Introduction to Processing

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Introduction to Processing
By Lan Tian
@ 17/10/2013

Published in: Business, Technology
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Introduction to Processing

  1. 1. INTRODUCTION TO PROCESSING A data visualization tool BY: Tian LAN The University of Hong Kong 2013-10-10
  2. 2. OUTLINE • WHY • WHAT • HOW • CONCLUSION.
  3. 3. Why Processing?
  4. 4. Why processing? • Data-driven research • Visualizing -> Data mining; • Sensible City Lab @ MIT (Personally). • Case: Live Singapore! • Real time data: Phone calls and text message activities; bus transit data; taxi trajectories; weather condition; airlines and shipment flows. • Put city and people under lens of data
  5. 5. Video demo
  6. 6. What is Processing?
  7. 7. Three perspectives of Processing • A language view • An IDE view • A community view
  8. 8. Three perspectives of Processing • A language view • O-O, Java “family”. • Data type: primitive, composite • Input: mouse and keyboard events, file. • tablets and devices (Leap Motion, Kinect…) • Graphics and renders: 2D/3D, shape, shaders, camera, light… • Math • … • Reference
  9. 9. Three perspectives of Processing • A language view (backbone of a sketch) • void setup() { • size(400, 400); stroke(255); • • Initializing work: canvas size, render mode, parsing… } • • • • void draw() { line(150, 25, mouseX, mouseY); } Loop work: updating, animation, … • • • • void mousePressed() { background(192, 64, 0); } User input: mouse event, …
  10. 10. Three perspectives of Processing • An IDE view • Plug into Eclipse
  11. 11. Three perspectives of Processing • A community view (Reference)
  12. 12. Three perspectives of Processing • A community view (None of our business?) • Unfolding map library • Geo-visualization; • More user interaction: multi-touch gestures; • Multi-map providers, tile-based map. • For Processing 1.5 only. • Shape file; GeoJASON file.
  13. 13. Three perspectives of Processing • A community view (None of our business?) • Unfolding map + TileMill
  14. 14. How to use Processing? “Hello world”
  15. 15. Other selected solutions of visualizing data
  16. 16. A little bit thought Technology or Art?
  17. 17. Image courtesy of Data Visualization Laboratory
  18. 18. Data sources • NASA data center • MARSA: Geolife • HK Government: data.one • Data Tang (数据堂) • Stanford Network Dataset Collection • Social media (Twitter API, micro blog API, …)
  19. 19. Liqui Data Video demo
  20. 20. Recommended online resources: • http://datavlab.org (Not accessible on Oct. 16) • http://www.civn.cn (Currently not available; server down) • Onformative studio • http://www.visualisingdata.com/index.php/resources/ • 视物致知

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