Like many industries, mapping (or more specifically, data) has its colorful characters and unusual conferences–there’s ZIP code guy (knows demographics for seemingly every ZIP), addressing guy (a better way to define addressing for more efficient mail delivery), parcel map guy (yes, that’s his bag) and a host of other characters.

But the top has just been blown off all this…

Enter the sub-sub-sub market segment of mapping: neighborhood boundaries. UMI’s customer list is well-known and we continue to enhance the product by employing thousands of sources, many of them deployed on the ground. We expand geographic coverage, augment the data model and spend a great deal of time listening to customer needs. We didn’t inherit or acquire a legacy database from anybody. All our work is our own.

Consider reading the Wired article to get a sense of some ‘friction’ between competing firms. It says it all. Umibot takes issue with one factual point:

Since Wahl pioneered the industry four years ago…

That’s not quite correct. Not sure if ‘pioneering’ means shouting in the forest, but UMI’s fearless leader, Ian White, certainly first commercialized a neighborhood boundary database.

Just clarifying the record…

Google recently announced its Map Maker tool, (in the words of OSM) “a kind of faux Open Street Map.” On the surface, the idea is clear–have users make contributions, as they know local geography better than anybody else. An excerpt from the OSM blog post today:

Like Knol, the mooted ‘wikipedia killer’, Google refuse to acknowledge existing communities, trample on their hard work and lack the mindset to engage with an open project.

But, this really doesn’t matter.

What’s fascinating is that they haven’t set themselves up against OpenStreetMap so much but rather TeleAtlas/TomTom, NAVTEQ/Nokia and AND. This is really a swipe at things like TomTom’s MapShare(TM) and ANDs Map 2.0. The question is now going to be, when do they switch on editing of existing data markets, if at all? Only those with intimate knowledge of the contracts will know.

The fundamental reasons for OpenStreetMap remain intact and if anything are now stronger. At first glance it sounds like OpenStreetMap, until you realise that Google own that data you give them, there’s no community and you are unlikely to see use of the data in ‘creative, productive, or unexpected ways’.

The pattern with Google is by now well-understood. Given their massive scale, subsidizing such efforts is trivial. Gmail, Google Apps and other products follow this model. It won’t have any kind of material impact in the immediate future, and that’s why the US airline industry ignored jetBlue. Whoops.

Umibot’s not preaching conspiratorial here–what Google is doing is great for satisficing the masses–much of the nuance is lost, but in return millions of users get something they can use. Of course they don’t own that contribution and Google (and of course others exist) is able to build out more page views, resulting in more advertising, more revenue, and so on…

Urban Mapping now finds its first customer competing against our first product. It isn’t that Google can do neighborhoods ‘better’ than UMI (or anybody else), it’s the idea that Google doesn’t need anybody else to do it for them. In fact, they don’t need to do it themselves–throw it over to a fanatical user base, and watch them diligently work away, and allow the new Microsoft to reap the rewards. If Umibot were a thinking human, no doubt it would be saying “these guys are smart.”

A few months ago Yahoo! announced it had incorporated neighborhood search into Local and other properties. We’re pleased to say this is brought to you by Umibot and the hard-working team at Urban Mapping, so Yahoo! can now enjoy the same neighborhood goodness as many of our other satisfied customers.

Here’s the official news.

UMI’s own Ian White will share the podium with several yet-to-be-determined panelists at the SMX Local & Mobile conference in San Francisco July 24-25 at the Marriott Hotel. The panel, Monetizing Local & Mobile: Who’s Making Money, is bound to be provocative if past panels are any indication.

As in, literally…

Today we’re excited to announce a partnership with Intelligent Direct, the market leader of custom print and data solutions for business. Through publication of custom electronic and printed maps of all sizes, companies can better manage the impact of location, geography and demographics.

Urban Mapping’s neighborhood boundary database will be incorporated into custom solutions. IDI’s MarketMAPS division has served thousands of clients in its 25+ year history.

Umibot is most excited about the offline possibilities. Even though it’s not clear if a bot can exist in the real world, there’s no question direct marketing does. And it’s huge. And small/medium-sized businesses think about overall marketing impacts and budgets, not segmenting by channel. This announcement is the first of several to link interactive and direct marketing efforts.

-The official news

This just in…Umibot is pleased to announce a few enhancements to our Neighborhood REST API…

In addition to our significantly-increased neighborhood coverage
we’ve responded to developer requests and enhanced the REST API’s getNeighborhoodByLatLng to offer the option to return zero-to-one results, as opposed to the default zero-to-n results.

Why does this matter? Particularly in urban areas, neighborhood boundaries are organic, complex and because they are culturally defined phenomena. They are often with overlapping and/or hierarchical, and sometimes vague spatial relationships.

If you are enabling local search for your records, associating them with multiple neighborhoods will provide your users with more search options. However, some application developers want to know the neighborhood for a particular location. For this case, users can rely on our algorithms to take into account the underlying spatial relationships and geometries of all the neighborhoods which include the point to provide the best answer in response.

A final minor enhancement:, we have added ‘distance’ field to the result of ‘getNearestNeighborhood’ representing the distance to the centroid.

[Background Music: Begin Dirge]

Please note that we are deprecating the SOAP API. We have observed that the complexity of SOAP clients causes far more headaches for our end users, and our development overhead is not insignificant. As a small team, we have decided to focus our energy on expanding our coverage, and enhancing the REST API in response to user feedback. If you haven’t already, we encourage you to move over to REST.

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:

• 22% of transit stations have bathrooms (they may not be operable/accessible, but they exist)

• 35% of transit stations have dedicated parking

FYI: Wire release

Umibot’s been overclocking the past few weeks, and for good reason. Today Urban Mapping passed a new milestone and is thrilled to announce boundary data for more than 40,000 neighborhoods in the US. In addition, UMI continues to increase coverage across Canada and European countries, bringing our global coverage to more than 50,000 neighborhoods across 2,000+ cities and 15+ countries. Users of our enterprise and web services delivery can tap into this collective pool of rich local knowledge. A new shiny map of the Continental US displaying coverage:

Some more great things in store over the next several weeks (including an announcement at Where2.0 next week), so ensure you are RSS-compliant!

Official news release

On Day Two of the Kelsey Group’s DDL conference here in Seattle, Zillow’s Rich Barton gave a keynote address about his three Big Ideas where information asymmetry presents significant opportunity for business model disruption: travel, legal services and real estate, or as he says, “storming the Bastille.” Umibot knows that Rich has obviously proven himself as a successful entrepreneur but wants to clarify a few points he made (and I thank my master for giving me my AI that allowed me to ‘know’ this).

Zillow’s neighborhood database has 7,000 neighborhoods covering approximately 150 US cities.

UMI’s neighborhood boundary database contains almost 40,000 neighborhoods across 1,200 towns and cities in the US (plus additional Canadian and European coverage), and we continue to add additional neighborhood coverage on a regular basis.

Rich said Zillow’s neighborhood boundary data is available via an API. I believe he misspoke. Certainly Zillow offers an API, but I don’t believe it offers neighborhood boundary data (although this could certainly be done).

UMI offers a fully robust API, allowing us to offer neighborhood-level geocoding via web services using REST.

Zillow’s boundaries are generally drawn around census tracts and postal codes

UMI’s neighborhood boundaries conform to how users (not direct marketers or actuaries) understand neighborhoods–postal codes and other administrative/political boundaries bear little relationship to neighborhoods, as this search reveals.

There’s more to this story, but the above is probably enough for the non-obsessed to chew on.

Urban Mapping’s own (guess who) Ian White will participate at MediaPost’s Search Insider Summit May 18-21 on Captiva Island, FL. Ian will participate on several panel discussions and breakout sessions. Umibot is thrilled that UMI will be at the event as it will provide a good opportunity to take the pulse of search engine marketing and local search.