Electronic Visualization Laboratory, University of Illinois at Chicago

PAVIS

Pervasive Adaptive Visualization and

Interaction Service

Javid AlimohideenElectronic Visualization Laboratory

University of Illinois at Chicago

CHI 2006

Workshop on Information Visualization and Interaction Techniques for Collaboration Across Multiple Displays

Montreal, Canada

04/22/06 – 04/23/06

Electronic Visualization Laboratory, University of Illinois at Chicago

Motivation & Goal

• U.S. Army Pantheon Project requirements– Process real-time sensor data to predict changes– Distribute information to variety of display platforms (from PDAs to tiled displays)

• Challenging for an application developer

PAVIS intends to automatically generate resource-aware visualizations & context sensitive user-interfaces that are best suited for the display device using rule-based techniques.

Electronic Visualization Laboratory, University of Illinois at Chicago

Related Work

• “An architecture for rule based visualization” incorporates perceptual rules into the visualization process (Rogowitz & Trenish, 1993, IBM Thomas J. Watson Research Center )

• SUPPLE – considers interface generation as an optimization problem (Gajos & Weld, 2004, University of Washington)

• iCrafter – uses hand created templates (Shankar et al, 2001, Stanford University)

• XIML – user specified layout constraints (Puerta & Eisenstein, 2002, RedWhale Software, Palo Alto, CA)

• Thinlet – XML based JAVA GUI toolkit (Robert Bajzat, 2002)

Cannot be used for Wall-sized displays, better knowledge of UI development is required, does not support both UI and visualization generation.

Electronic Visualization Laboratory, University of Illinois at Chicago

PAVIS - ArchitectureMain source of data

(E.g. 830 Chicago Highway sensor data, alerts,

weather affecting traffic conditions)

Main source of data(E.g. 830 Chicago Highway

sensor data, alerts, weather affecting traffic

conditions)

Display size, device type, network bandwidth

Display size, device type, network bandwidth

Data and device specific rulesare efficiently merged and

filtered

Data and device specific rulesare efficiently merged and

filtered

Data filtering on raw data based on filtered rules

Data filtering on raw data based on filtered rules

Generic built-in UI rule’s are tailored to device’s capabilities

based on filtered rules

Generic built-in UI rule’s are tailored to device’s capabilities

based on filtered rules

Scalable rendering to render data from few thousand pixels to several hundreds of mega

pixels

Scalable rendering to render data from few thousand pixels to several hundreds of mega

pixels

Electronic Visualization Laboratory, University of Illinois at Chicago

Research Issues

• What are the key constraints of each operating platform?– Constraints include display size, user input device (mouse, keyboard, num pad

or touch screen), network bandwidth– Constraints dictate the tasks that are most reasonable. (E.g. PDAs primarily

receive alert information rather than high-resolution images)• How does one build a Mathematical Rule based model using these constraints?• How might a rule-based system act?

– Relative salience of the data attributes determines which is crucial data for each platform (E.g. Alerts only for PDAs)

– Choice of control widgets (E.g. List Menu for a PDA, Pie Menu for a Desktop)– Interaction Techniques (E.g. Zone zoom for zoom/pan, magic lens for more

detail)– Interaction devices (E.g. Pointing interfaces for a Tiled display, mouse on a

desktop, num pad on a cell phone)• An alternative approach is to Design UI and Visualization scheme that makes sense

for all display sizes– Smart widget set that could scale across displays well– Scalable Visualization widgets

Electronic Visualization Laboratory, University of Illinois at Chicago

Current Status

• Implemented initial proof-of-concept: a client/server system that serves multiple PDA clients, and tiled displays with minimal data filtering techniques and generation of visualizations.

Electronic Visualization Laboratory, University of Illinois at Chicago

AcknowledgmentsSupported in part by U.S. Army Pantheon Project and National Science Foundation

Contact InformationJavid Alimohideen javid@evl.uic.eduJason Leigh spiff@uic.eduElectronic Visualization LaboratoryUniversity of Illinois at Chicagohttp://www.evl.uic.edu/pavis

Thank You

Electronic Visualization Laboratory, University of Illinois at Chicago

Rule Example

Ex: if (alerts)

cluster(alerts)

if (events)

display events

if (events > alerts)

highlight events

else

highlight alerts

if (device type cellphone)

map events to numpad

else if (device type desktop)

map events to mouse events

else if (device type tiled display)

map events to keyboard

Cluster(alerts) {

If (display size is small)

cluster size = 10

else

cluster size = 3

}

Electronic Visualization Laboratory, University of Illinois at Chicago

PAVIS related Research Questions

• How much can an application benefit from a system like PAVIS ?– Reduces wok load for the application developer– Code reuse– Easy deployment– UI / Viz changes transparent to Client

• Other possible domains ?• Is the generated layout and visualization optimal ?