At the time, most Internet businesses were keen to perpetuate extant geo-local user experiences, rather than seeing them as crude, if profitable, interim steps to something better. Nowhere was this more evident than at my former employer, Yahoo: as late as 2006, investment cases were still being pitched for either maps or local; the bulk of Yahoo’s geo engineering team resided in an entirely different country; and the mobile group had its own building with few, if any, connections to the rest of the company.

Today, entrepreneurs and execs know that local, geo, and mobile are not distinct product groups and technology stacks, but rather essential components of a unified toolset that better connects people with the world around them.

Nothing better reflects the diversity of this geo toolkit than the products on display at the recent Where 2.0 conference. The three-day event embraced the full spectrum of all things spatial: coding, licensing, marketing, daily deals, 3D visualization, and a bit of mapping thrown in for the traditionalists in the audience.

In this context I gave a short presentation on “Big Data, Big Local.” I’ve embedded the slides below. Although I anticipate receiving an award for including Borat, Homer Simpson, Bender, Winston Churchill, porn shops, kittens, surfing, and unicorns coherently in a single presentation on geo — the deck does not stand well on its own. Go figure.

I wanted therefore to provide a brief overview here, and perhaps tackle it more fully in subsequent posts. This is not intended to be a detailed argument, simply an accompanying narrative to the deck.

The general tenor of the discussion focuses upon how we have traditionally employed coordinates as the final word in how we position things and people in the physical world. The problem with this approach is that a coordinate pair lacks context — they are regular and orderly, which is great for machines, but are entirely ambiguous when used to represent more conceptual places like states, cities, stores and neighborhoods. That’s not so good for people. In fact, a single coordinate pair can be used to represent all these places, and their different associations, concurrently.

Social location has moved us toward a new form of positioning: by business or points of interest (POI). These geo-referenced entities exist across the world in an irregular and poorly typed graph, but they are rich with context. People exist and events happen at places, not coordinates — social location applications “snap” us to these nodes, and their context becomes ours.

We are stretching the traditional use of business listings beyond their limits. Looking back, however, you can see how they’ve been continuously extended to fit new models of bringing consumers and businesses closer together. You’ll soon see listings data act as hooks in the mobile payments space, and they will become increasingly pivotal in creating rich topological graphs among people, brands, and physical places.

We can do great things with business listings and POI as geo-commercial beacons, but they come with their own problems, two of which I cover in the deck. The first is a more pedestrian example of name canonicalization: stores in the same retail / restaurant chain are represented today in too many forms. The evidence presented by variants on “Subway Sandwiches” in slide 12 (below) would suggest that current data providers expend comparatively little effort normalizing this content. The problem may exist because this information is currently intended to serve an extant, limited use case — make the name discoverable using free text search and present to users — rather than drive new, data-driven markets.

The second, more important issue is that we are faced on the Internet with a multitude of electronic incarnations of one physical entity. While intended to enhance discoverability across properties, the current situation effects a near-complete inability to understand how users engage electronically with a physical place outside a single caisson such as Facebook, Twitter, or Yelp. This need is increasingly important, because URLs are now often employed as surrogates for a place — they can be resolved to machine-readable attributes and in fact act exactly like nodes in a graph of linked data.

This is a problem that requires solving, and we are tackling it at Factual. I include some topical commentaries from Chris Dixon and Albert Wenger as artillery support in slide 18:

So the problem is that we are collectively going to need this normalization, very soon. I conclude noting that Factual’s duty does not end with the creation of tab-delineated files. Instead, we are looking to create data-centric platforms that instill order on an increasingly chaotic Internet, and ensure that the result is meeting the future business needs of our contemporaries in the local space.

Related:

• Video: Tyler Bell on how big data will shape location
• Why location data is a mess, and what can be done about it
• Where the semantic web stumbled, linked data will succeed
• Toward a local syzygy: aligning deals, check-ins and places

1. Those attending to learn more about data, having recently discovered its potential.
2. Long-time data enthusiasts watching with mixed emotions as their interest is legitimized, experiencing a feeling not unlike when a band that you’ve been following for years suddenly becomes popular.

A data-oriented event like this, outside a specific vertical, could not have drawn a large crowd with this level of interest, even two years ago. Until recently, data was mainly an artifact of business processes. It now takes center stage; organizationally, data has left the IT department and become the responsibility of the product team.

Of course “data,” in its abstract sense, has not changed. But our ability to obtain, manipulate, and comprehend data certainly has. Today, data merits top billing due to a number of confluent factors, not least its increased accessibility via on-demand platforms and tools.   Server logs are the new cash-for-gold: act now to realize the neglected riches within your upper drive bay.

But the idea of “big data” as a discipline, as a conference subject, or as a business, remains in its formative years and has yet to be satisfactorily defined.  This immaturity is perhaps best illustrated by the array of language employed to define big data’s merits and its associated challenges. Commentators are employing very distinct wording to make the ill-defined idea of “big data” more familiar; their metaphors fall cleanly into three categories:

• Natural resources (“the new oil,” “goldrush” and of course “data mining”): Highlights the singular value inherent in data, tempered by the effort required to realize its potential.
• Natural disasters (“data tornado,” “data deluge,” data tidal wave”): Frames data as a problem of near-biblical scale, with subtle undertones of assured disaster if proper and timely preparations are not considered.
• Industrial devices (“data exhaust,” “firehose,” “Industrial Revolution”): A convenient grab-bag of terminologies that usually portrays data as a mechanism created and controlled by us, but one that will prove harmful if used incorrectly.

If Strata’s Birds-of-a-Feather conference sessions are anything to go by, the idea of “big data” requires the definition and scope these metaphors attempt to provide. Over lunch you could have met with like-minded delegates to discuss big data analysis, cloud computing, Wikipedia, peer-to-peer collaboration, real-time location sharing, visualization, data philanthropy, Hadoop (natch’), data mining competitions, dev ops, data tools (but “not trivial visualizations”), Cassandra, NLP, GPU computing, or health care data. There are two takeaways here: the first is that we are still figuring out what big data is and how to think about it; the second is that any alternative is probably an improvement on “big data.”

Strata is about “making data work” — the tenor of the conference was less of a “how-to” guide, and more about defining the problem and shaping the discussion. Big data is a massive opportunity; we are searching for its identity and the language to define it.

But this is not important. While OpenGraph avoids, or outright ignores, many of the problematic issues surrounding semantic annotation (see Alex Iskold’s excellent commentary on OpenGraph here on Radar), criticism focusing only on its technical purity is missing half of the equation. Facebook gets it right where other initiatives have failed. While OpenGraph is incomplete and imperfect, it is immediately usable and sympathetic with extant approaches. Most importantly, OpenGraph is one component in a wider ecosystem. Its deployment benefits are apparent to the consumer and the developer: add the metatags, get the “likes,” know your customers.

Such consumer causality is critical to the adoption of any semantic mark-up. We’ve seen it before with microformats, whose eventual popularity was driven by their ability to improve how a page is represented in search engine listings, and not by an abstract desire to structure the unstructured. Successful adoption will often entail sacrificing standardization and semantic purity for pragmatic ease-of-use; this is where the semantic web appears to have stumbled, and where linked data will most likely succeed.

Linked data intends to make the Web more interconnected and data-oriented. Beyond this outcome, the term is less rigidly defined. I would argue that linked data is more of an ethos than a standard, focused on providing context, assisting in disambiguation, and increasing serendipity within the user experience. This idea of linked data can be delivered by a number of existing components that work together on the data, platform, and application levels:

• Entity provision: Defining the who, what, where and when of the Internet, entities encapsulate meaning and provide context by type. In its most basic sense, an entity is one row in a list of things organized by type — such as people, places, or products — each with a unique identifier. Organizations that realize the benefits of linked data are releasing entities like never before, including the publication of 10,000 subject headings by the New York Times, admin regions and postcodes from the UK’s Ordnance Survey, placenames from Yahoo GeoPlanet, and the data infrastructures being created by Factual [disclosure: I've just signed on with Factual].
• Entity annotation: There are numerous formats for annotating entities when they exist in unstructured content, such as a web page or blog post. Facebook’s OpenGraph is a form of entity annotation, as are HTML5 microdata, RDFa, and microformats such as hcard. Microdata is the shiny, new player in the game, but see Evan Prodromou’s great post on RDFa v. microformats for a breakdown of these two more established approaches.
• Endpoints and Introspection: Entities contribute best to a linked data ecosystem when each is associated with a Uniform Resource Identifier (URI), an Internet-accessible, machine readable endpoint. These endpoints should provide introspection, the means to obtain the properties of that entity, including its relationship to others. For example, the Ordnance Survey URI for the “City of Southampton” is http://data.ordnancesurvey.co.uk/id/7000000000037256. Its properties can be retrieved in machine-readable format (RDF/XML,Turtle and JSON) by appending an “rdf,” “ttl,” or “json” extension to the above. To be properly open, URIs must be accessible outside a formal API and authentication mechanism, exposed to semantically-aware web crawlers and search tools such as Yahoo BOSS. Under this definition, local business URLs, for example, can serve in-part as URIs — ‘view source’ to see the semi-structured data in these listings from Yelp (using hcard and OpenGraph), and Foursquare (using microdata and OpenGraph).
• Entity extraction: Some linked data enthusiasts long for the day when all content is annotated so that it can be understood equally well by machines and humans. Until we get to that happy place, we will continue to rely on entity extraction technologies that parse unstructured content for recognizable entities, and make contextually intelligent identifications of their type and identifier. Named entity recognition (NER) is one approach that employs the above entity lists, which may also be combined with heuristic approaches designed to recognize entities that lie outside of a known entity list. Yahoo, Google and Microsoft are all hugely interested in this area, and we’ll see an increasing number of startups like Semantinet emerge with ever-improving precision and recall. If you want to see how entity extraction works first-hand, check out Reuters-owned Open Calais and experiment with their form-based tool.
• Entity concordance and crosswalking: The multitude of place namespaces illustrates how a single entity, such as a local business, will reside in multiple lists. Because the “unique” (U) in a URI is unique only to a given namespace, a world driven by linked data requires systems that explicitly match a single entity across namespaces. Examples of crosswalking services include: Placecast’s Match API, which returns the Placecast IDs of any place when supplied with an hcard equivalent; Yahoo’s Concordance, which returns the Where on Earth Identifier (WOEID) of a place using as input the place ID of one of fourteen external resources, including OpenStreetMap and Geonames; and the Guardian Content API, which allows users to search Guardian content using non-Guardian identifiers. These systems are the unsung heroes of the linked data world, facilitating interoperability by establishing links between identical entities across namespaces. Huge, unrealized value exists within these applications, and we need more of them.
• Relationships: Entities are only part of the story. The real power of the semantic web is realized in knowing how entities of different types relate to each other: actors to movies, employees to companies, politicians to donors, restaurants to neighborhoods, or brands to stores. The power of all graphs — these networks of entities — is not in the entities themselves (the nodes), but how they relate together (the edges). However, I may be alone in believing that we need to nail the problem of multiple instances of the same entity, via concordance and crosswalking, before we can tap properly into the rich vein that entity relationships offer.

The approaches outlined above combine to help publishers and application developers provide intelligent, deep and serendipitous consumer experiences. Examples include the semantic handset from Aro Mobile, the BBC’s World Cup experience, and aggregating references on your Facebook news feed.

Linked data will triumph in this space because efforts to date focus less on the how and more on the why. RDF, SPARQL, OWL, and triple stores are onerous. URIs, micro-formats, RDFa, and JSON, less so. Why invest in difficult technologies if consumer outcomes can be realized with extant tools and knowledge? We have the means to realize linked data now — the pieces of the puzzle are there and we (just) need to put them together.

Linked data is, at last, bringing the discussion around to the user. The consumer “end” trumps the semantic “means.”

Related:

• Facebook Open Graph: A new take on semantic web
• Linked data is opening 800 years of UK legal info
• Google’s Rich Snippets and the Semantic Web

This is a two-part post: here I look in more detail at check-ins, deals, and place products (including, briefly, the adventurously named Facebook Places) with an eye to what might follow. In a following post I will discuss how we may more actively ease their convergence with linked data and some basic adherence to extant standards, specifically how these efforts will affect the local consumer.

Place pages and check-ins

The check-in is hardly the apogee of the local consumer experience but it works, and this is what is most important about any product. However successful it is now, the check-in will remain an interim solution for identifying long-term customer/business affinities and physical point of presence. So what’s next?

I’ve written about check-ins previously: since then, Facebook has thrown its hat into the ring with their own place/check-in product, offering little feature distinction outside the problematic ability to check-in your friends on their behalf . Thanks to Facebook, the “Ferris Bueller Problem” — in which a friend checks you into (say) the Von Steuben Day Parade when you are officially at home, ill — may soon find its way into mainstream parlance. Expect a rise in just-for-larks in absentia check-ins to the local “gentlemen’s club” and similar places of sophomoric amusement.

More interestingly, casual requests for a similar product from LinkedIn, and the introduction of a third-party check-in offering for Twitter demonstrate that geo and social products are becoming more integrated in the mind of the consumer, and corporate product strategies: Greg Sterling remarked on this trend recently in yp.com’s new eat, play, live marketing campaign which attempts to transform the brand from its staid origins into “a lifestyle guide that also happens to feature contractors and plumbers.” He is spot-on: some lines of business will not fit within the check-in model, but they nonetheless must be accommodated in any successful business-to-consumer product.

I have no desire to see another check-in clone arrive anytime soon. Jeff Holden, the founder of Whrrl, recently noted that the check-in will shortly be a commodity, and Foursquare’s Dennis Crowley believes it already is. If you are an entrepreneur or developer thinking of building a new check-in service, please don’t. Instead, consider some of the more exciting challenges that provide real consumer benefit:

• Divorce the business from user authentication and social network: Social/local apps are entirely insular: you must be a Foursquare user using a Foursquare app (or the Foursquare API) to check into a Foursquare venue. I can see why this is, but it need not be. For example, consider an alternative platform where users supply instead an authenticated OpenID and an hcard. Authenticated user-to-venue relationships could be exposed across multiple social networks under the user’s control, and the access control list could even accommodate attribute criteria such as place type or business category. This is not simple aggregation or shimming, but a lower-level, cross-platform integration.
• Auto check-in: Manual check-ins are so 2009. Instead, think toward the endpoint where a geo-commercial footprint will be created automatically as an artifact of our day-to-day activities, should we wish it. The first steps in this direction will be toward improving the consumer’s retail experience. Shopkick is effectively an auto check-in service. Other efforts toward this end will include credit-card geo traces, perhaps combined with a “local favorites” list used to prescribe which businesses may be checked into automatically. There are critical privacy implications here, so this footprint must be controlled by users, and employed by small and medium businesses (SMBs) to engage their customers on their own terms — offering deals and events rather than advertising. As sharing your location with others becomes more codified, it will place demands on forthcoming products and start-ups that expose this under very granular, controlled conditions. This includes timestamps, geofences, disparate social networks, and leveraged venue classification.
• Micro beacons: Expect over the next two years a bloom of micro-positioning products: sensor-and-platform combinations that assist with indoor navigation (malls), determining when a user is genuinely “in store,” and guiding the consumer directly to a product on-shelf. Shopkick’s iPhone product uses the device’s microphone (simple, clever) to do this, but “Bluetooth beaconing” and QR codes are other low-energy, low-hassle options. We shall see both passive and active implementations to assist with the auto check-in and location disambiguation, depending on the particular use case.

Advances along these tracks should obviate the check-in as we know it today. This is a good thing — check-ins are something to get over, an intermediate solution to tolerate until we have something that works better. Foursquare certainly knows this. The excitement — for Foursquare’s business and users — lies wholly in their ability to deliver utility, novelty, and serendipity beyond the check-in.

Get it here: the deal

Groupon’s $134 million series C funding in April and its estimated $1.34 billion valuation woke investors and entrepreneurs to the monetary value of group buying, and local deals more generally. There are now hundreds of variants and multiple aggregators, while “Groupon clone scripts” can be purchased (caveat emptor) from any number of freelance developer sites.

Groupon and its ilk tend to get bundled under the “group buying” or less-apt “social couponing” monikers, but — in regards to Groupon certainly — there’s little that’s actively social about the products. The less charitable may argue that Groupon’s success is due as much to the severity of discounts on offer. However, Groupon and others have raised awareness that advertising is no longer the only solution. Specifically, SMBs are slowly gaining access to tools to engage their customers on mutually favorable terms. Examples:

• Just-in-time delivery: Businesses increasingly have the ability to deliver discounts, incentives, and upsells to consumers in a highly relevant, just-in-time manner. Think of services that provide attractive discounts when tables are open at a restaurant, when spare inventory is available, or the business simply requires immediate revenue to help with cashflow. These new approaches secure short-term, incremental revenue for the business and offer great value to the user. Win-win.
• Topical content: Most of these products now deliver deals based on city and zip code with little accommodation for either personal preferences or current location. Expect “relevance” to become the new watchword in deal and coupon delivery. Relevance will be obtained via platforms that exploit an accessible selection of local business favorites: Facebook is in a position to deliver, as is Hunch local, or my former shop, LikeList.
• Coupon organizers: Digital deals are big, and will become only more common as delivery channels are improved. Jim Moran, co-founder of daily deal aggregator Yipit, records more than 100 companies offering deals in the U.S. alone, most recently Yelp. With these numbers, digital deals threaten to become as unmanageable as their hardcopy equivalents. In the same way that local favorites will assist in filtering the signal from the noise in the forthcoming local clamor, I would expect that intelligent, digital coupon wallets will be employed to remind or introduce users to deals that are relevant to their immediate location and circumstance. One coupon vendor called Savings Sidekick (apparently not related to the Shopkick iphone app) is doing something similar by using the tip feature in Foursquare to remind users of nearby deals from their coupon books. This particular implementation is as interesting as it could be annoying.

Part 1 wrap

Local is huge and only getting bigger. As a litmus, Borrell’s recent ad forecast notes that “local online advertising should grow by almost 18% [...] to $16.1 billion, in 2011.” Money follows money: we can expect further me-too products around deals, check-ins, and place products, but there is huge scope for investment into products that contribute genuine value to the consumer experience and enhance SMBs’ ability to connect to their customers.

Much of this will take place at the data and platform levels. In my next post I’ll take a look at how linked data might help cross-platform integration, and join deals, check-ins and place pages to the benefit of the consumer.

Related:

• Why check-ins and like buttons will change the local landscape
• Where’s the map?
• Foursquare wants to be the mayor of location apps
• What you need to know about local search

On first blush the idea of a “check in” is unworthy of note — broadcasting publicly that you are at a particular venue is neither technologically sophisticated nor particularly novel. However, the driving impulse here is what’s interesting: the check-in is much more about who you are than where you are. The passion driving the uptake of Foursquare, Gowalla, and their ilk is sociological rather than geographical.

People check-in to venues for the same reasons they consciously display swooshes on shirts, Coach emblems on handbags, and glowing apples (or penguins for the more enlightened) on computing devices: these emblems communicate a facet of one’s identity to the world in a facile, shared language. Checking into “Zeitgeist” in San Francisco tells the world you have roguish good looks (surely), plus a penchant for beer, outdoor smoking, and tamales. Checking into “Costco” tells the world that you own a car, and have an apartment or house in which to store large bulk items; checking into “SFO Long Term Parking” tells the world that you check-in too much, and should maybe ease-off a bit.

What logo or symbol can say so much, with such brevity, about an individual? The venue makes the man.

The magic here is the expression of affinity with a business, which is where the idea of the “like” has similar power in the local space (here I use “like” as any systemic convenience to express affinity, not exclusively Facebook’s). In many ways liking a local business has significant advantages over a check-in: you do not have to be on-site, you like only once in perpetuity, and your affinity for the business is not measured by the number of times you visit. Check-ins, however, measure on-site presence, a hugely important metric for any business that values feet-through-the-door.

Thus the check-in holds the most potential for point-of-sale, in-the-moment marketing (“I see you are next door; come try a free latte at our place instead”), while Likes may offer greater potential for geo-relevant demographic targeting (“Here are deals for restaurants, similar to the ones you like, in areas where you are commercially active”). Likes and check-ins are really two sides of the same coin, but unfortunately share the same curse: there is no way to realize this user-to-business affinity and the value it represents uniformly across platforms.

Where previously this lack demanded only a frustrating duplication of effort, the problem has become more serious: the advent of likes and check-ins drive a semantic necessity to open and aggregate — the problem is no longer one of mere inconvenience.

Gary Gale calls this problem “Geo Babel“, and the local landscape has all the hallmarks of the eponymous tower. Without a common means, our likes and check-ins will continue to be bound to the platform on which they were created, hamstringing their potential. Elbowing my way into Tim O’Reilly’s metaphor, I would propose that this is a critical, missing component of the Internet Operating System. It seems outrageous that we find ourselves in 2010 without the means to refer to a business in a unique and unambiguous manner. Developers are left holding the bag for a number of reasons; here are my big three:

1. Focus on listings data as end rather than means: Local search as we know it today is the parthenogenous child of the Yellow Pages industry. Many local search sites, and the data vendors they rely on, remain grounded in YP-era thinking, where the value was found in owning the listing data, making them discoverable in alphabetical order, and advertising against these listings. Local search for ages focused on being an electronic version of the Yellow Pages. Few organizations have looked above the horizon and considered carefully what value could be realized if listings were viewed as a means to connect users to businesses, rather than only advertise against their search.
2. Attempts at distinction with common data: With peripheral exceptions, every local site out there has the same data. Boil these listings down to their hcards and you’re looking at dupes across the board. This is of course known by all the big players, which is why they focus on differentiation with ancillary data such as ratings and reviews, or making their listings the most inclusive or the most current. This strategy drives competitors to attempt the “one ring” approach, where each tries to climb above the other in an effort to become the premier source of online local listings. It is a bugbear for developers because efforts to differentiate a commodity are always frustrating and rarely carry the sector forward.
3. Over-fascination with pins on maps: The advent of GPS-enabled devices and Wi-Fi positioning gave us the ability to show people’s location on the map; this has proved hugely distracting while the sector over the last four years has attempted to make buddy-finding interesting. We’ve since learned, I think, that people do not navigate by Long/Lat — Foursquare and Gowalla succeed in part because they use business listings or venues as mechanisms of personal expression within a shared social landscape. Social location is best referenced by place not space; the coords tell me nothing.

This lacuna can be resolved one of two ways — either one will do the trick but I am hoping for both:

First, we can work together toward an open database of places. Erick Schonfeld’s post on TechCrunch a few weeks back is the most recent clarion. This is not an insignificant undertaking, but is certainly the preferred outcome. However, even with OpenStreetMap at our back, realizing this goal will take an eon in Internet time unless we see an unanticipated outbreak of altruism on the part of a data supplier. Of course, the ‘new’ players in the game — those whose businesses use listings as a conveyance of value — understand this need and are best positioned to deliver against it.

The second alternative — one that is much more realistic in the short term — is an open and accessible Local Listings Crosswalk, essentially an API that takes your URI and translates it to my URI so we can ensure we are speaking about the same business (I am less concerned about geographic place-names because such services already exist); Placecast’s Match API went live as I was writing this post, so I hope that theirs will be the first step in getting us to where we want to be. The outcome,of course, will be achieved when we have a number of these services crosswalking via callbacks and hcard/og-aware crawlers, perpetuating listings data and ensuring they are up-to-date and uniformly accessible.

One or both of these services will allow us to put the bother of business listings management behind us, so we can get on with what’s really exciting about local: connecting consumers with businesses they love, and providing genuine value to both.

Related:

• What you need to know about local search
• Foursquare wants to be the mayor of location apps

Placecast Match API

The free service “simplifies the process of de-duplicating and matching content like business listings, reviews, check-ins and events to their true location”; it is the first of what will certainly be many Local Disambiguation platforms we see that attempt to generate concordance between how Places are called. With this product Placecast appears to be moving out of the ad-world and into the geo platforms space. Details are few as the API is not yet out the door, but you can sign up in advance at the link above.

Skyhook Local Faves

An all-in-one iphone SDK that brings location to social sharing applications: “in a Local Faves-enabled wine app, users could check-in to a restaurant via the wine they are drinking, giving the app developer the opportunity to broadcast user location” or allow users to “see where around the world their favorite song is playing, or view all songs playing locally”. I’m not yet convinced that the overly broad use cases demonstrate anything otherwise unavailable to developers, but this product (and the company’s recent launch of SpotRank) shows how Skyhook is positioning itself in the center of the geoweb to become a critical provider of location context. The API comes out ‘mid April’; register in advance here.

Yahoo Concordance

One for the toponymsters: a geographic Rosetta Stone” that lets you convert between GeoPlanet WOEIDs (Yahoo’s open place-based identification namespace) and other geographic naming systems including, most notably, Geonames. A step in the right direction from my geo alma mater, but I would hope that Yahoo is planning to do something very similar with Business Listings if it is to avoid being out-maneuvered entirely in the immediately forthcoming Social/Local landscape.

SimpleGeo

SimpleGeo is only about a year old now but is successfully positioning itself as a dead-easy geo service and recently boosted its small team with a few seasoned hires. The nascent API is available via XML and JSON and includes supported iphone SDK and PHP PEAR libs. The functionality is basic, but growing: object-based point storage, proximity lookups, reverse geocoding (in US) and spatiotemporal headcounts via Skyhook’s SpotRank (above). Expect more services to be integrated via their recent deCarta and Quova deals. Use it now for free for up to 1m calls-per-month, and then scale up as far as Amazon’s S3 will take you.

Have I missed any? (Let me know.) These products are the litmus of the geo sector: what we are seeing here is the importance of Business Listings as first-person reference (soon to obviate Yellow Pages entirely), the continued advent of simple-and-deep over shallow-and-feature-rich product methodologies, and the “virtuous circle of data,” where the use of these products generates value (data about us), which is exposed again through the API. Platform plays like these — not the next iPhone app — are what genuinely carry the sector forward.

The C3 team dropped jaws with a few sneak previews of their product at last year’s Where 2.0, and their CEO Mattias Åström spoke yesterday; I followed up today with C3 PM Ludvig Emgård who provided me with a few shots of their local Bay Area work that I can share here:

You’ll see that these are not projected images with the occasional visual 3D model spiking out of the plain, but complex and immersive topographic textured wireframes. C3 do their own flying with a five-camera rig (flying between the fog multiple times over San Francisco) and resultant data are crunched automatically over “a couple of days” per city. C3 are rolling out at a modest pace with 5 cities now available in the US and 50 in Europe. Little forthcoming product, partner or launch details are available for 2010 but we’ll see, quite literally, much more C3 in the coming year.

Guest blogger Tyler Bell is a geotechnologist with broad interests in open source and place-based information systems He is currently managing Platform technologies at AlikeList, a Sunnyvale-based Social/Local start-up, where he designs disambiguation systems, geo technology platforms, and syndication APIs. Until recently Tyler led the Geo Technologies product team at Yahoo!, conceiving and launching the Placemaker and GeoPlanet geo-enrichment platforms.

This year’s Where 2.0 has sold out, pushing the San Jose Marriott’s fire code into the red with over 900 attendees. With assured kudos to the conference team, it speaks more loudly as a bellwether for the Geo Sector itself, because the so-called Year of the Map is finally here. However the Map is playing only a supporting role, and will continue to be relegated as “Local and Geo” becomes less about Mapping and more about Local Experiences.

Take Foursquare: Opening his keynote today with a curiously genuine “have you heard of Foursquare?”, Denis Crowley recounted in congenial staccato his founding premise: how can we make Life more like a game? The recipe for success was simple: take an existing behavior (going out and doing stuff), enrich it, and make it fun. Crowley and his Team have managed to twig onto something so elegant and popular that the big players have vocally wished they invented it (a dancecard full of eager VCs is further reason, should any be needed). But what started as a game is now “driving users to lead a more interesting life” as Foursquare players compete for Fitness and Pizza badges — rarely both, I assume — and vie for Mayorships that translate virtual accomplishments into real-world rewards.

At Foursquare (and Gowalla, Yelp and similar services) every check-in is a small advertisement for a place, and this really is where the magic lies: Foursquare connects SMBs (Small and Medium Businesses) to their customers, and rewards both: “if you give our users deals”, Crowley says to SMBs “we give you data”. Because Foursquare can provide vendors welcome insight into their users’ behavior (who shows up where, when), they are positioned to become a “Google Analytics for bricks-and-mortar businesses”, and releasing the data back out through the API: a winning, virtuous, and undoubtedly profitable, circle. Compare this approach to something like (for example) Groupon, where the SMB-to-Customer contact is interdicted and owned by the facilitating company.

But back to the map – it’s not in evidence. Geo Technology is critical to Foursquare; but its map is only a casual convenience. Nor can the Map be found in what is increasingly incorrectly described as ‘Local Search’.

Danny Sullivan (Search Engine Land) chaired an all-too-brief ‘Big Panel with the Big Players’ session with the – wait for it — ‘Big Players’ in Local Search: Google, Microsoft, Yahoo, and (in august company) Yelp. Panels such as this present the audience an opportunity to hear unscripted industry commentary straight from the source, but are often a sump of uninformative doggerel; this one managed to be a bit both. Danny kept the discussion on course, charitably teeing up the usual suspects to warm up the panel: mobile, reviews, and street side imagery.

While much of the panel discussion could be anticipated in advance (Streetview is popular, Mobile is important), the audience probably found the discussion of Reviews to be the most revealing with regards to product thinking and corporate character: John Henke gave what can most accurately be described as a Google-like commentary: Reviews “raise the level of participation, and users can look at the aggregate to obtain a general signal”, while Tom Wailes (Yahoo) was perhaps unsurprisingly most sympathetic with my own thinking: the future of local referrals lies not in reviews and ratings from semi anonymous individuals, but rather in trusted recommendations from people I know. A recent Forrester survey says 86% of people prefer trusted recommendations; that number will only rise.

But wherein lies the map? Microsoft’s Arcas hit this one on the head: “our initiatives are more about assembling and presenting the virtual world, not owning it”. The Map, then, becomes the means of conveyance for locally-relevant information, not the end in itself.

A final segue: Gary Gale’s (Yahoo!) talk on “Ubiquitous Location, The New Frontier and Hyperlocal Nirvana” was similarly map-free: Location is not as precise, ubiquitous, correct as we presume, and the map itself is too often an incorrect and misleading codification of geography (see Paul Ramsey’s ‘Why Your Data Sucks‘ Ignite talk last night as a succinct, supporting argument).

Although not called out explicitly in Brady’s “Big Conversations” at Where 2.0, a significant tenor at this year’s conference is the advent of “Disambiguation Platforms”: APIs that take one identifier for a place and translate it into another: while Brightkite is doing this in part with its check.in service, more holistic platforms have launched today at Where with Placecast’s Placematch API and Yahoo’s Concordance Platform. These services highlight the forthcoming importance of Local/Place/Venue identifiers as users locate, and associate themselves with named places rather than long/lat coordinates. I would modify Michael Jones’ (Google) tweeted take that “Maps are not just driving directions. Maps are a way that humans understand their planet”. Places are, in fact, they way that people understand the world around them; maps are just a way of representing this understanding. This is not semantics; this is important.

So the Year of the Map is upon us, but increasingly without the Map.