Information Design and Visualization Chris North CS 3724

Information Design and Visualization Chris North CS 3724: HCI

To do • Hall of Fame/Shame Presentations • Project: Requirements Analysis

ANALYZE analysis of stakeholders, field studies Problem scenarios claims about current practice DESIGN metaphors, information technology, HCI theory, guidelines Activity Functionality scenarios Information scenarios Look and feel iterative analysis of usability claims and re-design Interaction scenarios PROTOTYPE & EVALUATE summative evaluation Usability specifications formative evaluation

The Problem Human Data Transfer Data Goal: Insight How?

Human Vision • • • Highest bandwidth sense Fast, parallel Pattern recognition Pre-attentive Extends memory and cognitive capacity • (Multiplication test) • People think visually Impressive. Lets use it!

Find the Red Square:

• Which state has highest Income? • Relationship between Income and Education? • Outliers?

College Degree % Per Capita Income

Scenarios = Data + Tasks • Data categories: – Spatial (1, 2, 3 D) – Tabular (Multi-dimensional) – Network, Tree – Text, documents • Combinations of categories

User Tasks • Easy stuff: (1 or few items) • Min, max, average, % • Exact queries, known item search Excel can do this • Hard stuff: • • Patterns, trends, distributions, changes over time, outliers, exceptions, relationships, correlations, multi-way, combined min/max, tradeoffs, clusters, groups, comparisons, context, anomalies, data errors, Visualization can do this! Paths, …

Examples of Tabular data visualization • Data. Maps • Spotfire • Table. Lens

Data. Maps • demo

Spotfire • Mapping data to graphics (x, y, size, color, shape…) • Multiple views: brushing and linking • Dynamic Queries • Details window Cars data

Visual Mapping: Step 1 1. Map: data items visual marks Visual marks: • • • Points Lines Areas Volumes Glyphs

Visual Mapping: Step 2 1. Map: data items visual marks 2. Map: data attributes visual properties of marks Visual properties of marks: • • • Position, x, y, z Size, length, area, volume Orientation, angle, slope Color, gray scale, texture Shape Animation, time, blink, motion

Mapping Example in Spotfire • Film database • • • Film dot Year x Length y Popularity size Subject color Award? shape

Table. Lens (Eureka by Inxight) • Visual encoding of cell values • Details expand within context (fisheye) • Sorting Cars data

Examples of Tree data visualization • Windows Explorer • Star Tree • Tree. Maps

Star Tree (Hyperbolic Tree) • Focus+Context • Radial; shrink with distance to center • Drag to navigate • Scalability? • Xerox PARC, Inxight • http: //startree. inxight. com/

Treemaps • Parent/child containment • Size & color encoding • Map of the Market: http: //www. smartmoney. com/marketmap/ • People Map: http: //www. truepeers. com/ • Coffee Map: http: //www. peets. com/tast/11/coffee_selector. asp • U. Maryland

• “Squarified” Tree. Map • http: //www. research. microsoft. com/~masmith/all_map. jpg

Sequoia. View • http: //www. win. tue. nl/sequoiaview/ •

Context is Important!

Information Visualization Mantra • • • Overview first, zoom and filter, then details on demand Overview first, zoom and filter, then details on demand - Ben Shneiderman

What is Information Visualization? The use of computer-supported, interactive, visual representations of abstract data to amplify cognition

Keys points • Power of visual system • scenario = data + tasks • Mapping data to graphics & visual properties • 2 steps • Interaction for what doesn’t fit in visual rep. • Dynamic queries, brushing, … • Examples: tabular data, trees • Mantra: Overview first… • Choice of visual representation matters

What’s the Big Deal?

- Edward Tufte Presentation is everything!

Project Step 3 – Design • Due 3 weeks: get started early! • Design space • Dimensions of the design space • Alternative designs • Claims analysis • Formative evaluation • Wizard of Oz • Refinements • Final design: • Scenarios • Representations