graph visualization options and latest developments
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Graph Visualizationoptions and latest developments
By @Linkurious - [email protected]
London Neo4j meetup at Skills Matter, Feb 27, 2013
Linkurious startup: a few words about us• Jean Villedieu, CMO Linkurious• Sébastien Heymann, CEO Linkurious• Romain Yon, CTO Linkurious (is coding tonight)
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Example of graph
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Graphs are in our DNA• Gephi, the leading graph analysis and exploration solution• Democratizing network thinking• Linkurious
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The best way to store and access the data of a connected world
• Graphs are “everywhere”: conceptual view on data• Neo4j and graph databases offer a fast and intuitive way to use data• Social networks, recommendation engines, networked systems…
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Visualization is key to understanding graphs• Verify data• Check algorithm• View information in context• Build a visual representation• Understand relationships• Discover information• Find patterns• Illustrate and communicate data
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Global approach vs Centred approachCard, Shneiderman (Using Vision to Think, 1999)
1. Overview first,2. Zoom and filter,3. Details-on-demand.
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Van Ham, Perer (2009)
1. Search, 2. Show Context, 3. Expand on Demand.
Play now: which tool for which approach?
Cytoscape, D3.js, Gephi, GraphViz, KeyLines, Linkurious, MentionMap,
Neo4j server web interface, Neoclipse, NodeXL, Palantir,
Sigma.js, SocialAction, Wikisway, WikiWeb...
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WikiWeb
D3.js
Toolkits
Summary: which tool for which approach?Cytoscape, GraphViz,
Gephi, GraphInsight, GUESS,NodeXL, SocialAction, Tulip,
UCINET
Global approach
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Linkurious, MentionMap, Neo4j server web interface,
Neoclipse, Wikisway, WikiWeb
Centred approach
+ Toolkits to build your own App: D3.js, KeyLines, Sigma.js
Global approach vs Centred approachGreat for:
Identifying communities and global properties
Finding correlations properties / structure
Communicating « wow » effect
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Great for:
Investigating entities
Exploring local context
Communicating insights
Global approach vs Centred approachIssues:
Difficult to learn (data mining + CS + design skills)
Poor insights with large graphs
Highly sensitive to graph incompleteness (<5% missing data => important bias)
Hardware limits (goodbye mobile!)
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Issues:
Users must know what to search
Poor statistical insights (bias due to hidden information)
Orientation is difficult
Global approach vs Centred approachUse it for:
Analysis at the global scale.
Make hypotheses or try to confirm statistical properties.
Graphs of size < 50k nodes.
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Use it for:
Database browsing to quickly find information.
Analysis of local views.
Graphs of any size.
3 applications of the centred approach
Use case 1: fraud detectionAutomatic outlier detection over time (Seb's Ph.D.)
Visualization of outlier-centred graphs
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Use case 2: visual recommendationYasiv.com
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Use case 3: (telco) impact analysisNetwork: millions of routers and machinesLocal impact of a router failure in network services?
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Entypo pictograms by Daniel Bruce — www.entypo.com
Linkurious: visualize graph data easily• A tool to visualize any graph database• Graph search made easy• Approach : search, show context, expand on demand
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Linkurious competitorsLocked to a specific use case:MentionMap => Twitter mentionsPalantir => for Palantir customers onlyTheAdvisor => scientific papers recommendationWikiways => TechCrunch DatabaseWikiweb => Wikipedia browsing
Limited browsing features:Neoclipse, Neo4j web admin
Toolkits (require to code): D3.js, KeyLines, Sigma.js
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Live demo
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