Crowdsourced GIS Data

April 20, 2010 By: Eric Gakstatter

Crowdsourcing is a hot topic in the geospatial world and rightly so. The geospatial engines (Google Earth, Bing Maps, ArcGIS, gobs of LBS apps, etc.) are starving for data. They are like Formula 1 race cars trying to go faster and faster around the circuit. They have powerful engines, but geospatial data is the fuel and the fuel is expensive.

If one looks at the big picture of geospatial data collection, at one end of the spectrum are companies or organizations that finance the collection of geospatial data themselves. Think about how Navteq and TeleAtlas (more specifically their derivative companies) started their efforts a couple of decades ago. There was very little digital street and address data available so their digital maps had to be created, more or less, from scratch.

Over the past decade, more and more digital geospatial data has become available, mostly via government-financed efforts, and it has been a tremendous resource for companies to develop geospatial applications that don’t have the resources to collect digital geospatial data needed for their engines. Initiatives such as the U.S. geodata.gov portal and others make sourcing digital geospatial data possible and easier than ever before. But that’s not enough.

Source: geodata.gov

The reason we are hearing more about crowdsourced data is because just mining existing geospatial data off of the web isn’t enough to feed the hungry geospatial engines any longer.

Video describing crowdsourcing (3 min.)

Crowdsourced data is data collected and reported by the user community. Crowdsourced data collection is largely driven by the consumer market due to mobile phone LBS applications. It makes a lot of sense if the data can be processed and verified reasonably well. I’ll give you an example.

One of the earlier crowdsourced efforts was launched by TomTom in 2007. TomTom is a maker of GPS navigation devices used in automobiles, motorcycles, etc. A core part of any GPS navigation device is the map database. Without the map database, the GPS navigation device is useless. Furthermore, the quality of the map database reflects on the quality of the GPS navigation device. For example, if the GPS device instructs you to turn left when you know there is a better route, the typical consumer blames the GPS device, not the real culprit, which is the map database (or the routing algorithm). Ensuring maps are current and correct is a challenge for all GPS device makers. Typically, GPS deveice manufacturers rely on one of the two major map database providers in the world, Navteq or TeleAtlas. TomTom primarily uses TeleAtlas and was at the mercy of the TeleAtlas updates. It’s a huge effort for Navteq and TeleAtlas to ensure their databases current and correct.

One of TomTom’s solutions to this problem was crowdsourcing. Instead of relying on TeleAtlas’s organic effort to maintain its map database, TomTom turned to its customers and created an initiative called Map Share. Map Share is a portal that allows TomTom users to report map errors and new map features. Within seven months of launching the Map Share program, TomTom reported that it received the one millionth map improvement upload.

I think the challenge of any crowdsource data collection effort is to make it very easy for users to report data. In TomTom’s case, there’s a menu item on the GPS device so the user can enter data immediately as they experience the error. It would be naïve to hope that users would make the effort to report the error via their personal computer when they arrived at home.

In the case of TomTom’s Map Share program, the users have a vested interest in improving the product. Users will benefit from their reports and also from other users' reports at no cost. This crowdsourcing strategy seems to work.

What about crowdsourcing in traditional GIS?

I read a blog from Accela Product Manager Brian Wienke this week where he writes about crowdsourcing at the municipality level. For example, how does a municipal public works department know when there’s a sidewalk in need of repair? Either a city employee sees it and reports it or a citizen reports it. If a citizen wants to report it, typically they call City Hall and presumably they reach the correct person who jots down the information, it gets placed in the work order file, entered into the work order system, and then a crew is dispatched to repair the problem.

In Wienke’s scenario, a citizen would have an application installed on his or her mobile phone that would interface with the public works department. The GPS-enabled mobile phone would record the location of the problem; the citizen would enter information about the problem and perhaps even shoot a photo or video of the problem. When sent to the public works department, it would be automatically entered into the work order system and scheduled for dispatch.

The challenge

Crowdsourcing data collection is a super-powerful way of collecting a massive amount of data. The upside is clear, whether it’s reporting the streets of a new subdivision in town or a defective sidewalk. In the end, it results in more data being available so people can make faster and better decisions.

The challenge with this scenario, and crowdsourcing in general at any level, is motivating the user. The majority of citizens who walk on that same defective sidewalk everyday will not take any action. Some that do take action will do so by calling the public works department. A tiny sliver of users might be motivated enough to install an application such as what Wienke describes. It might end up being that the tiny sliver of users end up driving the crowdsourcing effort. In fact, it might even be the youngest generation, today’s teenagers, who are growing up with mobile phones in their pockets that end up being the gem of crowdsourcing data collection.

GITA and ACSM conferences next week

I’ll be blogging and such from the Geospatial Infrastructure Technology Association (GITA) annual conference and American Congress on Surveying and Mapping (ACSM) annual conference next week in Phoenix, Arizona. In addition to presenting at both conferences, I’ve got a number of interviews scheduled with interesting people. Follow my blog on the Geospatial Solution’s website Live Event Blog area.

Thanks, and see you next week.

Follow me on Twitter at http://twitter.com/GPSGIS_Eric