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Big Data & Graphs in Rome
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Big Data & Graphs in Rome


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How to visualize your connected big data with graph visualization technology, KeyLines.

How to visualize your connected big data with graph visualization technology, KeyLines.

Published in: Technology

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  • Use either patents and dcm demos
  • Use filters and twitter demo
  • Use combos2 demo
  • Use advanced app demo
  • Transcript

    • 1. KeyLines: Interact with your graph Marco Liberati
    • 2. Why data visualization? • The user is sitting on the data • Wants to make meaningful decisions • A single number is not enough for that
    • 3. Data is invisible To be seen, data must be VISUALLY ENCODED Can I just look at the data?
    • 4. Quantitative Ordinal Nominal More Accurate Less Accurate Quantitative Ordinal Nominal Position Position Position Length Density Hue Angle Saturation Density Slope Hue Saturation Area Length Shape Density Angle Length Saturation Slope Angle Hue Area Slope Shape Shape Area Visual encoding by data type
    • 5. Why graph visualization then? Graphs can give better answers to these kind of question: •What depends on what? •What’s the flow? •Where are bottlenecks/risks? •What’s the impact of this?
    • 6. There are several design options for graph visualisation
    • 7. Use a matrix
    • 8. Edge bundling
    • 9. Hive plots
    • 10. Classic node-link
    • 11. I want to visualize a larger network
    • 12. Deal with big networks is not easy.
    • 13. Here some tips to improve the experience: •Use colors •Use filters •Aggregate nodes and links •Info on demand •Expand on demand
    • 14. Use colors
    • 15. Use filters
    • 16. Aggregate nodes and links
    • 17. Info on demand
    • 18. Expand on demand
    • 19. Reference Architecture
    • 20. Graph Database Reference Architecture Search Index User Authentication (eg Active Directory) Chart Store
    • 21. Visualise and analyse networks in the browser •Communication networks •Social networks •Fraud networks Features •Pure HTML5 •Works on IE6, 7, 8 via Flash •Graph layouts •Graph analytics – SNA measures, path finding & more •Full event model •Full workflow support – Image generation for reports, undo stack, etc • Very quick integration time • Thorough documentation • Good performance • Great support
    • 22. Cambridge Intelligence Start-up, founded May 2011 We make network visualisation tools
    • 23. Combined 40+ years developing and designing visual tools for law enforcement and national security Joe Kaush MarcoAndrew Corey PhilNate Ex- Cambridge Intelligence
    • 24. Thanks! @key_lines @CambridgeIntel All demos made with: All logos, trademarks, service marks and copyrights used in this presentation belong to their