Structured data mp may 2012
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The document discusses how users interact with structured, semi-structured, and unstructured data on the internet and discusses design challenges around organizing information for understanding and ease of use as data becomes more structured with unique identifiers and metadata. It also notes that while structured data enables new capabilities, usability is still important to consider for users who just want to find information without learning complex systems.
Structured data mp may 2012
- 1. Structured Data: None / Some / All Mad*Pow User Experience, May 2012
- 2. Mad*Pow | May 2012 | 2 1995-2012 = 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. Mad*Pow | May 2012 | 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. 2012=Massive Pattern of Nodes
- 5. 2012=Nodes with Geo Context
- 6. Mad*Pow | May 2012 | 6 Today 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
- 7. Mad*Pow | May 2012 | 7 Today Users want to — Record, share, publish — Be convinced, amused, in control — Find, sort, sift and copy — Mix, reorder and arrange They don’t explicitly know what metadata is They are solving problems by implicitly manipulating metadata
- 8. Mad*Pow | May 2012 | 8 Today’s IA/UX Problem Every IA/UX problem is a Metadata Continuum — No Structure Vacuum Raw — Some Structure Marsh Eatable — Complete Structure Field Cooked
- 9. Mad*Pow | May 2012 | 9 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: not missing anything that might contain what you are looking for
- 10. Mad*Pow | May 2012 | 10 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”
- 11. Mad*Pow | May 2012 | 11 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 serving in Iraq Professor at Yale Plantation FL psychological Spiritual University, counselor and Director of Zen New Haven CT disability rights Garland in advocate in Wyckoff, NJ Newton MA
- 12. Mad*Pow | May 2012 | 12 What are most people searching for?
- 13. Mad*Pow | May 2012 | 13 Who is searching?
- 14. Mad*Pow | May 2012 | 14 Use algorithms to surface what users might want to see (and what we want them to see)
- 15. Mad*Pow | May 2012 | 15 Where did I put that document? The tools we use: — Personal Memory — Folder names — Desktop search What kinds of structure can we present?
- 16. Implicit metadata: — Document type — File name — Document content
- 17. Mad*Pow | May 2012 | 17 LATCH (+): Organize information for understanding & ease of use Location Alphabet Richard Saul Wurman Time INFORMATION ANXIETY 2 Category Hierarchy + Common Focus
- 18. Mad*Pow | May 2012 | 18 Semi-Structured Data Data Marsh: some metadata without predefined language or requirements — Tagging : users add uncontrolled keywords — Profile: users intentionally add metadata about themselves — Time / Location stamps: where and when — Tracking: users unintentionally add metadata about themselves as interactions are tracked
- 19. Mad*Pow | May 2012 | 19 Aggregation/Reproduction Sites — Sites that aggregate user-provided content Slideshare / YouTube / Dailymotion / Vimeo / SoundCloud / Flickr — Sites where users create and republish content to social networks LinkedIn / Facebook / Twitter
- 20. Mad*Pow | May 2012 | 20 — Search — Feature — Categories + Time — Common Focus
- 21. Mad*Pow | May 2012 | 21 Implicit metadata: — Sort criteria — Time/Date stamp — Document type (2010 version)
- 22. Mad*Pow | May 2012 | 22
- 23. Mad*Pow | May 2012 | 23
- 24. Mad*Pow | May 2012 | 24 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. Mad*Pow | May 2012 | 25
- 27. Mad*Pow | May 2012 | 27
- 28. Mad*Pow | May 2012 | 28 Map of the Market
- 30. Mad*Pow | May 2012 | 30 NY Times Immigration Explorer
- 31. Mad*Pow | May 2012 | 31 Structured data ≠ Usable data
- 32. Mad*Pow | May 2012 | 32
- 33. Mad*Pow | May 2012 | 33 Open Paths data from my iPhone
- 34. Mad*Pow | May 2012 | 34 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?
- 35. Mad*Pow | May 2012 | 35 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
- 36. Mad*Pow | May 2012 | 36 Structured Data Value Proposition — People want to find things, they don’t want to “learn” how to find things — People understand how to use Structured Data — No one wants to create Structured Data — It is our task to leverage the Structured Data people already understand