February 23, 2009
Urban Mapping Goes Everywhere it Matters
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Susan Smith, Managing Editor
Urban Mapping Goes Everywhere it Matters
By Susan Smith
Taking the place of traditional IP based geotargeting, Urban Mapping is a company with a very clear focus on location based advertising. CEO Ian White attests to the fact that local search in the interactive world is “very difficult to solve,” and local knowledge “doesn’t scale in any way.”
Founded in 2006, the company now has nine employees. One way White thinks their product can be described is as a “faster, cheaper, better NAVTEQ.”
What does Urban Mapping do differently? They are interested in urban areas, ones that require a lot of detail and because the data is perishable, require a lot of maintenance. With a team of researchers, they develop new products and go out in the field to collect data. “There’s no substitute for that,” claims White.
Core products offered include:
The Urban Mapping Neighborhood database is a collection of “informally defined terms,” according to White, because as he describes it, neighborhoods fall under the category of informally defined space not centrally defined.
“In an urban environment, this is how somebody really understands where they are in their context,” says White. “A postal code might be sufficient if it meant something to us, but the granularity is too coarse. So a postal code may represent a few square miles whereas neighborhoods need to be more tightly defined. So 10004 where I used to live in NYC means something only because that’s what my postal code was but I don’t know what it’s bound in by. ‘Coffee in SoHo’ would make more sense for me than ‘10004.’ So all these kinds of terms SoHo, downtown, TriBeca French Riviera, the great Midwest, Motown, these are all synonyms, vanity names, etc. and they serve as a
proxy for a geographic state.”
White adds that the problem is these identifiers are hard to find because the boundaries aren’t known by any one party. “We define them and we’re the first to do it.” Customers include Google, Yahoo, Microsoft, MapQuest, YellowPages.com and many others.
The application can also be used for its search functionality. Coffee in SoHo means a great deal for people with a mobile phone. If you want to meet someone for dinner for example, the neighborhood database can offer a lat long of restaurant locations in say, TriBeca, in a way that a postal code cannot. A postal code is merely an artificial construct designed to deliver mail.
Urban Mapping logs into all the major portals with the Neighborhood database, and coverage extends through the U.S., Canada and Europe, “everywhere it matters,” which essentially focuses on urban areas.
White says that they don’t simply define regions and package them up, because there are overlaps between neighborhoods such as SoHo and NoHo and no clearly defined boundaries. For real estate listings, a property could appear both in SoHo and NoHo listings, for example. This way the user gets what he or she wants, and the advertisers and listing agents will also be happier. The user can conduct a search and get relevant results based on their query.
The Neighborhood database also includes hierarchical relationships, such as the fact that SoHo is a child neighborhood of downtown.
The Neighborhood database is available in two ways: 1) Urban Mapping can ship a database to a customer periodically and charge a flat fee, or 2) a transactional model whereby customers have access to an API which does all the geoprocessing for the them, for those customers who have little or no experience with GIS.
The service is useful for mobile users. For social networking such as Facebook users, users can reveal their location to their friends, and choose to do so revealing lat long, address where they are located now, plus neighborhood, city, etc. It’s also possible to keep a level of privacy with some friends so that the user doesn’t reveal his or her location to them.
Recently Urban Mapping announced free access for a limited number of transactions to the API. They also introduced a free Mass Transit Proximity API. The Proximity API is similar to the Neighborhood API in that if the user sends a point to the database, it will return the corresponding attributes about that train station or line, with times, etc. If a user has a list of properties or restaurants they can send them to the database and it will return associated information about them. This allows the user to construct an application and do directory searches for train stations, real estate or other needs based on requirements such as how far the user wants to walk, and whether the train
station is accessible by wheelchair, etc.
“Routable data is shipped to customers so it can allow them to do proximity searching,” explains White. “They have all the points, if they then have the network, all the heuristics and the costs, they’re able to do routing.” White says there isn’t a commercially available routing engine for them to use, as the only one, Google Transit, doesn’t give you access to its application, and there is no API for transit.
The basis for the mass transit routing database is an open source routing engine Urban Mapping has developed called GraphServer, which builds out a network graph based on Graph theory. Urban Mapping doesn’t own GraphServer as it is an open source application, but they are heavily invested in it as they are in the business of selling data. White says that if someone uses the routing engine they are free to augment it and put it in a repository as is done with other open source software. A hosted version will allow Urban Mapping to offer multimodal routing as well, which will enable drive to the train, walk to the train, train to train, train to bus, train to bus to walk, etc. It is
easier for the customer to simply plug in, making an API, call to get a transit route. Conversely, to use GraphServer on their own, a customer would need to spend time understanding and building the infrastructure, then trying to tie it in with their existing routing engine. Multimodal routing allows customers to own their own data. It’s also possible to take the GTFS data from Google Transit and load it into GraphServer.
“Part of the value of what we offer in doing the data transit collection is it’s all been normalized so it works,” says White. “If you were to go different transit agencies on your own you’d find there are incompatibilities even with Google Transit GTFS, the way schedules are defined. It is stuff that requires field research and a lot of massaging. Each subway entrance we go to we understand if it’s handicapped, accessible hours of operations, amenities available, a lot of related components there.” Updates from different transit systems and other sources are also ingested to give timely information.
The company supports approximately 65 transit systems in North American, Canada and the UK.
The idea behind GeoMods is the geographically modified keyword used to make an explicit query. Geographically modified keywords have great value when you sum them up, according to White, though individually they don’t have much relevance.
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