OPENVIS Conference Quick Report Part 2

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Quick report of OpenVis Conference 2014 in Boston. This is the second half of my report. Prepared for Cytoscape developer team meeting on 5/15/2014.

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OPENVIS Conference Quick Report Part 2

  1. 1. Cytoscape Team Meeting 5/15/2014 ! Keiichiro Ono Part 2: Quick Report Part 2
  2. 2. Outline -Keynote 2: John Resig -Selected Talks -Mostly Technical Ones
  3. 3. Keynotes
  4. 4. Keynotes Mike Bostock - NTY Visualization Team John Resig - Khan Academy, Ex-Mozilla
  5. 5. John Resig
  6. 6. John Resig - Creator of jQuery - Engineer at Khan Academy - Was a member of Mozilla Corporation - a JavaScript hacker
  7. 7. http://ejohn.org/
  8. 8. - Lightweight JavaScript library - Reduces many lines of code - Used in more than 50% of the web sites today - Solves lots of cross-browser issues
  9. 9. Keynote by John Resig: ! Analyzing Art Data for Fun and Profit
  10. 10. ukiyo-e.org 飾北斎 富嶽三十六景 神奈川沖浪裏
  11. 11. What is Ukiyo-e? - Japanese woodblock prints (mostly) produced in Edo period (江戸時代) - Means “Pictures of the floating world” - Kabuki actors, 美人画 (pictures of beautiful women), landscapes, etc. - One of the most popular Japanese art forms in the world - In Japan, it was a popular culture in17-18 centuries, and re-discovered as art by Europeans
  12. 12. (Post) Impressionism and Japonisme Madame Monet in a Japanese kimono. Claude Monet. ! 1875, Museum of Fine Arts, Boston La courtisane (after Eisen), Vincent van Gogh, 1887
  13. 13. Sudden Shower Over Shin-Ohashi Bridge and Atake (名所江戸百景 大はしあたけの夕立) by Hiroshige (歌川広重)
  14. 14. Bridge in the rain (after Hiroshige) by Vincent van Gogh
  15. 15. Meta-database of Ukiyo-e for Fun - He is a big fan of Japanese art - One day, he noticed there is no central repository of ukiyo-e - Then, let’s make one as a fun project…
  16. 16. Source Web Site WebKit PhantomJS CasperJS SpookyJS XML Files MongoDB Log libxml & xpath MongoDB Data Processing Script Artists Data Image Data Consolidate Date and Artist Data Add to the site Pipeline Built on node.js
  17. 17. Source Web Site WebKit PhantomJS CasperJS SpookyJS Crawling Pipeline
  18. 18. CasperJS SpookyJS XML Files MongoDB Log libxml & xpath MongoDB Data Processing Script
  19. 19. MongoDB Data Processing Script Artists Data Image Data Consolidate Date and Artist Data Add to the site
  20. 20. Many-to-Many Mapping - Metadata for the pictures were “fuzzy” - Example: Metadata for an artist 「歌川広重」 - 広重 - 歌川広重 - hiroshige - Hiroshige utagawa - ひろしげ - Representation of Japanese names - Ando, 安藤, 安東, あんどう, 安堂, etc. - ex: Keiichiro, Keiichiroh, けいいちろう, 圭一朗, 圭一郎
  21. 21. 東洲斎写楽.json { "original": "Sharaku Tōshūsai (東洲斎写楽)", "locale": "ja", "kanji": "東洲斎写楽", "given": "Sharaku", "given_kana": "しゃらく", "surname": "Tōshūsai", "surname_kana": "とおしゅうさい", "surname_kanji": "東洲斎", "given_kanji": "写楽", "name": "Tōshūsai Sharaku", "ascii": "Tooshuusai Sharaku", "plain": "Toshusai Sharaku", "kana": "とおしゅうさいしゃらく" }
  22. 22. Collaboration with Frick Collection - While he was building this DB, he found a lot of errors in the museums’ databases - Image similarity search - He contacted them and curators are impressed by his work - Collaboration: Image/graph analysis of Frick Collection and metadata update - Graph analysis with Neo4j / Cypher
  23. 23. Summary - Today, we can build this level of complex data analysis pipeline only with JavaScript - Node.js as a workflow engine - Write Code Every Day - http://ejohn.org/blog/write-code-every-day/
  24. 24. Selected Talks
  25. 25. Using D3 with Backbone, Angular and Ember - Sam Selikoff Lyra: An Interactive Visualization Design Environment - Arvind Satyanarayan Python in the Browser Age: Data Exploration in the IPython Notebook - Jake Vanderplas Selected Talks
  26. 26. Using D3 with Backbone, Angular and Ember Sam Selikoff
  27. 27. Post-jQuery World - Large-scale JavaScript client-side code without structure = unmaintainable - There are lots of frameworks to solve this issue
  28. 28. D3.js + MV* Frameworks - D3.js visualization code tend to be procedural - For large scale development, encapsulate it - Then embed the code by following the framework’s idioms
  29. 29. https://github.com/samselikoff/talks/blob/master/4-apr2014-using-d3-backbone-angular-ember/final/6_angular_d3.html
  30. 30. Structure to DataViz Applications - Try existing framework - d3.Chart - Make your visualization code reusable! - http://bost.ocks.org/mike/chart/
  31. 31. Lyra: An Interactive Visualization Design Environment Arvind Satyanaraya
  32. 32. What is Lyra? - Node.js based tool to create custom visualization without coding - “Lyra is an interactive environment that enables custom visualization design without writing any code.“ - Targeting somewhere between D3.js and Excel - Pre-alpha status
  33. 33. Napoleon's March to Moscow by Charles Minard, 1869
  34. 34. Custom Visualizations without Coding - It is interesting, but challenging - Complex UI - Learning curve - But worth trying to satisfy demands of complex visualizations
  35. 35. Python in the Browser Age: Data Exploration in the IPython Notebook Jake Vanderplas
  36. 36. - Most of the core commuters are scientists - Tool for scientists by scientists - Goal: Reproducible Science IPython and Notebook
  37. 37. http://www.brianckeegan.com/2014/04/the-need-for-openness-in-data-journalism/
  38. 38. http://nbviewer.ipython.org/github/brianckeegan/Bechdel/blob/master/Bechdel_test.ipynb Reproducible Data Journalism
  39. 39. New in IPython Notebook 2.0: Interactive Widget
  40. 40. http://mpld3.github.io/
  41. 41. Bokeh
  42. 42. Tips: New Presentation Style with IPython Notebook - Write demo code and descriptions as an IPython Notebook - Upload it to gist - Open it with nbviewer - http://nbviewer.ipython.org/ - Also, the audience can directly clone the repository and play with their local machine
  43. 43. Summary
  44. 44. Summary - Tons of interesting new projects are going on outside of Java world - Some of the tools are extremely important for us - IPython Notebook - D3.js - We need to keep watching them…
  45. 45. 2014 Keiichiro Ono kono@ucsd.edu

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