WELCOME TO THE JUNGLE


       Matt Moore
Use Your Illusion I:
Information Ecologies
http://www.flickr.com/photos/benchilada/2467379649/
Information Ecology
Information Ecology
●   Information Strategy
●   Information Politics
    ●   Federal, Feudal, Monarchy, Anarchy
●   Infor...
Your New Usability Lab
http://www.flickr.com/photos/scottdavie
s/3067194897
Usability
Usability
Sociability
http://commons.wikimedia.org/wiki/File:Terrac
otta_tragic_actor_Louvre_CA1784.jpg
Information Architects
             vs
Online Community Managers
If our applications are
social and changeable
then where is the “action”?




                              http://www.fli...
Cynefin
“How do I settle the long-standing dispute between
Web site designers and data/information modelers,
where Web site design...
How is your work getting more
        social (or not)?

 In what ways do you think our
methods need to change (or not)?
Use Your Illusion II:
Taxonomies & Cyborg Metadata
Why does taxonomy matter?
•   000 – Computer science, information & general works
•   100 – Philosophy and psychology
•   200 – Religion
•   300 – S...
•   000 – Computer science, information & general works
•   100 – Philosophy and psychology
•   200 – Religion
•   300 – S...
•   000 – Computer science, information & general works
•   100 – Philosophy and psychology
•   200 – Religion
•   300 – S...
Experts




http://www.flickr.com/photos/raster/3380860520/
Experts



      Machines




http://www.flickr.com/photos/raster/3380860520/
http://www.flickr.com/photos/brewbooks/33156...
Experts



      Machines



           Users

http://www.flickr.com/photos/raster/3380860520/
http://www.flickr.com/photo...
Advantages                 Disadvantages



Experts    High-quality & consistent         Expensive
                   outp...
http://www.powerhousemuseum.com/dmsblog/index.
php/2008/03/31/opac20-opencalais-meets-our-
museum-collection-auto-tagging-...
TaxoFolk




 Source: Eric Tsui, Hong Kong Polytechnic University
1. Building
• Buy off the shelf externally (…and tweak it a
  bit)
• Machine analysis
• Existing organisational vocabulari...
2. Applying
• Auto-categorisation
• User-based tagging (either free or based on
  taxonomy)
• Expert tagging and/or editin...
3. Consuming
• Users like pictures (maps, trees, tags clouds)
• Linked to other apps (e.g. Search) or via
  workflow




T...
Building            Applying         Consuming




           Buy off the shelf    Manual Tagging           -
Experts     ...
How are taxonomies important to
            our work?

  What is the optimal balance of
experts, machines and users for ou...
Some Links
●   Me: http://innotecture.com.au/
●   Survey:
    http://www.surveymonkey.com/s/oztaxom
●   Workshop: http://i...
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Welcome to the Jungle - Oz-IA 2010 - Matt Moore
Upcoming SlideShare
Loading in …5
×

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

949 views

Published on

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
949
On SlideShare
0
From Embeds
0
Number of Embeds
176
Actions
Shares
0
Downloads
5
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

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

  1. 1. WELCOME TO THE JUNGLE Matt Moore
  2. 2. Use Your Illusion I: Information Ecologies
  3. 3. http://www.flickr.com/photos/benchilada/2467379649/
  4. 4. Information Ecology
  5. 5. Information Ecology ● Information Strategy ● Information Politics ● Federal, Feudal, Monarchy, Anarchy ● Information Behaviour ● Information Staff ● Information Processes ● Information Architecture
  6. 6. Your New Usability Lab
  7. 7. http://www.flickr.com/photos/scottdavie s/3067194897
  8. 8. Usability
  9. 9. Usability Sociability
  10. 10. http://commons.wikimedia.org/wiki/File:Terrac otta_tragic_actor_Louvre_CA1784.jpg
  11. 11. Information Architects vs Online Community Managers
  12. 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. 13. Cynefin
  14. 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. 15. How is your work getting more social (or not)? In what ways do you think our methods need to change (or not)?
  16. 16. Use Your Illusion II: Taxonomies & Cyborg Metadata
  17. 17. Why does taxonomy matter?
  18. 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. 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. 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. 21. Experts http://www.flickr.com/photos/raster/3380860520/
  22. 22. Experts Machines http://www.flickr.com/photos/raster/3380860520/ http://www.flickr.com/photos/brewbooks/3315685906/
  23. 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. 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. 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. 26. TaxoFolk Source: Eric Tsui, Hong Kong Polytechnic University
  27. 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. 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. 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. 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. 31. How are taxonomies important to our work? What is the optimal balance of experts, machines and users for our situation?
  32. 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/

×