May 23rd, 2010
We’re thrilled to announce that CoSstar Group, the leading provider of commercial real estate research and information services, has implemented Urban Mapping’s hosted mapping services. In record time, CoStar leveraged Mapfluence to incorporate public transportation data into their web-based platform. The rapid development time and ease of implementation are further evidence that hosted mapping services are here to stay.
In the screen shot below, CoStar used Bing Maps for a base map API and Mapfluence elegantly renders cartographically-pleasing transit lines, stations and detailed attributes on a map for the Washington DC area. Urban Mapping’s mass transit data is available for fixed rail (subway, commuter, light, long haul) across North America and several European countries. The difficulty in creating a visually satisfying solution that can be created algorithmically cannot be overstated–rail systems are unique and each one has its own quirks. We’ve done a great deal of tweaking to best represent rail maps in the way that locals expect them to look–an even more refined version is in the works and will be available very soon.
In addition to visually delineating transit lines/stations on a map, CoStar incorporates UMI’s mass transit data into the property search function. As the screen shot below indicates, a subscriber can create a transit-based time or distance constraint. This allows for would-be tenants to search for available property that is (say) only within a five minute walk of a commuter rail station.
In this property profile view, the individual listing is annotated with proximity to nearby public transportation and airport info. Our Mass Transit Proximity API easily allows customers to code property listings (or any location) with proximity to train stations.
Tags: bing, customers, mapfluence, maps, mass transit
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July 14th, 2009
Today we announced several advanced features of Routeserver, Urban Mapping’s multi-modal routing engine (supports rail, walk, bus, bike, ferry). One of the features we’ve been working on plays into cognitive psychology, something we’ve researched for other products. Urban Mapping doesn’t profess to be a domain expert, but by applying existing research to our field of work, we are able to come up innovative products and features from time to time.
The executive summary of the latest goes something like this: perception of time does not follow ‘actual’ time; in computing, the (technical) cost of completing a journey (by automobile, walking, transit, etc…) is a function of the number of transfer points/nodes, modes of travel, travel time/schedule and route-segment attributes (average speed, express v local, elevator v stair, etc…). The psychology of waiting can be easily understood. An oft-cited (and possible urban myth) puts it well in an article from the esteemed Harvard Business School:
What do you do when you’re waiting for a slow elevator?
A number of years ago, a company that had just built a major building realized their elevators were intolerably slow. What to do? It was too expensive to reengineer the elevators. After thinking about the problem for a while, mirrors were installed in the lobby and elevators. It turns out that people will tolerate a much longer wait if they can see themselves in a mirror.
Today, most tall buildings have mirrors or polished metal surfaces in their lobbies and elevators.
Routeserver now does something similar with transit routing–standing and waiting for a bus/train/stop light has a longer perceived duration, despite the fact that it may actually be of shorter duration. Academic research (for example) has verified this, and common sense seconds the motion. So there you have it. Routing–have it your way!
Tags: mass transit, multimodal, routeserver, routing
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February 2nd, 2009
Since everybody loves free (especially in the current economic climate), we decided to offer more free products. Today we’re announcing the Free Mass Transit Proximity API–this product was announced last November, and it enables developers to use location in (more) interesting ways: associate ad address with subway/bus/train station name, distance and other attributes. Or open your mobile phone and ping our API to tell you the closest train station to your location.
You can register as a developer, read more about the Mass Transit Proximity API and sign up for a key at our developer portal.
Tags: api, gps, mass transit, mobile phone
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December 16th, 2008
O’Reilly Radar with a post about Google Transit, pgRouting, OSM and other developments in the world of mass transit data. Unfortunately, Jim didn’t get the complete picture, so Umibot provided an extended comment in the post, appearing below with links for enhanced reading pleasure.
I’m glad you made this post, but a bit disappointed it has such a narrow perspective. I like Andrew Turner lots, but to take him as the definitive source for all things transit-related is a *bit* of a reach.
Urban Mapping has been doing a whole heck of a lot of work in this area, with some pieces announced. We have detailed data and schedule-related info for around 70 public transportation systems (note: link not current!). This is mostly US-focused, but we’re rapidly expanding coverage in Europe.
First response is to data. GTFS has been invaluable in raising awareness, but make no mistake, Google does little of the work in data. With the exception of NYC’s MTA, agencies provide data to Google in the prescribed format. Google collects this data, tests it, then dumps it into their routing engine/index and millions of people can enjoy. There are 70 or so agencies that participate in Google Transit, yet only 10 or so make the data available to anybody else. In fact, an agency cannot make selective disclosure and *must* make it available to all (but compelling one to do this may involve unnecessary time and expense).
Because data is not made available to Google (or anybody else) does not mean data is not available. I spoke about this at the Where2.0 conference several years ago in my talk “How Open Is Open?” It means that companies have to actually do work to get it. Urban Mapping has a developed a massive inventory of spatial, attribute and schedule data, the vast majority of which we source the old fashioned way–on the ground research. Collecting, normalizing and maintaining this base of data is no easy task, especially when data at the detail of a subway entrance is required.
But data is (relatively) useless on its own, so we’ve made a significant investment in the Graphserver project. Now *this* is compelling–an open source, super-fast engine with a small memory footprint that can ingest GTFS or whatever schedules you like. We’ve been testing this engine with customers and have performed multimodal (walking, driving, inter-agency) lickety-split. If you want to build applications, graphserver is *the* place to be (but don’t worry, UMI will also offer hosted solutions).
Finally, a schedule is relatively useless unless a train (or bus, etc…) sticks to depart/arrive times. But they don’t…so updates/alerts/notifications become of paramount importance. Urban Mapping has also developed a method to poll and ingest the 1000s of incidents and associate them with the relevant IDs. This info is pushed out via a feed, so UMI data subscribers can rest assured their data is the freshest it can be.
And there’s much much more going on. The advent of ITS has raised awareness (and federal $$) to upgrade, experiment and partner with industry in novel ways. UMI will be announcing some unique initiatives in the coming months, and others will also continue to push this along.
Tags: google transit, GTFS, mass transit, oreilly, UMIFS
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September 11th, 2008
Urban Mapping is a proud sponsor of TransitCamp (why no space?), which actually has its roots in BarCamp, and descends from the old metasyntactic variable. TransitCamp takes place this Saturday, September 13 at the SamTrans offices in San Carlos, CA. We’re supporting this event because mass transit is the next big thing. UMI’s going all in. We’ve announced some of our transit initiative, but there is much, much more under the hood and it will be announced in the very near future.
Tags: mass transit, subways, transit data, web2.0
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July 31st, 2008
Urban Mapping’s own Ian White will participate on a panel discussion about alternative markets for navigation products. We’ll have lots more to say at this event about mass transit navigation and other non-automobile products. The conference is October 7-8 in Eindhoven, Holland.
Tags: conferences, gps, mass transit, navigation, subway
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May 14th, 2008
Phew! After more than a year in development and two years deep in Umibot’s RAM, today we unveil a grand plan: normalized mass transit data for (today) 53 public transportation systems in the US, Canada and UK. To get here we had to develop other pieces–a data intake platform and a schema. Some more info on all of these:
Web-based Mass Transit Data Intake Platform (no acronym yet) Umibot believes the greatest cost in data collection is identifying and purging the system of dirty data. By auto-validating data at point of input, we’re able to significantly reduce this cost. UMI’s proprietary web-based platform is flexible and captures the vast collection of spatial and attribute data we manage. This includes things like routes, station footprints, exits (you can’t generally exit at a ‘station’), hours of operation, handicap accessibility, elevator location, amenities (retail, bathroom, telephone, etc…) and a great deal more. We then associate this attribute data with the ‘spine’ of spatial data and then compute a graph network, making the data ‘routing ready’ across a variety of platforms.
Transit agencies can take advantage of this platform by using UMI’s infrastructure as a platform to inventory their own data. It’s a well-known fact that transit agencies face bureaucratic, technical and legal challenges to releasing data, and this platform is one more reason for transit agencies to partner with industry to increase data distribution and support increased ridership by driving awareness.
Normalized schema
Before we began data collection, a uniform schema that recognizes transit nuances and complexities needed to be developed. For example, scheduling for the London Tube operates on a headway, meaning trains depart every Xish minutes. New York’s MTA operates on a tabular schedule, with scheduled departure times. Sounds like a detail, and it that’s exactly what it is–multiply this nuance 100 times and there’s a great deal of data definition that matters. What we’ve developed is internal to UMI and offers tremendous flexibility to add new mode types (ferry, funicular, etc). It has nothing to do with the output customers receive, and we’ll have more news about that soon.
Coverage The map below reflects current US coverage. Across the 53 transit systems, UMI has defined over 14,000 individual stations and over 100,000 data attributes. Stay tuned for increased coverage, attributes, service delivery and partnerships!
And some fun transit statistics for current coverage:
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22% of transit stations have bathrooms (they may not be operable/accessible, but they exist)
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35% of transit stations have dedicated parking
FYI: Wire release
Tags: geolocation, geotargeting, google transit, local search, mass transit, neighborhood database, pressworthy, public transportation data, transit data
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April 5th, 2008
Umibot recently caught up with a few favorite blogs, including the -ist family. In not so unbelievable, yet simultaneously incredible fashion, here is the change of service announcement from hell.
Umibot may not be human, but he still understands that too many facts in too short a space equals too much confusion….Information anxiety, for sure. Stay tuned for UMI’s Urbanware Transit product–a fully robust and highly-structured database of mass transit systems.
Thanks Gothamist
Tags: geodata, local search, mass transit, mta, musings, new york city transit, subway, subway data, urban rail
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March 14th, 2008
It happened a few weeks ago, but Umibot is just now getting around to posting…UMI is one of 15 companies nominated for the semi-finals of the annual NAVTEQ Global LBS Challenge. We aren’t sure how many entrants there were, but we are privileged to be included in this group.
The UMI application is based on the highly structured data than comprises our Urbanware: Mass Transit data product. Built on the where.com platform, Urban Mapping was able to quickly develop for mobile using uLocate’s location-aware platform.
Finalists will be announced April 2 in Las Vegas during CTIA Wireless.
Tags: conferences, data, local search, mass transit, neighborhoods, pressworthy, transit data, where.com
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October 16th, 2007
How many times have you emerged from a New York City subway station, only to feel turned-around and out of sorts? Although Umibot is the pinnacle of logic, we understand how people get caught up in spatial confusion-land–especially in complex urban environments like NYC.
This project, courtesy of the Grand Central Partnership and the NYC DoT, aims to put floor decals outside Grand Central Station-area MTA exits that indicate which direction is East, Downtown, etc…
It isn’t intended as a system-wide project as the GCP is a NYC Business Improvement District, but perhaps city agencies will get involved. Umibot likes this initiative as it acknowledges the highly personal, and very confusing nature of urban navigation–the very things that Urban Mapping seeks to address through its print and digital products.
from Gothamist
Tags: grand central station, manhattan, mass transit, mta, musings, new york city, spatial cognition, subway, wayfinding
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