Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Mdst3703 visualization-2012-10-23


Published on

  • Be the first to comment

Mdst3703 visualization-2012-10-23

  1. 1. Visualization and the New Epistemology Prof. Alvarado MDST 3703/7703 23 October 2012
  2. 2. Business• Midterms graded• Office hours – Tomorrow 11:00AM—3:00PM – Friday 1:00PM—3:00PM• Project homework – Mark-up text for paragraphs and quotes – Quotes are SPAN elements with CLASS attributes of either ‘quote’ or ‘extract’ – Make sure file and directories are named properly
  3. 3. Review• Web 2.0 – Post-Google era of the web – Massive participation in social media – Social production of knowledge – New models of how knowledge is produced, maintained, organized• Tags – One example of this shift – A new kind of knowledge “product”
  4. 4. A “folksonomy” visualized
  5. 5. A Flickr “folksonomy” visualized
  6. 6. Eric Fischer creates maps that merge geographic locations with geotagged photos from Flickr and tweets from Twitter. Red dots pinpoint the locations of Flickr pictures, blue dots show tweets, white dots mark places that have been posted to both. This map of Washington, D.C., s hows messages concentrating around the national landmarks and power corridors of the city‟s federal zone.
  7. 7. An algorithm generates a virtual Rome in 3D from150,000 Flickr Users Photos
  8. 8. Flickr Photos Yield Tourist Trails. An algorithmuses images from millions of tourists to suggestways for visitors to spend their time.
  9. 9. Trends Map for #OWS m
  10. 10. These visualizations are created out of “Big Data”
  11. 11. What is Big Data? What are some examples?
  12. 12. What is distinctive about the form of thiskind of knowledge generated by Big Data?
  13. 13. Organic RhizomicSocially generated Transductive
  14. 14. What about the content of this kind of knowledge? What does it tell us about what?
  15. 15. ?
  16. 16. A new epistemology? An new science?(media determinism again)
  17. 17. Franic Bacon in 1620 described anew kind of knowledge based onobservation and induction(empiricism). This view can bepartly traced to the successes ofexploration and instruments inlearning about the world.
  18. 18. Anderson argues that a similar shift is happening nowWith the era of the “cloud” and massive data the Petabyte Age comes a new kind of knowledge
  19. 19. The database is not just a symbolic formIt is the pervasive and standard form in which our knowledge is organized
  20. 20. Anderson• The end of theory – Positivism (see definition) – It’s algorithms all the way down• No need for models and causality – Correlation is enough• More is different – The “Petabyte Age” – The sheer amount of data makes it valuable – Quality does not matter
  21. 21. Some Definitions• Petabyte (PB) = 250 1,125,899,906,842,624 bytes 1,024 terabytes• Positivism (my definition) – A theory of knowledge that views physical laws and models as more or less stable patterns – Regards statistics and pattern recognition as more authentic forms of knowledge than laws – Radically empiricism (nothing “behind” the observed)
  22. 22. The Page Rank algorithm visualizedGoogle does not care about what is on a page, itjust cares about this
  23. 23. Same approach to advertising
  24. 24. “AdWords analyzes every Google search todetermine which advertisers get each of upto 11 „sponsored links‟ on every results page.It‟s the world‟s biggest, fastest auction, anever-ending, automated, self-serviceversion of Tokyo‟s boisterous Tsukiji fishmarket, and it takes place, Variansays, „every time you search.‟ ”Steven Levy, “Secret of Googlenomics: Data-Fueled Recipe BrewsProfitability,” WIRED 17.06.
  25. 25. It’s all about the algorithmThere is no real theory behind the formula It just happens to work
  26. 26. Sometimes this approach is called “the physics of clicks”
  27. 27. Manovich’s experiments explore this concept (examples from Mapping Time Exhibit)
  28. 28. Time Magazine 1923—2009
  29. 29. Science and Popular Science Magazines 1872-1922
  30. 30. Anna KareninaThis visualization of AnnaKarenina is inspired by a commonreading practice of underliningimportant lines and passages in atext using magic markers. Tocreate this visualization wedesigned a program that reads thetext from a file and renders it in aseries of columns running from topto bottom and from left to right asa single image it also checkswhether text lines containparticular words (this versionchecks for the word Anna) andhighlights the found matches.
  31. 31. Manga Style SpaceENTROPY VARIATION
  32. 32. MONDRIAN ROTHKO 13 years of data for each X: Brightness Y: Saturation
  33. 33. ImagePlot of Vertov’s film, The Elevent HourBRIGHTNESSNUM SHAPES
  34. 34. VisualizationAlgorithm Big Data
  35. 35. Visualizing Text
  36. 36. Co-presence of characters in Les Miserables
  37. 37. Same data, different display algorithm