GeoIQ - multivariate heat mapping

I had the chance to speak with Sean Gorman who developed GeoIQ , a new mashup that can integrate several demographic variables into heat maps. They have several demos, one is a demo that compares demographic heat maps between San Francisco and New York City, another on traffic in LA and Washington DC. The point of the demos of two city comparisons escapes me; the only concept that comes to mind is comparability of neighborhoods - identifying San Francisco's Pacific Heights as perhaps equivalent to the Upper East Side.

On just one map however, the obvious value is in identifying niche neighborhoods across a variety of variables... Sean's favorite example - areas with concentrations of single women and bars... add crime data and you'll know if you're in a red light district or the Marina.

There's more detail about GeoIQ's concepts about how to use their heat maps in their very readable blog... GeoIQ and its macroeconomic counterpart Neighboroo are first generation heat maps now in search of an application and business model that will stick after the initial "wow" factor generates an audience.

Sean says there is a challenge to cleansing existing demographic data like census data so that it is annotated well enough for presentation in a mashup. GeoIQ just released its API for developers... since the backend requires "mapable" data, Sean proposes an open source community of developers who would share these data among each other.

Related note: the NY Times Sunday business
article on Web 3.0 by John Markoff is an interesting, light read that posits Web 3.0 will mine data to automate complexes processes like identifying best locations for car washes. Although the article confers respectability to GeoIQ's quest, the tech bloggers immediately panned Markoff's Web 3.0 vision as no substance. And they're right... it's my little epiphany to the power of blogs... last spring I would have taken the NYT at face value.

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