Structured data EuroIA IV

1. Structured Data: None / Some / All EuroIA VI, Paris, September 2010

2. EuroIA Paris | September 2010 | 2 1995-2010 = Gazillions of Websites Our design problem was an evolution of visual literacy —Readers were trained to find information in printed books/magazines/newspapers —Digital publications lack physical context —Location and scope of information was invisible

3. EuroIA Paris | September 2010 | 3 Clients = Publishers Users = Readers Our Design Task was to connect Readers to content —Adapt graphic language – type, color, image – from the page to the screen —Create navigation systems that help users understand what they can find on a website —Communicate the structure of content in flexible repeatable units

4. 2010=Massive Undifferentiated Data

5. EuroIA Paris | September 2010 | 5

9. EuroIA Paris | September 2010 | 9 2010 Users are —Convinced they can find what they want “on the Internet” —Producing & managing dematerialized content: photos, videos, music, email, compound documents —Creators & consumers with storage/creation and retrieval/consumption needs —Looking for something all the time

10. EuroIA Paris | September 2010 | 10 2010 Users want to —Record, share, publish —Be convinced, amused, in control —Find, sort, sift and copy —Mix, reorder and arrange Users now have the experience of solving problems by manipulating metadata even though they don’t know what metadata is

11. EuroIA Paris | September 2010 | 11 Today’s IA/UX Problem Every IA/UX problem is a Data Continuum —No Structure Vacuum Raw —Some Structure Marsh Eatable —Complete Structure Field Cooked

12. EuroIA Paris | September 2010 | 12 Unstructured Data Data Vacuum: no metadata has been added to items Even Data Vacuums include content & context The 50-year-old Information Retrieval / Library Science trade-off: —Precision: finding only what you are looking for —Recall: finding everything that might contain what you are looking for

13. EuroIA Paris | September 2010 | 13 Data with no structure: Names —A character-string a person, place or thing is known by —People have many names: professional names, familiar names, legal names —Places and things have many names in different languages —As data, a name presents a major problem: IT IS NOT UNIQUE —For example: “paul kahn”

14. EuroIA Paris | September 2010 | 14 “paul kahn” string exist in many places —About 299,000 results in Google —25 different people in LinkedIn —100+ different people in Facebook —378 photos on Flickr (where the tag “paulkahn” is used for two different people)

15. EuroIA Paris | September 2010 | 15 There are many “paul kahn”s Paul W. Kahn, Dr. Paul Kahn, Paul Kahn, Roshi Paul Paul Kahn author and Law Urologist in writer, editor, Genki Kahn chef, The Professor at Plantation FL psychological Spiritual Publican, Yale University, counselor and Director of Zen Chicago IL New Haven CT disability rights Garland in advocate in Wyckoff, NJ Newton MA

16. EuroIA Paris | September 2010 | 16 Semi-structured Workarounds Add additional strings for context [screen grab of sample completion for paul kahn in Google toolbar or Google search]

17. EuroIA Paris | September 2010 | 17 Where did I put that document? The tools we use: —Personal Memory —Folder names —Desktop search What kinds of structure can we present?

18. Implicit metadata: —Document type —File name —Time/Date stamp

19. EuroIA Paris | September 2010 | 20 LATCH (+): Five ways to organize information for understanding and ease of use Location Alphabet Richard Saul Wurman Time INFORMATION ANXIETY 2 Category Hierarchy + Common Focus

20. EuroIA Paris | September 2010 | 21 Semi-Structured Data Data Marsh: some metadata without predefined language or requirements —Tagging : ad hoc uncontrolled keywords —Time / Location stamps: where and when —Each metadata dimension is flat (no hierarchy) and independent —Many kinds of relationships can be inferred

21. EuroIA Paris | September 2010 | 22 Aggregation/Reproduction Sites —Sites that aggregate user-provided content Slideshare / YouTube / Dailymotion / Vimeo / SoundCloud / Flickr —Sites where users can create and republish content to social networks LinkedIn / Facebook / Twitter

24. EuroIA Paris | September 2010 | 26 Structured Data Data Fields: where metadata has been explicitly added to items according to an agreed-upon standard —The Content is made to fit a pre-defined structure —The required parts of the structure are completed —Each metadata dimension qualifies and reinforces the meaning of the content —Many kinds of relationships can be harvested

25. EuroIA Paris | September 2010 | 29 Map of the Market

26. EuroIA Paris | September 2010 | 30 Newsmap.jp

27. EuroIA Paris | September 2010 | 31 NY Times Immigration Explorer

28. EuroIA Paris | September 2010 | 32 NPR Patchwork Nation

29. DC Homicide Map — http://dc.everyblock.com/crime/by-offense/homicide/by-date/2010-01- 01,2010-05-31/#tallermap

30. EuroIA Paris | September 2010 | 34 USHMM Propaganda Timeline

31. EuroIA Paris | September 2010 | 38 Microsoft Live Labs Pivot

32. EuroIA Paris | September 2010 | 40 Would the world be a better place if —Everything had a unique ID? —Every digital object with a unique ID contained structured data? How does structured data affects quality of life questions?

33. EuroIA Paris | September 2010 | 41 A Proverb for User Centered Design —Hwa is thet mei thet hors wettrien the him self nule drinken [who can give water to the horse that will not drink of its own accord?] (Old English Homilies, circa 1175) —You can lead a horse to water but you can’t make it drink

34. EuroIA Paris | September 2010 | 42 Structured Data Value Proposition —2010 Users know what they want —Almost no one wants to create Structured Data —Our clients and their audience increasingly understand how to use Structured Data —The Structured Data Value Proposition is the key to our profession