information graphics (draft)

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Information Graphics Jeff McNeill University of Hawaii at Manoa 2007 Copyright © Jeff McNeill, 2007 Licensed under Creative Commons Attribution 3.0 http://creativecommons.org/licenses/by/3.0/

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Page 1: Information Graphics (Draft)

Information Graphics

Jeff McNeill

University of Hawaii at Manoa

2007

Copyright © Jeff McNeill, 2007Licensed under Creative Commons Attribution 3.0http://creativecommons.org/licenses/by/3.0/

Page 2: Information Graphics (Draft)

Overview• This is an overview of information graphics,

good, bad and ugly

• These can be extremely helpful in walkthrough and summary slides

Page 3: Information Graphics (Draft)

List of Information Graphics• 2 x 2 chart• Bar chart• Concept map• Diagram• Gannt chart• Line chart• Map• Org chart• Parallel coordinates• Pert chart• Process map• Scatter plot• Table• Tag cloud• Venn diagram

• Meaningful elements– Color– Size– Location– Connections (lines)– Directionality (arrows)– Degree of overlap– Proximity– Order– Label– Scale

• Do not use– Radar diagram

• Parallel coordinates instead– Pie chart

• Bar chart instead

Page 4: Information Graphics (Draft)

2 x 2 chart* 2 dimensions by 2 measurements

Bar chart One or more measures, can be comparative

Concept map* Shows connections and relationships

Diagram Drawing illustrating parts and relationships

Gannt chart (Project management) shows dependencies & time

Line chart* Like bar chart but shows slope between datapoints

Map Geographical or any 2d space plotting

Org chart Don’t confuse with concept map, only for orgs

Parallel coordinates

For 3 or more dimensions, better than radar diagrams or multiple bar or 2 x 2 charts

Pert chart Individual time assignments (project management)

Process map* Shows steps in a process, left-to-right with arrows

Scatter plot Usually 2 dimensional plotting, shows clusters

Table* The basic structured way of comparing items

Tag cloud Shows frequency, centrality, importance of terms

Venn diagram* 2+ items with overlapping and non- parts

Information Graphics Descriptions

* Included in the Notetaking Toolkit.

Page 5: Information Graphics (Draft)

Graphics Concepts

• Chartjunk• Data-to-ink ratio

• Colorblindness

Page 6: Information Graphics (Draft)

Notetaking Toolkit• This toolkit identifies information graphics

which are easy to create on the fly when taking notes

• These should be mastered first and can be useful in gathering information, not just in presenting

• Includes the 2 x 2 chart, Concept map, Line chart, Process map, Table, and Venn diagram

Page 7: Information Graphics (Draft)

2 x 2 Chart*

• Simplified version of the Line chart

• Can be used as a Scatter plot overlay

• It divides each of two dimensions into two levels, usually low and high

• Quadrants

• Most desirable– Upper right

* Included in the Notetaking Toolkit.

low

low

high

high

second dimension

firs

t d

imen

sio

n

Page 8: Information Graphics (Draft)

2 x 2 Chart* Components

• Components– Datapoints– X and Y Axes– X and Y Axes Labels– X and Y Axes Level Labels– Partition lines into quadrants– Datapoint labels (or legend)

• Variations– Datapoints can be scatterplot along interval

scales or simply categories

low

low

high

high

Different

Good

Good but not

different

Not good and not different

Different but not good

Good and

different

Page 9: Information Graphics (Draft)

Bar Chart

* Included in the Notetaking Toolkit.

Page 10: Information Graphics (Draft)

Concept Map*

• Hierarchical composition of elements

• Visualizes connections between elements (concepts and examples)

• Can be read to form sentences

• Superior to “mind mapping” (Buzan)

• From Novak based on Ausubel

• Similar to process map, which indicates horizontal, time-ordered relationships

• Useful for component decomposition* Included in the Notetaking Toolkit.

Page 11: Information Graphics (Draft)

Concept Map* Components

• Elements (circles)

• Element labels (inside element)

• Relationships (lines w/ arrows)

• Relationship labels (optional)

• Vertical placement– Indicates hierarchy– Use bottom-up arrows for Goldratt

reality trees

• See also Process map* Included in the Notetaking Toolkit.

Food

BeanNut

PeanutAlmon

d

Examples

Includes

Page 12: Information Graphics (Draft)

http://www.mc.maricopa.edu/dept/d43/glg/Study_Aids/concept_maps/conceptmaps.html

Page 13: Information Graphics (Draft)

http://www.mc.maricopa.edu/dept/d43/glg/Study_Aids/concept_maps/conceptmaps.html

Page 14: Information Graphics (Draft)

Diagram

* Included in the Notetaking Toolkit.

Page 15: Information Graphics (Draft)

Gannt Chart

Page 16: Information Graphics (Draft)

Line Chart*

• Similar to the 2 x 2 and chart plots

• Like bar chart but with slope

• Usually uses ratio data (interval w/ zero)

• Can show relationship between two or more variables on different scales

* Included in the Notetaking Toolkit.

then

less

now

moreChoices

Time

Page 17: Information Graphics (Draft)

• X and Y axes• X and Y axes labels• One or more lines• Data set (optional)• Scale indicator labels• Scale indicators (optional)• Variable labels or legend• Projected values (optional) (dotted lines)

Line Chart* Components

* Included in the Notetaking Toolkit.

2005

0

1,000

Choices

Time

500

2006 2007

220 310 570

680 580 400

750

250

Page 18: Information Graphics (Draft)

Map

Page 19: Information Graphics (Draft)

Org Chart

• Typically squares and straight lines• Do not use org chart look for non org charts• See sociogram (type of concept map)• Components include positions and/or persons• Hierarchical order• Boss and direct reports• Support staff off to side

PresidentChris Charlie

VPAlice Alfa

VPBob Bravo

AssistantDon Delta

Page 20: Information Graphics (Draft)

Parallel Coordinateshttp://www.nbb.cornell.edu/neurobio/land/PROJECTS/Inselberg/

Parallel Coordinates

Virtual Ludic Robotic Fantastic

Classroom Low Low Low Low

Online High Medium Medium Low

Virtual World High High Medium High

V L FR

Page 21: Information Graphics (Draft)

Radar Diagram (Do Not Use)

Radar Diagram

Virtual Ludic Robotic Fantastic

Classroom Low Low Low Low

Online High Medium Medium Low

Virtual World High High Medium High

V

L

F

R

Use parallel coordinates instead

http://www.internet4classrooms.com/excel_radar.htm

Page 22: Information Graphics (Draft)

Pert Chart

Page 23: Information Graphics (Draft)

Process Map*

• Shows parts and steps

• Similar to GANTT chart, which shows dependencies and a timeline

* Included in the Notetaking Toolkit.

Step 1 Step 2 Step 3

Page 24: Information Graphics (Draft)

Scatter Plot

Page 25: Information Graphics (Draft)

Table*

• Extremely flexible and useful• Can be used whenever there are two or more

things to compare/contrast• Columns, rows, headers, and data• Primary data collection is row• Variables and values are columns• Center and align when appropriate• Headers usually bold• Order of elements

– Time, importance, alphabetical

* Included in the Notetaking Toolkit.

Page 26: Information Graphics (Draft)

Table* Examples

• Data collection units are ususally rows• Totals go down rows (vs. across columns)• Any information can be placed in tables• Increases speed and accuracy of understanding

and visual comparisons

* Included in the Notetaking Toolkit.

Ver 1 Ver 2

Cost $1.00 $2.00

Weight 100 lbs 50 lbs

Sold 1,000 2,000

Version Cost Weight Sold Sales

Ver 1 $1.00 100 lbs 1,000 $1,000

Ver 2 $2.00 50 lbs 2,000 $4,000

Total 3,000 $5,000

Incorrect Correct

Page 27: Information Graphics (Draft)

Tag (Text) Cloud

• Alphabetical or some other meaningful arrangement

• Meaningful dimensions– Size = frequency– Color = time (or other), optional– Proximity = similarity

• Advanced versions become similar to multidimensional cluster plots

Page 28: Information Graphics (Draft)

Tag (Text) Cloud

Steve Jobs2007 Macworld ConferenceAvg. Words/Sentence: 10.5Lexical Density: 16.5%Hard Words: 2.9%Gunning Fog Index: 5.5

Bill Gates2007 Consumer Electronics ShowAvg. Words/Sentence: 21.6Lexical Density: 21.0%Hard Words: 5.11%Gunning Fog Index: 10.7

Page 29: Information Graphics (Draft)

• Indicates commonality and difference• Overlaps share or combine qualities

Venn Diagram*

Ice Cream

Cake

Chocolate

Chocolate Ice Cream Cake

Page 30: Information Graphics (Draft)

Additional Notes

Page 31: Information Graphics (Draft)

Information VisualizationCMSC 838B – Spring 2003

Visual DesignBenjamin B. Bederson

University of Maryland

www.cs.umd.edu/~bederson

This presentation adapted from John Stasko

Page 32: Information Graphics (Draft)

Semiotics• The study of symbols and how they convey

meaning

• Classic book:– J. Bertin, 1983, The Semiology of Graphics

This presentation taken largely from John Stasko

Page 33: Information Graphics (Draft)

Related Disciplines• Psychophysics

– Applying methods of physics to measuring human perceptual systems

• How fast must light flicker until we perceive it as constant?

• What change in brightness can we perceive?

• Cognitive psychology– Understanding how people think, here, how it

relates to perception

Page 34: Information Graphics (Draft)

Potential Preattentive Features

lengthwidthsizecurvaturenumberterminatorsintersectionclosure

hueintensityflickerdirection of motionbinocular lustrestereoscopic depth3-D depth cueslighting direction

Page 35: Information Graphics (Draft)

Key Perceptual Properties• Brightness

• Color

• Texture

• Shape

Page 36: Information Graphics (Draft)

Luminance/Brightness• Luminance

– Measured amount of light coming from some place

• Brightness– Perceived amount of light coming from source

Page 37: Information Graphics (Draft)

Color for Categories• Can different colors be used for categories

of nominal variables?– Yes– Ware’s suggestion: 12 colors

• red, green, yellow, blue, black, white, pink, cyan, gray, orange, brown, purple

Page 38: Information Graphics (Draft)

Color Categories• Are there certain

canonical colors?– Post & Greene ‘86

had people namedifferent colors on amonitor

– Pictured are oneswith > 75%commonality

Page 39: Information Graphics (Draft)

Color for Sequences

Can you order these (low->hi)

Page 40: Information Graphics (Draft)

Possible Color Sequences

Gray scale Single sequencepart spectral scale

Full spectral scale Single sequencesingle hue scale

Double-endedmultiple hue scale

Page 41: Information Graphics (Draft)

Color Purposes• Call attention to specific data

• Increase appeal, memorability

• Increase number of dimensions for encoding data– Example, Ware and Beatty ‘88

• x,y - variables 1 & 2• amount of r,g,b - variables 3, 4, & 5

Page 42: Information Graphics (Draft)

1. Graph• Graph - Show the relationships between

variables’ values in a data table– Visual display that illustrates one or more

relationships among entities– Shorthand way to present information– Allows a trend, pattern or comparison to be

easily comprehended

Page 43: Information Graphics (Draft)

Issues• Critical to remain task-centric

– Why do you need a graph?– What questions are being answered?– What data is needed to answer those

questions?– Who is the audience?

time

money

Page 44: Information Graphics (Draft)

Graph Components• Framework

– Measurement types, scale

• Content– Marks, lines, points

• Labels– Title, axes, ticks

Page 45: Information Graphics (Draft)

Basic Data Types• Nominal (qualitative)

– (no inherent order)– city names, types of diseases, ...

• Ordinal (qualitative)– (ordered, but not at measurable intervals)– first, second, third, …– cold, warm, hot

• Interval (quantitative)– list of numbers

Page 46: Information Graphics (Draft)

Common Graph Formats

Linegraph

Bargraph

Scatterplot

Y-axis is quantitativevariable

See changes overconsecutive values

Y-axis is quantitativevariable

Compare relative pointvalues

Two variables, want tosee relationship

Is there a linear, curved orrandom pattern?

Page 47: Information Graphics (Draft)

Graphing Guidelines• Independent vs. dependent variables

– Put independent on x-axis– See resultant dependent variables along y-axis

• If there are two independent variables, often place them along the 2 axes (you choose which) and then the mark may encode the dependent variable

Page 48: Information Graphics (Draft)

2. Chart

• Structure is important, relates entities to each other• Primarily uses lines, enclosure, position to link entities

Examples: flowchart, family tree, org chart, ...

Page 49: Information Graphics (Draft)

3. Map

• Representation of spatial relations• Locations identified by labels

Page 50: Information Graphics (Draft)

Choropleth Map

Areas are filledand coloreddifferently toindicate someattribute of thatregion

Page 51: Information Graphics (Draft)

Cartography• Cartographers and map-makers have a

wealth of knowledge about the design and creation of visual information artifacts– Labeling, color, layout, …

• Information visualization researchers should learn from this older, existing area

Page 52: Information Graphics (Draft)

4. Diagram

• Schematic picture of object or entity• Parts are symbolic

Examples: figures, steps in a manual, illustrations,...

Page 53: Information Graphics (Draft)

Tufte’s Design Principles• 1. Tell the truth

– Graphical integrity

• 2. Do it effectively with clarity, precision…– Design aesthetics

E. Tufte, The Visual Display of Quantitative Information (1983)E. Tufte, Envisioning Information (1990)E. Tufte, Visual Explanations (1997)

Page 54: Information Graphics (Draft)

1. Graphical Integrity

20022001200019991998

500

475

450

Stock market crash?

Your graphic should tell the truth about your data

Page 55: Information Graphics (Draft)

Show entire scale

20022001200019991998

500

250

0

Page 56: Information Graphics (Draft)

Show in context

20001990198019701960

500

250

0

Page 57: Information Graphics (Draft)

Measuring Misrepresentation

• Visual attribute value should be directly proportional to data attribute value

• Height/width vs. area vs. volume

Size of effect shown in graphicSize of effect in data

Lie factor =

“Lie factor” = 2.8

Page 58: Information Graphics (Draft)

2. Design Principles• Maximize data-ink ratio

Data ink ratio =Data ink

Total ink used in graphic

= proportion of graphic’s ink devoted to the non-redundant display of data-information

Page 59: Information Graphics (Draft)

Design Principles• Avoid chartjunk

– Extraneous visual elements that detract from message

don’t be the duck of architecture

Page 60: Information Graphics (Draft)

Design Principles• Utilize multifunctioning graphical elements

– Graphical elements that convey data information and a design function

Page 61: Information Graphics (Draft)

Design Principles• Use small multiples

– Repeat visually similar graphical elements nearby rather than spreading far apart

Page 62: Information Graphics (Draft)

Design Principles• Show

mechanism, process, dynamics, and causality– Cause and

effect are key

Page 63: Information Graphics (Draft)

Design Principles• Escape flatland

– Data is multivariate– Doesn’t necessarily mean 3D projection

Page 64: Information Graphics (Draft)

Design Principles• Utilize layering and separation

Page 65: Information Graphics (Draft)

Design Principles• Utilize narratives

of space and time– Tell a story of

position and chronology through visual elements

Page 66: Information Graphics (Draft)

Design Principles• Content is king

– Quality, relevance and integrity of the content is fundamental

– What’s the analysis task? Make the visual design reflect that

– Integrate text, chart, graphic, map into a coherent narrative

Page 67: Information Graphics (Draft)

Graph and Chart Tips• Avoid separate legends and keys – Put that in the graphic• Make grids & labeling faint so that they recede into

background

Page 68: Information Graphics (Draft)

Proper Color Use• To label

• To measure

• To represent or imitate reality

• To enliven or decorate

Page 69: Information Graphics (Draft)

Color Examples

Page 70: Information Graphics (Draft)

Guides for Enhancing Visual Quality

• Attractive displays of statistical info– have a properly chosen format and design– use words, numbers and drawing together– reflect a balance, a proportion, a sense of relevant scale– display an accessible complexity of detail– often have a narrative quality, a story to tell about the

data– are drawn in a professional manner, with the technical

details of production done with care– avoid content-free decoration, including chartjunk

Page 71: Information Graphics (Draft)

Graphical Displays Should• Show the data• Induce the viewer to think

about substance rather than about methodology, graphic design the technology of graphic production, or something else

• Avoid distorting what the data have to say

• Present many numbers in a small space

• Make large data sets coherent

• Encourage the eye to compare different pieces of data

• Reveal the data at several levels of detail, from a broad overview to the fine structure

• Serve a reasonably clear purpose: description, exploration, tabulation, or decoration

• Be closely integrated with statistical and verbal descriptions of a data set