Information Visualization & Visual Analytics Jack van Wijk - PowerPoint PPT Presentation

Information Visualization & Visual Analytics Jack van Wijk Dept. Math. & Computer Science TU Eindhoven BPM round table, March 28, 2011

Overview • InfoVis • Visual Analytics

Why is my hard disk full? ?

SequoiaView • www.win.tue.nl/sequoiaview Van Wijk et al., 1999, Bruls et al. 2000

Information Visualization • The use of computer-supported, interactive, visual representations of abstract data to amplify cognition ( Card et al., 1999 ) Abstract Information data image dataset Visualizatio User (table, n graph, tree) interaction

Abstract data • Multivariate data visualization scatterplot • Tree visualization tree diagram • Graph visualization node link diagram

InfoVis at TU/e Focus: • Large data sets, professional users • Use of computer graphics know-how – shading, geometry, texture, … • Software Visualization (similar issues as BPM?)

Software Visualization • User: developer, architect, manager, … • Some fuzzy questions: – Is the structure sound? – Can I improve the structure by refactoring? – What has happened with the system? – Does the implementation conform the architecture? – Where are the weak spots?

Different views on software • Architecture – System structure – Data – Coordination, temporal aspects • Code – Structure – Derived data, metrics – Evolution • Execution – Traces, call graphs

Challenges in Software Visualization Combination of large amounts of – Multivariate data (metrics) – Hierarchical data (system, subsystem, module, ..) – Graph data (call relations) – Text (names, code) + = +

Trees + graphs • Ubiquitous!

MatrixView Data: – hierarchy of layers, units, modules, classes, methods – methods calling each other

MatrixView Matrix representation of graph A B C D E A A B B C C E D D E

MatrixView Van Ham 2003, Van Wijk et al., 2003

Hierarchical Edge Bundles • Again, tree+graph, but now completely different Holten, 2006

Showing directions in edges arrow light-to-dark dark-to-light green-to-red curved tapering Holten et al., 2009

Result of experiments

Visual Analytics: Beyond visualization

Origin • Founder: Jim Thomas, NVAC • Illuminating the Path , 2004 Visual Analytics: The science of analytical reasoning facilitated by interactive visual interfaces

Definition • The science of analytical reasoning facilitated by interactive visual interfaces – Compact! – Complete! – Perfect! – But what is it?

Video • VisMaster

An InfoVis perspective Abstract data image dataset Information User (table, graph, Visualization tree) interaction

An InfoVis perspective data statistics mathematics design art management - domain expertise - gigabytes, terabytes, petabytes - statistics, machine learning, Many, large, - fit in workflow - tables, images, documents, videos, audio,… pattern recognition, artificial heterogenous Data mining - from data foraging intelligence, … datasets to presentation - teamwork Abstract data image Professional dataset Information User (table, graph, Visualization tree) interaction software cognitive graphics HCI perception engineering psychology

The key ingredients • Huge, heterogenous data sets • Integration of data mining and visualization • Integration in workflow • Support for all stages of data analysis • Support for multiple users • Keyword: INTEGRATION • Result = product of parts (2 x 2 x 2 x 2 x 2 = 32)

FAQ We know this already, isn’t it just: • applied infoVis, visual data mining, visual data analysis, statistical graphics, … Sure, Visual Analytics builds on existing technologies and earlier examples exist…

One year of time-series data #people at work 365 graphs 0:00 12:00 24:00 Van Wijk et al., 1999

After clustering #people at work 365 graphs 0:00 12:00 24:00 Van Wijk et al., 1999

Command Post of the Future • Steven Roth et al. • Visage (1996), CoMotion, MAYA Viz Interaction, heterogenous data, knowledge sharing, teamwork, decision making, …

FAQ We know this already, isn’t it just: • applied infoVis, visual data mining, visual data analysis, statistical graphics, … Sure, Visual Analytics builds on existing technologies and earlier examples exist… but integrating all of these is still novel, difficult, and challenging.

FAQ • This Visual Analytics, that’s American, right? • No, wrong.

• EU-funded Coordination Action Project • 26 partners, 12 countries • Developing roadmap • Organizing events • Communication platform • Video (youtube: vismaster) Daniel Keim Jörn Kohlhammer

Summary Visual Analytics: • Great! • Big! • Challenging!