COMP Visualization. Lecture 11 Interacting with Visualizations

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COMP 150-04

Visualization

Lecture 11

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Assignment 5: Maps

Design a thematic map visualization

Option 1: Choropleth Map

Implementation in Processing

Option 2: Tourist Map

Design/interaction sketch + thorough discussion Option 3: Interactive Layered Map

or “Mapper’s Delight”

Implementation in Processing

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Visual information-seeking mantra

“Overview ﬁrst, zoom and ﬁlter, then details on demand.” Design of GUIs and interactions

Ben Schneiderman, “The eyes have it: A task by data type taxonomy for information visualization”

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Desktop interfaces

Interactions we take for granted can be powerful Detail on demand:

Mouse selection

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Tangible interfaces

Novel interaction styles Detail on demand:

Gestural selection Multiple selections

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Interaction in infovis

Static or dynamic visualization? What are the goals?

What aspects of the design can we control? What user tasks/operations must we support?

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Static infovis

Goal: Create an effective, expressive view of the data Data encoding

Composition

Perception: popout, Gestalt Cognitive skills

Communicate Compare, rank

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Static infovis

Goal: Create an effective, expressive view of the data Data encoding

Composition

Perception: popout, Gestalt Cognitive skills

Communicate Compare, rank

Identify correlation, causation

Goal: Enable user to focus on goals rather than controls

Presentation: Good static views linked together well

Perception

Cognitive skills Motor skills Explore

Find best match

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Obtain the data

Order the data into categories by meaning

Remove all but the data of interest

Discern patterns, place the data in mathematical context

Select a visual encoding model

Improve the basic representation

Support dynamic queries

ACQUIRE PARSE FILTER MINE REPRESENT REFINE INTERACT PARSE FILTER MINE PRESE REFIN TERAC

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ACQUIRE PARSE FILTER MINE REPRESENT REFINE INTERACT PARSE FILTER MINE PRESE REFIN TERAC DATA HANDLING GRAPHIC DESIGN INTERACTION DESIGN Regular expressions, ... Perl, Python, ... Graphics APIs UI toolkits Visualization toolkits

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What is “interactive”?

< 10 sec cognitive response

< 1 sec system response, conversation break < 0.1 sec visual continuity, GUI widgets

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Data type taxonomy

1D, 2D, 3D Temporal Multi-dimensional (nD) Tree Network

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Task taxonomy

Overview: see overall patterns in data Zoom: see a subset of data

Filter: see a subset based on values Detail on demand: see values of items Relate: compare values

History: keep track of actions Extract: mark and capture

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Task taxonomy

Visual Languages, 1996

Overview: see overall patterns in data Zoom: see a subset of data

Filter: see a subset based on values Detail on demand: see values of items Relate: compare values

History: keep track of actions Extract: mark and capture

overview+detail focus+context geometric zoom semantic zoom mouseover query selection query brushing/linking dynamic query

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Overview+Detail display

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Overview+Detail display

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Overview+Detail display

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Overview+Detail display

Show overview and detail in separate views

+ No spatial distortion

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Focus+Context display

Uniﬁed view:

Focus object is in full detail Surrounding, contextual info

is available with less detail

+ Simultaneous display matches human visual system

- Distortion/occlusion may impede understanding

Patrick Baudisch, “Focus plus context screens” http://patrickbaudisch.com

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Pan and zoom

Geometric vs. semantic zoom? Distortion?

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Semantic zoom

Hybrid views: drill down to display more information

+ Simultaneous display of overview and detail possible - Visual clutter: occlusion may impede understanding

Ken Perlin, Zoomable user interfaces http://mrl.nyu.edu/~perlin/experiments/zoom/Presentation.html

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Recall: Small multiples

Pictorial and tabular layouts Constancy of design

Same design structure repeated for all images

Economy of perception

Draws the eye to differences and outliers

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Recall: Small multiples

Invite comparison, contrasts

Must use same units, scale, measurements

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Coordinated multiple views

Use two or more views to support understanding of one concept Vary views by visual encoding, scale, data set

Different visual encodings of the same data

Different scale of same data, same encoding (overview+detail) Different data with same encoding, same scale (small multiples)

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Coordinated multiple views

TimeSearcher: Visual Exploration of Time Series Data http://www.cs.umd.edu/hcil/timesearcher

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Brushing

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Linking

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Coordinated multiple views

Addresses issue of scale: can’t ﬁt many marks/attributes in one view Addresses issues of data complexity

Design considerations:

Attention: Working memory, context switch Learnability

Screen real estate

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Operations on data tables

Rearrange by attribute Sort by attribute

Select a subset of records

Write a query: formal query language SELECT address

FROM bostondb

WHERE price <= 500,000 AND bedrooms >= 2

bathrooms >= 2 AND garage == true

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Dynamic queries

Visual model of the world: Objects

Actions: rapid, incremental, reversible Query: Direct selection

Results: “Immediate” (< 0.1 sec)

Ben Shneiderman et al, Dynamic HomeFinder, U. Maryland, 1993 http://www.youtube.com/watch?v=5X8XY9430fM

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Dynamic queries on the web

http://housingmaps.com http://housingmaps

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Dynamic queries on the web

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Dynamic queries on the web

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Dynamic queries

+ Responsive interaction: “ﬂy through the data” + Natural interaction: ﬁnd the “best” results + Exploration

- Conjunctive controls: requires user training - Spatially expensive

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Designing and evaluating a program

for molecular visualization

Dynamic queries: replace query language Multiple views: show multiple alignment

Variation: data types, encodings, resolution Conciseness

Linking and brushing Attention management