A Big Data System for Things that Move

Tuesday, October 20, 2015 - 2:00pm - 2:50pm
Keller 3-180
Damon Wischik (Urban Engines)
The human world is full of things that move: people travelling, in
buses and trains and cars and taxis, goods being shipped and
delivered, etc. etc. Sensors for recording these movements are
becoming cheaper and more widespread, from GPS-equipped mobile phones
to smart commuter cards, and so there is an explosion in the amount of
movement data that is available. How can this wealth of data be
understood, and how can it be put to work to improve the way the world

I will present a system we have built, called the Space-Time Engine,
for working with big data about urban mobility. It has three parts:
(1) algorithms for stitching together partial or noisy observations to
reconstruct a fine-grained digital replica, (2) interactive
visualizations and a query language for answering questions and
building models about movement data, (3) integration with simulation
and other operations-research tools to answer what might happen?
rather than just what did happen?

The Space-Time Engine aims to be a data science tool for users who are
comfortable with Excel but not with probability or optimization
theory. Based on our experience designing it, I will discuss ways in
which big data might make network modeling accessible to a broader
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