Collaborative Visual Analytics of Earth Science Data for Emergency Response Scenarios

Bruce CampbellCenter for Environmental Visualizationbrucedc@u.washington.edu

Relevant History of the CEV

• started in 1995 with high quality illustration work

• multimedia production work – 1996• exploration of virtual environments – 1997• development of specialized graphics

engine – 2000

• oceanographers workbench – current• UW visualization and analytics center

liaison – current

(we are six UW staff members with 2-3 undergraduates interning at any one time)

Demonstrations

Illustrations (Earth and Ocean Processes)Animations (Earthquakes and Glacial Retreat)Virtual Environment (Big Beef Creek)3D Presenter (Admiralty Inlet)

The Emerging Science of Visual Analytics

Visual Analytics attempts to predict how human beings use their perception and cognition skills honed by walking about in our natural complex 3-D environment to identify expected patterns and discover unexpected patterns in abstract data sets, given a presentation and interaction tools for exploring that data.

For Example, Consider Extrapolating from Successes in the 2-D Realm

The Oceanographers Workbench

Investigators Toolkit Desktop Visualizer 3-D Presenter Visualization Server

The RVAC Opportunity

Five campuses across the US have been chosen to facilitate regional visualization and analytics centers.

The UW-based PARVAC will coordinate visual analytic research around the Pacific Rim

The NVAC (National Visualization and Analytics Center)

The national visualization and analytics center is run out of the Pacific Northwest National Laboratory in Richland, WA.

We are the closest RVAC to the NVAC The NVAC has been developing abstract

data visualization tools for ten years

NVAC Visualization Tools specialty: text to terrain/galaxy (INSPIRE)

A Goal Worthy of Discussion?

How can we best design interactive tools for investigating earth and ocean data set layers such that targeted analyst groups can share the analytical discourse process over geographical distance and assess to make prevention, response, and recovery plans (even within stressful time constraints)?

Assessing Collaborative Visual Analytics Tools

An interesting research area concerns trying to quantify the success of using visual analytics tools to provide insights.

Certainly, the humans, tasks, and data participating in the tool use each contain success components.

How do you go about quantifying the metrics of success?

Links of Interest

CEV – www.cev.washington.edu NVAC – nvac.pnl.gov Visual Analytics – Illuminating the

Path nvac.pnl.gov/agenda.stm