Trac
ows were the rst data to be automatically sensed in cities but databases of various
spatial data go back centuries. Indeed digital computing emerged as much from a concern over
collecting census data as it did from a concern for scientic computation. Herman Hollerith
introduced punched card technology for the 1890 US Census from which sprang the company
that ultimately became IBM. Since the late 1990s, such data has been routinely collected and
displayed using GIS (geographic information systems) technology, and the rst visual systems
to be widely available on the web were maps for navigation. This is the backcloth against
which many dierent initiatives in collecting data from new varieties of digital access are being
fashioned such as GPS in vehicles and on the person, from electronic messaging in the form
of social media sites, from traces left through purchase of goods and related demand-supply
situations, and from access to many kinds of web site. Satellite remote-sensing data is also now
widely deployed, more local scale sensing from LIDAR is proliferating, and a variety of scanning
technologies that range from the region to the person and to very ne scale tagging as in the
focus associated with the internet of things, are becoming signicant. One of the most extensive
crowd-sourcing applications, next to Wikipedia, is Open Street Map built from a community
of some 20000 active users who continually update the map using GPS. Indeed new models
of scientic discovery are emerging from developments in rather focussed crowd-sourcing and
these are applicable to how we might gure out good designs for ecient and equitable cities