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During the holiday break, I have had the opportunity to do some undirected reading in a variety of areas. One of the topics I’ve browsed is urban data. My favorite source for this type of work, IBM Smarter Planet, indirectly led me to a transcript of a talk by an IBM Distinguished Engineer, Colin Harrison. He was discussing the advent of Urban Information Networks during the Paris 2030 Colloque.

Harrison specifically focused on the type of data used to link urban services and their users to each other using three classes: the invisible rendered visible, information for resource management, and open data 2.0. Urban information networks are tearing down the boundaries between citizens and their participation in the pragmatic management of their own urban resources by increasing process transparency at the same time exclusivity of information access is reduced.

One of the possibilities emblematic of the types of problems I hope to address in this space is an anecdote Harrison gives concerning CalTrans:

An example of how information enables the inhabitants to most effectively use the immediately available capacity of the total, multi-modal transportation system comes from our work with CalTrans in the San Francisco bay area. Here inhabitants with smart mobile telephones can subscribe to a service that enables CalTrans to observe their journeys based on the GPS reading from the telephone. From these observations CalTrans can determine the individual user’s common journeys. When the system sees the user beginning a familiar journey, for example commuting from home to the workplace, it looks at the multi-modal choices available to the traveller and the operational status of each of those systems along the required paths, and then makes a recommendation to the traveller for the optimal way to make this journey at this time. The traveller thus makes the journey with the minimum delays and disruptions and the transportation systems’ loads can be balanced.

The opportunities in understanding the impacts of the interplay between user behaviors and system properties is truly awesome. Let us work together to continue seeking understanding of how these emerging problems can be more greatly understood.