BA1220 (Bahen Centre, 40 St.George Street)
  • March 9, 2017 from 11:00am to 12:00pm

Research seminar hosted jointly by the departments of Computer Science and Statistical Sciences presented by: Arvind Satyanarayan, Stanford University

Interactive visualization is an increasingly popular medium for analysis
and communication as it allows readers to engage data in dialogue.
Hypotheses can be rapidly generated and evaluated in situ, facilitating an
accretive construction of knowledge and serendipitous discovery. Yet,
existing models of visualization relegate interaction to a second-class
citizen: imperative event handling callbacks that are difficult to
specify, and even harder to reason about.

In this talk, I will introduce two new declarative languages that lower
the threshold for authoring interactive visualizations, and enable
higher-level reasoning about the design space of interactions. Reactive
Vega is an expressive representation that is well-suited for custom,
explanatory visualizations. It shifts the burden of execution from the
user to the underlying streaming dataflow system. Vega-Lite builds on Vega
to provide a higher-level grammar for rapidly specifying interactive
graphics for exploratory analysis. Its concise format decomposes
interaction design into semantic units that can be systematically

Together, these languages serve as platforms for further research into
novel methods of expressing visualization design, and systems for
interactive data analysis. And, critically, they provide a growing and
engaged community to study their use with — the Wikipedia and Jupyter
communities, for instance, have embraced Vega and Vega-Lite to author
interactive visualizations within articles and data science notebooks,


Arvind Satyanarayan is a Computer Science PhD candidate at Stanford
University, working with Jeffrey Heer and the University of Washington
Interactive Data Lab. Arvind’s research develops new declarative languages
for interactive visualization, and leverages them in new systems for
visualization design and data analysis. His work has been recognized with
a Google PhD Fellowship, Best Paper Awards at IEEE InfoVis & ACM CHI, and
has been deployed on Wikipedia to enable interactive visualizations within