Transcript What Researchers Want - UMD Department of Computer Science

What Researchers Want
Cody Dunne
Links from this talk:
Dept. of Computer Science and
Human-Computer Interaction Lab,
University of Maryland
[email protected]
bit.ly/stmwant
STM 3rd Master Class
November 7-9, 2011 Adelphi, MD, USA
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Researchers want to…
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Find a specific paper
Explore a research area
Do retrospective analysis
Share their results
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1. Find a specific paper
• Metadata or PDF?
• From memory (search)
• From reference list
– DOI/URL
– Search
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2. Exploring a research area
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Foundations
Emerging research topics
State of the art/open problems
Collaborations & relationships between
Communities
• Field evolution
• Easily understandable surveys
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User requirements
• Control over the paper collection
– Choose custom subset via query, then iteratively drill
down, filter, & refine
• Overview either as visualization or text statistics
– Orient within subset
• Easy to understand metrics for identifying
interesting papers
– Ranking & filtering
• Create groups & annotate with findings
– Organize discovery process
– Share results
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Action Science Explorer
• Bibliometric lexical link mining to create a
citation network and citation context
• Network clustering and multi-document
summarization to extract key points
• Potent network analysis and visualization tools
www.cs.umd.edu/hcil/ase
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Reference management & grouping
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Citation network overview
Communities, outliers, invalid data
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Statistics & visualization
• Network statistics
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Degree
Betweenness
Closeness
Pagerank
• Attributes
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Year
Downloads
Citations
References
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Field evolution
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Citation context &
summarization
• Citation context
– Key contributions
– Critical reception
– Citations to subsequent/similar work
• Hyperlinked citations in text
– See surrounding context of citation
– View cited papers while reading
• Multi-document summarization
– Citation context
– Abstract
– Full text
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3. Retrospective analysis
• Automatic collection & processing of
bibliometric data
• Easy access to visual analytic tools for finding
clusters, trends, outliers
• Communities for sharing data, tools, & results
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STICK Project
• Scientific, data-driven way to track innovations
– Vs. current expert-based, time consuming
approaches (e.g., Gartner’s Hype Cycle, tire track
diagrams)
• Includes both concept and product forms
– Study relationships between
• Study the innovation ecosystem
– Organizations & people
– Both those producing & using innovations
stick.ischool.umd.edu
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Case study: tree visualization
• Problem: Traditional 2D node-link diagrams of
trees become too large
• Solutions:
– Treemaps: Nested Rectangles
– Cone Trees: 3D Interactive Animations
– Hyperbolic Trees: Focus + Context
• Measures:
– Papers, articles, patents, citations,…
– Press releases, blog posts, tweets,…
– Users, downloads, sales,…
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Treemaps: nested rectangles
www.cs.umd.edu/hcil/treemap-history
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Smartmoney MarketMap Feb 27, 2007
smartmoney.com/marketmap
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Cone trees: 3D interactive animations
Robertson, G. G., Card, S. K., and Mackinlay, J. D., Information visualization using 3D interactive animation,
Communications of the ACM, 36, 4 (1993), 51-71.
Robertson, G. G., Mackinlay, J. D., and Card, S. K., Cone trees: Animated 3D visualizations of hierarchical information,
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Proc. ACM SIGCHI Conference on Human Factors in Computing Systems, ACM Press, New York, (April 1991), 189-194.
Hyperbolic trees: focus & context
Lamping, J. and Rao, R., Laying out and visualizing large trees using a hyper-bolic space, Proc. 7th Annual ACM
symposium on User Interface Software and Technology, ACM Press, New York (1994), 13-14.
Lamping, J., Rao, R., and Pirolli, P., A focus+context technique based on hy-perbolic geometry for visualizing large
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hierarchies, Proc. SIGCHI Conference on Human Factors in Computing Systems, ACM Press, New York (1995), 401-408.
TM=Treemaps
CT=Cone Trees
HT=Hyperbolic Trees
Patents
Academic
Papers
Trade Press
Articles
Case study: tree visualization impact
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TM=Treemaps
CT=Cone Trees
HT=Hyperbolic Trees
Patents
Academic
Papers
Case study: tree visualization citations
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Case study: business intelligence
Proquest News 2000-2009
Co-occurrence of concepts
with organizations
Data Mining
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Year
National Security Agency
White House
FBI
AT&T
American Civil Liberties Union
Electronic Frontier Foundation
Dept. of Homeland Security
CIA
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Business
Intelligence
2000-2009
Matrix
showing CoOccurrence
of concepts
and entities
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Business
Intelligence
2000-2009:
(subset)
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Business
Intelligence
2000-2009:
Data mining
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NSA
CIA
FBI
White House
Pentagon
DOD
DHS
AT&T
ACLU
EFF
Senate Judiciar
Committee
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Business
Intelligence
2000-2009:
Tech1
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Google
Yahoo
Stanford
Apple
Tech2
• IBM, Cognos
• Microsoft
• Oracle
Finance
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NASDAQ
NYSE
SEC
NCR
MicroStrategy
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Business
Intelligence
2000-2009:
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Air Force
Army
Navy
GSA
UMD*
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STICK Process
• Identify concepts
• Query data sources
• Processing
• Automatic entity recognition
• Crowd-sourced verification
• Co-occurrence networks
• News
• Dissertation
• Academic
• Patent
• Visualizing & analyzing
• Overall statistics
• Co-occurrence networks
• Network evolution
• Blogs
• Sharing results
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4. Sharing results
• Easily usable metadata (BibTeX, EndNote, etc.)
• Collaborative authoring
• Online communities
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Collaborative literature reviews
• Organized references
• Annotated PDFs
www.mendeley.com
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Shared data & analysis repositories
stick.ischool.umd.edu/community
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Researchers want to…
1.
2.
3.
4.
Find a specific paper
Explore a research area
Do retrospective analysis
Share their results
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What Researchers Want
Cody Dunne
Links from this talk:
Dept. of Computer Science and
Human-Computer Interaction Lab,
University of Maryland
[email protected]
bit.ly/stmwant
This work has been partially supported by
NSF grants IIS 0705832 (ASE) and
SBE 0915645 (STICK)
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