information visualisation (multimedia 2009 course)
DESCRIPTION
Introduction to information visualisation (Multimedia course)TRANSCRIPT
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Information Visualisatie
... is the use of interactive visual representations of abstract data to amplify cognition. [Card et al.]
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Information Visualisatie
... is the use of interactive visual representations of abstract data to amplify cognition. [Card et al.]
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Let A, B, C, D, E be natural persons, departments of universities, states, etc. • A is positively affected by B and affects B, C and E positively. • B is affected by A and C positively and affects D negatively and A positively. • C is positively affected by A, negatively affected by E, and affects B positively. • B and E negatively affect D. • E affects C and D negatively and is positively affected by A.
What’s going on?
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Information Visualisation
A B
C
DE
Let A, B, C, D, E be natural persons, departments of universities, states, etc. • A is positively affected by B and affects B, C and E positively. • B is affected by A and C positively and affects D negatively and A positively. • C is positively affected by A, negatively affected by E, and affects B positively. • B and E negatively affect D. • E affects C and D negatively and is positively affected by A.
What’s going on?
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Information Visualisation
A B
C
DE
“A picture is worth a 1000 words...”
Let A, B, C, D, E be natural persons, departments of universities, states, etc. • A is positively affected by B and affects B, C and E positively. • B is affected by A and C positively and affects D negatively and A positively. • C is positively affected by A, negatively affected by E, and affects B positively. • B and E negatively affect D. • E affects C and D negatively and is positively affected by A.
What’s going on?
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Information Visualisation
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Use Human Perceptual System
Pattern recognition
scan, recognize, remember
Graphical elements facilitate comparisons
length, shape, orientation, texture, color
Animation
time changes
The Visualisation Pipeline
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The Visualisation Pipeline
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Issues
How to provide efficient and effective access to large collections of data
to enable insight in the contents of such a collection.
using information visualisation techniques
Does it work better?
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[Van Wijk, 2006], [Spoerri, 2004]
CS1: Visualising a LOR
Study LOM [IEEE LOM, 2002]
start from Topic of LO [France et al., 1999], [Najjar, 2008a]
Study existing information visualisation techniques
Tree-map visualisation [Shneiderman and Johnson, 1991], [Shneiderman, 1996], [Lamping
and Rao, 1996], [Venn, 1880], [Kobsa, 2004], [Wang et al., 2006], [Rivadeneira and Bederson, 2003], [Bruls et al., 2000], etc.
Design & practical creation of an exploratory search application
Evaluation
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[IEEE LTSC LOM, 2002]
Learning Object Metadata
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[IEEE LTSC LOM, 2002]
Learning Object Metadata
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[IEEE LTSC LOM, 2002]
Learning Object Metadata
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Tree-map AlgorithmAriadne Classification
Exact Sciences
Informatics Physics
Human Sciences
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Tree-map AlgorithmAriadne Classification
Exact Sciences
Informatics Physics
Human Sciences
Ariadne Classification
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Tree-map AlgorithmAriadne Classification
Exact Sciences
Informatics Physics
Human Sciences
Ariadne Classification
Exact Sciences
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Tree-map AlgorithmAriadne Classification
Exact Sciences
Informatics Physics
Human Sciences
Ariadne Classification
Exact Sciences Human Sciences
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Tree-map AlgorithmAriadne Classification
Exact Sciences
Informatics Physics
Human Sciences
Ariadne Classification
Exact Sciences Human Sciences
Informatics
Physics
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Access to the Ariadne KPS
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Exact SciencesHuman
Sciences
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Access to the Ariadne KPS
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Access to the Ariadne KPS
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Access to the Ariadne KPS
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Overview first, Zoom and Filter, then Details on Demand“Visual Information-Seeking Mantra” [Shneiderman, 1996]
Access to the Ariadne KPS
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Overview first, Zoom and Filter, then Details on Demand“Visual Information-Seeking Mantra” [Shneiderman, 1996]
Access to the Ariadne KPS
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Overview first, Zoom and Filter, then Details on Demand“Visual Information-Seeking Mantra” [Shneiderman, 1996]
Access to the Ariadne KPS
Access to Ariadne KPS: Demo
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Access to Ariadne KPS: Demo
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Prototype Evaluation
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Prototype EvaluationStudy 1: Perception of 1 infovis expert user [Nielsen, 1992b]
7 user tasks to support Exploratory Search [Shneiderman, 1996]
overview, zoom, filter, details-on-demand, relate, history, extract
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Prototype EvaluationStudy 1: Perception of 1 infovis expert user [Nielsen, 1992b]
7 user tasks to support Exploratory Search [Shneiderman, 1996]
overview, zoom, filter, details-on-demand, relate, history, extract
Study 2: User Study [Rubin, 1994], [Nielsen, 1992a], [Likert, 1932], [Najjar et al., 2005],
10 users, 2 groups of 5, independent tasks
comparison traditional tool (SILO) and Prototype
Task time, Task Accuracy, Satisfaction (Likert Scale)
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Prototype EvaluationStudy 1: Perception of 1 infovis expert user [Nielsen, 1992b]
7 user tasks to support Exploratory Search [Shneiderman, 1996]
overview, zoom, filter, details-on-demand, relate, history, extract
Study 2: User Study [Rubin, 1994], [Nielsen, 1992a], [Likert, 1932], [Najjar et al., 2005],
10 users, 2 groups of 5, independent tasks
comparison traditional tool (SILO) and Prototype
Task time, Task Accuracy, Satisfaction (Likert Scale)
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Visual Information Seeking
Overview
Zoom
Filter
Details-on-Demand
Relate
History & Extract
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CS2: Eurosong 2009 Results
http://blob.creanode.com/blob/eu2009/
Visualisation for analysis16
CS3: EC-TEL Proceedings
Visualisation of concepts17
Music Industry
bron: http://en.wikipedia.org/wiki/Music_industry18
CS4: Visualising ReuseStudy ALOCOM [Verbert et al., 2005]
isPartOf/hasPart relations
Study existing information visualisation techniques
Node-link graph [Ware and Franck, 1994], [Becker et al., 1995], [Shneiderman, 1996]
Design & practical creation of an exploratory search application with advanced support to
Gain insight in actual reuse of the different components
Search & Find relevant components
Evaluation
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Reuse?
Repository filled with 48286 components from 653 presentations:
14113 slides5768 images198 tables26 diagrams27543 text fragments
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Reuse?
Repository filled with 48286 components from 653 presentations:
14113 slides5768 images198 tables26 diagrams27543 text fragments
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➡ Average reuse-value: 0.22
Reuse?
Repository filled with 48286 components from 653 presentations:
14113 slides5768 images198 tables26 diagrams27543 text fragments
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➡ Average reuse-value: 0.22
Access to ALOCOM: Demo
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Access to ALOCOM: Demo
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Access to ALOCOM: Demo
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Evaluation
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Evaluation
Expert review
4 expert users in TEL community
prototype = effective & efficient
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Evaluation
Expert review
4 expert users in TEL community
prototype = effective & efficient
Recommendations
calculate statistics, social network of authors, reuse through time, other dynamic controls, generalise target group
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CS5: http://www.liveplasma.com/
Visualisation for recommendation 23
CS6: Visualising Social BookmarksStudy social bookmarks & metadata
del.icio.us [delicious, 2008], CALIBRATE [CALIBRATE, 2008]
Investigate existing information visualisation techniques
Cluster map [Fluit et al., 2005], [Dodge and Kitchin, 2001], [Pampalk, 2006], [Heer and Boyd, 2005]...
Design & practical creation of an exploratory search application with advanced support to
provide understanding in bookmarks, tags, users and the relationships between them
Evaluation
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Clustermap Algorithm
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Clustermap Algorithm
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Clustermap Algorithm
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Clustermap Algorithm
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Clustermap Algorithm
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Clustermap Algorithm
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Access to del.icio.us: Demo
Selection Widget
Empty Visualisation:
“Start with what you know, then grow”
Filters
Results
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Access to del.icio.us: Demo
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Prototype Evaluation
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Prototype EvaluationStudy 1: Expert review by 4 experts
portal integration, zooming, learning curve, complexity, timeline integration
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Prototype EvaluationStudy 1: Expert review by 4 experts
portal integration, zooming, learning curve, complexity, timeline integration
Study 2: Subjective review by 10 end users to assess
effectiveness
efficiency
subjective acceptance
usability issues
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CS7: Many Eyes: Visualisation for the masses
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/finding-new-music-artists-takes-time
Visualisation for recommendation 28
CS8: Visualising a Network of LORS
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CS8: Visualising a Network of LORS
Unlock the deep web of the learning repository networks that members of GLOBE maintain [Globe, 2008]
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CS8: Visualising a Network of LORS
Unlock the deep web of the learning repository networks that members of GLOBE maintain [Globe, 2008]
Timeline Visualisation of Search History
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Find Material: Demo
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Find Material: Demo
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Timeline Visualisation of History: Demo
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Timeline Visualisation of History: Demo
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CS9: Listening History
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http://www.leebyron.com/what/lastfm/example.jpg
CS10: Emotion in Lyrics
HAPPY ANGRY
SURPRISEFEAR
SADNESS DISGUSThttp://www.synesketch.krcadinac.com/
Integrated Karaoke Player with Synesketch
On-the-fly visualisation of lyrics during Song.
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Thriller, Michael Jackson
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Thriller, Michael Jackson
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Shiny Happy People, REM
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Shiny Happy People, REM
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Information Visualization Manifesto (1/2)
“The purpose is insight, not pictures” (Sheiderman)
“Form Follows Function”
“Start with a Question”
“Interactivity is Key”
“Cite your source”
http://www.visualcomplexity.com/vc/blog/?p=64436
Information Visualization Manifesto (2/2)
“The power of Narrative”
“Do not glorify Aesthetics”
“Look for Relevancy”
“Embrace Time”
“Aspire for Knowledge”
“Avoid gratuitous visualizations”
http://www.visualcomplexity.com/vc/blog/?p=64437
Pointers
http://wearecolorblind.com/articles/quick-tips/
http://visualizingmusic.com/
http://infosthetics.com/
http://www.visualcomplexity.com/vc/
http://bestario.org/research/remap
http://visualthinkmap.blogspot.com/
http://www.infovis.net/
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Libraries
http://wiki.okfn.org/OpenVisualisation
http://flare.prefuse.org/
http://iv.slis.indiana.edu/sw/
http://abeautifulwww.com/2008/09/08/20-useful-visualization-libraries/
etc.
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Further Readings
“Readings in Information Visualization: Using Vision to Think”, Card, S et al
“Show Me the Numbers”, Few, S.
“Beautiful Evidence”, Tufte, E.
“Information Visualization. Perception for design”, Ware, C.
etc.
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Thanks
Questions?
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