Information Visualization, Human-Computer Interaction, and Cognitive Psychology: Domain...
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Transcript of Information Visualization, Human-Computer Interaction, and Cognitive Psychology: Domain...
Information Visualization, Human-Computer Interaction, and Cognitive Psychology: Domain Visualizations
Kevin W. Boyack
Sandia National Laboratories
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Outline
• Motivation
• Process
• VxInsight
– description– demo
• Observations
• Recommendations
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Motivation for Study
• DIGITAL LIBRARIES (DL)
– need technology insertion from
•Information Visualization (IV)•Human-Computer Interaction (HCI)•Cognitive Psychology (CP)
• Are these fields merging? … If so, in what areas?
• Apply our visualization tool, VxInsight
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Study
• Create domain visualizations
• Combine the fields of IV, HCI, CP, and DL
• Several views
– article map– semantic map– co-author network
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Mapping Process Steps
• Data acquisition
• Define relationships
• Organize (cluster)
• Display, browse, access, analyze
Database search
Similarities based on common attributes
VxInsight ordination algorithm (VxORD)
VxInsight
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Steps
• Data acquisition
– Queried SCI (>1991) and SSCI (>1995) titles / abstracts / keywords
Database search
visualization (IV)exploration (IV)navigation (IV)browsing (IV)human-computer interaction (HCI)human-computer interface (HCI)
cognitive psychology (CP)cognitive science (CP)cognitive model (CP)cognitive system (CP)digital library (DL)mental model
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Steps
• Data acquisitionData acquisition
• Define relationships
– co-occurrence
Database searchDatabase search
Similarities based on common attributes
wij = Tij / sqrt(ni * nj)
Tij - number of keywords in common for articles i and jnk - number of keywords for any article k
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Steps
• Data acquisitionData acquisition
• Define relationshipsDefine relationships
• Organize (cluster)
– Force-directed placement algorithm
Database searchDatabase search
Similarities based Similarities based on common on common attributesattributes
VxInsight ordination algorithm (VxORD)
coordinateat/near objects ofdensity
edge oflength euclidean
edge of weight
node toconnected edges ofnumber
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Steps
• Data acquisitionData acquisition
• Define relationshipsDefine relationships
• Organize (cluster)Organize (cluster)
• Display, browse, access,analyze
Database searchDatabase search
Similarities based Similarities based on common on common attributesattributes
VxInsight VxInsight ordination ordination algorithm algorithm (VxORD)(VxORD)
VxInsight
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VxInsight™ ConfigurationVisualize and navigate
large data sets
Configurable menus; detailed information on single data objects
Viewfinder
Choice of landscape rendering
Peak labeling, updated dynamically upon zoom
Linkages between data elements
Mouse buttons control zooming in or out
Limit displayed data with date slider
SQL query to database lights up matching data objects
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Observations
• Few overlaps between fields
• Current overlap is Information Retrieval
• Terms show growth in smart algorithms
• Co-authorship network between fields is nonexistent
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Recommendations
• Focus collaborative work on Information Retrieval
• Additional focus on algorithms
• Should do author co-citation analysis
– Might show more extensive knowledge network
• Keywords are lacking on many articles
– LSA on titles/abstracts would include them