  Urban planning and morphology have relied on analytical cartography and
visual communication tools for centuries to illustrate spatial patterns,
propose designs, compare alternatives, and engage the public. Classic urban
form visualizations - from Giambattista Nolli's ichnographic maps of Rome to
Allan Jacobs's figure-ground diagrams of city streets - have compressed
physical urban complexity into easily comprehensible information artifacts.
Today we can enhance these traditional workflows through the Smart Cities
paradigm of understanding cities via user-generated content and harvested data
in an information management context. New spatial technology platforms and big
data offer new lenses to understand, evaluate, monitor, and manage urban form
and evolution. This paper builds on the theoretical framework of visual
cultures in urban planning and morphology to introduce and situate
computational data science processes for exploring urban fabric patterns and
spatial order. It demonstrates these workflows with OSMnx and data from
OpenStreetMap, a collaborative spatial information system and mapping platform,
to examine street network patterns, orientations, and configurations in
different study sites around the world, considering what these reveal about the
urban fabric. The age of ubiquitous urban data and computational toolkits opens
up a new era of worldwide urban form analysis from integrated quantitative and
qualitative perspectives.
