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ITM 734 Fall 2005. Information Visualization Part 1. Dr. Cindy Corritore Creighton University. principles of good graphics (Tufte). data graphics should draw viewers attention to the substance and meaning of the data, not to something else goal: help user reason about the data

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Information visualization part 1

ITM 734

Fall 2005

Information Visualization Part 1

Dr. Cindy Corritore

Creighton University


Principles of good graphics tufte

principles of good graphics (Tufte)

  • data graphics should draw viewers attention to the substance and meaning of the data, not to something else

    • goal: help user reason about the data

    • relative rather than absolute judgements

      Principle 1: above all else, always show the data!

Corritore, 2005


Information visualization part 1

Corritore, 2005


Principles of good graphics

principles of good graphics

  • chartjunk - non-data ink, decoration, over-redundancy

    • moire vibration - appearance of movement

    • grid - remove or mute

    • unnecessary 3-D

      Principle 2: remove chart junk

Corritore, 2005


Information visualization part 1

Corritore, 2005


Information visualization part 1

Corritore, 2005


Principles of good graphics1

principles of good graphics

graphic content consists of:

data ink and non-data ink

  • data ink is non-erasable core of graphic

  • text can be data ink

  • get rid of the rest as much as possible

Corritore, 2005


Principles of good graphics2

principles of good graphics

Data-Ink Ratio:

data ink / total ink used

Principle 3: maximize the data-ink ratio, within reason (erase non-data ink as much as possible)

Corritore, 2005


Information visualization part 1

Corritore, 2005


Information visualization part 1

Corritore, 2005


Information visualization part 1

Corritore, 2005


Principles of good graphics3

principles of good graphics

  • redundancy can go too far

    • bilateral symmetry - can reduce

      • have double redundancy - people just process first half anyways, then check to see other half is the same

        Principle 4: erase redundant data ink, within reason

Corritore, 2005


Information visualization part 1

What can be erased (redundant)?

Corritore, 2005


Information visualization part 1

Word ‘Year’

’19’

Data labels on left or in columns

No color or no borders

Grid lines

Corritore, 2005


Principles of good graphics4

principles of good graphics

  • proximity principle - integrate text and graphics

    • but be careful …

      Principle 5: integrate text and graphics, when possible.

Corritore, 2005


Information visualization part 1

We don’t estimate volume and area well – back barrel is much larger

than actual 30% growth.

Corritore, 2005


Information visualization part 1

This is much better -

Corritore, 2005


Principles of good graphics5

principles of good graphics

  • know a problem if you have to talk yourself through it

    “let’s see, if it is yellow, it is …”

    • often involve color as we don’t give visual ordering to colors

    • use varying shades of gray - see order better

      Principle 6: keep it simple and understandable to audience

Corritore, 2005


Information visualization part 1

Two charts of the same data (linguistic ability of Canadians

correlated with primary language)

Corritore, 2005


Overall

overall

  • focus on the data, not the chart elements

  • emphasize the important (not the unimportant)!

Corritore, 2005


Information visualization part 1

Corritore, 2005


Problem

problem ….

Everyone spoke of an information overload,

but what there was in fact

was a non-information overload.

Richard Saul Wurman,

What-If, Could-Be (Philadelphia, 1976)

Corritore, 2005


Overview

overview

  • increasingly common to actually have all of the data potentially available

    • how to map and use it becomes harder and harder

  • challenges: world of the computer and data and world of the human

    • bridge between the intuitive, creative, experience and the digital, analytical

      Solution: Involve the user!

corritore, 734


Challenges

challenges

Corritore, 2005


Challenge 1

challenge 1

1. growing volume of data with declining information content

  • provision of data ever cheaper and available

  • our ability to consume information largely unchanged

  • Key Issues: exploring, navigation, browsing, immersion/involvement of human and their perceptional apparatus

  • Corritore, 2005


    Challenge 11

    challenge 1

    • interactive visualization interface for exploration of network fault data (network alarm data)

      • experienced network administrator looks for trends/patterns

      • interactive with filters

    Corritore, 2005


    Challenge 12

    challenge 1

    • large information spaces

    Corritore, 2005


    Challenge 2

    challenge 2

    2. convert appropriate data to relevant data: analysis and interpretation

    • summarize and compress without signif. loss of content

    • complex data analysis tools and models for analysis hard to use

    • goal: human involvement in processing and analysis of data

      • experience and intuition

    Corritore, 2005


    Challenge 21

    challenge 2

    • visual interface to model that assess customer perception of phone connections

      • 12 input parameters specifying circuit

      • user explores performance as a func. of any two parameters

    Corritore, 2005


    Challenge 22

    challenge 2

    • visual correlation between lightning strikes & network alarms

      • time series movie

    Corritore, 2005


    Challenge 3

    challenge 3

    • managing abstract problems/intangibles against increasingly short timescales

      • build a building - can see the progress; intangibles hard to visualize

      • better informed decisions

      • goal: retain overview of abstract problem while providing for immediate visibility of changes

    Corritore, 2005


    Challenge 31

    challenge 3

    • software development

      • each sphere a module (diameter - size)

      • lines are func. calls

      • change requests mapped to rate of spin

    Corritore, 2005


    Challenge 32

    challenge 3

    • five releases showing selected metrics

      • most recent @ top

      • points modules

      • as evolves, see changes in system

        • perhaps spikes overly convoluted modules

    Corritore, 2005


    Challenge 4

    challenge 4

    • communicate a vision - wide audience and increasingly conceptual

      • wider, less specialist audience; mix of technical, business, customer

      • hence, must provide a shared experience

        picture is worth 1,000 words

    Corritore, 2005


    Information visualization part 1

    Goal: let human observe, manipulate, search, navigate, explore, filter, discover, understand, and interact with large volumes of data rapidly

    Corritore, 2005


    Shneiderman

    shneiderman

    • King of Direct Manipulation

      • mantra: overview first, zoom and filter, details on demand

    Corritore, 2005


    Data types

    data types

    • 1D

      • lists, words

      • http://www.textarc.org/Alice2inWindow.html - Alice in Wonderland

      • fisheye – next week

    • 2D

      • map data (gis)

      • google earth (demo)

      • smartmoney.com - http://www.smartmoney.com/maps/?nav=dropTab

    Corritore, 2005


    Data types1

    data types

    • 3D

      • scientific visualization (molecules, etc)

      • ThemeView - http://in-spire.pnl.gov/IN-SPIRE_Help/galaxy.html - shows documents and their relationships

        • galaxy view

        • themeview

      • task manager –

      • Digital library prototype http://student.ifs.tuwien.ac.at/~andi/libViewer/

    Corritore, 2005


    Data types2

    data types

    • 3D and file systems

    Corritore, 2005


    Data types3

    data types

    • multi-dimensional

      • n-dimensional space – examples?

      • spotfire

    • temporal

      • time lines (stock markets, health care)

    Corritore, 2005


    Data types4

    data types

    • temporal

      • variables over time

      • metaphors

    • River metaphor: Each attribute is mapped to a “current” in the “river”, flowing along the timeline

      Current width ~= strength of theme

      River width ~= global strength

      Color mapping (similar themes – same color family)

      Time line

    Corritore, 2005


    Information visualization part 1

    A company’s patent activity

    Corritore, 2005


    Extended exploration

    extended exploration

    Linking a river to a histogram

    Comparing two rivers

    Corritore, 2005


    Critique

    critique

    Strong points:

    • Intuitive exploration of temporal changes and relations

    • Evalutation + improvements

    • Applicable to general attributes

    Weak points:

    • Limited number of themes / attributes

    • Interpolated values / outer attributes misleading

    • No ability to reorder currents

    • Performance issues

    Corritore, 2005


    Spiral example

    spiral Example

    • Spokes (months) and spiral guide lines (years)

    • Planar spiral

    • Distinguishable patterns (rainy season / 1984)

    Chimpanzees Monthly food consumption 1980-1988

    Corritore, 2005


    Data types5

    data types

    • temporal –

      • Time Searcher (http://www.cs.umd.edu/hcil/timesearcher/videos/ts2_HCILsoh2005R.html) – movie

      • lifelines - http://www.cs.umd.edu/hcil/lifelines/latestdemo/chi.html

    Corritore, 2005


    Data types6

    data types

    • trees

      • hierarchies (file structure)

      • magnifind

      • lexusnexus - http://www.lexis-nexis.com/lncc/hyperbolic/default.htm

      • Cop - http://ai.bpa.arizona.edu/COPLINK/demo/Visualization.htm

      • Visual Thesauru

    Corritore, 2005


    Data types7

    data types

    • network – look at these next week

    Corritore, 2005


    Challenges1

    challenges

    • multiple data input

    • combine visual and text

    • show relationships

    • large information spaces – overview then details

    • collaboration?

    • navigation must be accurate

    • all elements must be interactive

    • new paradigms ……

    Corritore, 2005


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