Welcome to the Jungle - Oz-IA 2010 - Matt Moore

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  • 1. WELCOME TO THE JUNGLE Matt Moore
  • 2. Use Your Illusion I: Information Ecologies
  • 3. http://www.flickr.com/photos/benchilada/2467379649/
  • 4. Information Ecology
  • 5. Information Ecology ● Information Strategy ● Information Politics ● Federal, Feudal, Monarchy, Anarchy ● Information Behaviour ● Information Staff ● Information Processes ● Information Architecture
  • 6. Your New Usability Lab
  • 7. http://www.flickr.com/photos/scottdavie s/3067194897
  • 8. Usability
  • 9. Usability Sociability
  • 10. http://commons.wikimedia.org/wiki/File:Terrac otta_tragic_actor_Louvre_CA1784.jpg
  • 11. Information Architects vs Online Community Managers
  • 12. If our applications are social and changeable then where is the “action”? http://www.flickr.com/photos/jeffwerner/5 37297103/ http://www.flickr.com/photos/grahamb/25 71040783/
  • 13. Cynefin
  • 14. “How do I settle the long-standing dispute between Web site designers and data/information modelers, where Web site designers declare that IA is their purview and is defined as the structure of our organization’s Web site as opposed to what IA really is, which is the structure of information across the enterprise? IA has been hijacked by the Web weenies.” (Enterprise architect, financial services firm) Forrester Topic Overview: Information Architecture (21 Jan 2010)
  • 15. How is your work getting more social (or not)? In what ways do you think our methods need to change (or not)?
  • 16. Use Your Illusion II: Taxonomies & Cyborg Metadata
  • 17. Why does taxonomy matter?
  • 18. • 000 – Computer science, information & general works • 100 – Philosophy and psychology • 200 – Religion • 300 – Social sciences • 500 – Science • 600 – Technology • 700 – Arts and recreation • 800 – Literature • 900 – History, geography, and biography
  • 19. • 000 – Computer science, information & general works • 100 – Philosophy and psychology • 200 – Religion • 300 – Social sciences • 500 – Science • 600 – Technology • 700 – Arts and recreation • 800 – Literature • 900 – History, geography, and biography – 930 History of ancient world – 940 General history of Europe – 950 General history of Asia; Far East – 960 General history of Africa – 970 General history of North America – 980 General history of South America – 990 General history of other areas
  • 20. • 000 – Computer science, information & general works • 100 – Philosophy and psychology • 200 – Religion • 300 – Social sciences • 500 – Science • 600 – Technology • 700 – Arts and recreation • 800 – Literature • 900 – History, geography, and biography – 930 History of ancient world – 940 General history of Europe – 950 General history of Asia; Far East – 960 General history of Africa – 970 General history of North America – 980 General history of South America – 990 General history of other areas • 993 General history of other areas; New Zealand • 994 General history of other areas; Australia • 995 General history of other areas; Melanesia; New Guinea • 996 General history of other areas; Other parts of Pacific Polynesia • 997 General history of other areas; Atlantic Ocean islands • 998 General history of other areas; Arctic islands & Antarctica • 999 Extraterrestrial worlds
  • 21. Experts http://www.flickr.com/photos/raster/3380860520/
  • 22. Experts Machines http://www.flickr.com/photos/raster/3380860520/ http://www.flickr.com/photos/brewbooks/3315685906/
  • 23. Experts Machines Users http://www.flickr.com/photos/raster/3380860520/ http://www.flickr.com/photos/brewbooks/3315685906/ http://www.flickr.com/photos/ntr23/730371240/
  • 24. Advantages Disadvantages Experts High-quality & consistent Expensive outputs Time-consuming Can handle ambiguity May not understand user perspective Machines Scalable Poor at ambiguity Quick Costs may vary Users Cheap Rarely consistent Scalable (ish) Often Uninterested
  • 25. http://www.powerhousemuseum.com/dmsblog/index. php/2008/03/31/opac20-opencalais-meets-our- museum-collection-auto-tagging-and-semantic- parsing-of-collection-data/
  • 26. TaxoFolk Source: Eric Tsui, Hong Kong Polytechnic University
  • 27. 1. Building • Buy off the shelf externally (…and tweak it a bit) • Machine analysis • Existing organisational vocabularies & data models • Input from users (workshops, tagging) This will be an ongoing process.
  • 28. 2. Applying • Auto-categorisation • User-based tagging (either free or based on taxonomy) • Expert tagging and/or editing in workflow It all depends on scale & risk.
  • 29. 3. Consuming • Users like pictures (maps, trees, tags clouds) • Linked to other apps (e.g. Search) or via workflow Taxonomies should not be run for experts!
  • 30. Building Applying Consuming Buy off the shelf Manual Tagging - Experts OR against Taxonomy Build based on analysis Machines Semantic and/or Automated Ontology-based Concept Analysis Categorisation Processes Users Tagging & Manual Tagging Tag Clouds & Folksonomies (whatever) Visualisation Search
  • 31. How are taxonomies important to our work? What is the optimal balance of experts, machines and users for our situation?
  • 32. Some Links ● Me: http://innotecture.com.au/ ● Survey: http://www.surveymonkey.com/s/oztaxom ● Workshop: http://innotecture.com.au/taxonomy/ ● Ambient Collaboration Cafe: http://nswkmoct10.eventbrite.com/