twango. Twango is a media sharing web application for mobile devices. Unlike its main competitor Shozu, which offers to forward your media to your web sharing app of choice (such as YouTube, Flickr and others), Twango wants you to store all your media in one place, on its servers, and share it using its URLs as a destination. With Twango soon installed by default on new Nokias mobiles, Nokia will be making a play to capture the generated media of its hundreds of millions of mobile phone users, so that network effects are its to dispense — with uploaded videos and photos providing eyeballs to advertisers.
Shozu gives users more choice when it comes to which network they want to contribute to, and I hope that this is the model that catches on, as it is in the users’ best interests to have device agnosticism when it comes to networks, and network agnosticism when it comes to devices. Meanwhile, Shozu already georeferences images for you if you have a GPS-enabled phone, though presumably Twango will soon follow — at the moment you have to tag for places manually.
So: Car navigation devices are going to communicate data in both directions, live; mobile phone manufacturers are going to load their phones with default software in a bid to capture and host the generated media; and other network web apps are going make sure they have APIs to which these devices can post, perhaps even automatically. With Nokia’s GPS phones already providing a fee-based navigation service, it’s inevitable that all these manufacturers are converging on devices with similar functionality, while the information gathered from these gadgets is going to be valuable to whoever gets access to them.