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MDST 3703 F10 Seminar 8
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MDST 3703 F10 Seminar 8

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  • 1. Seminar 8 Shirky, Wesch and Web 2.0 Introduction to the Digital Liberal Arts MDST 3703 / 7703 Fall 2010
  • 2. Business • Mid-terms next Thursday • For those who missed Thursday—see Final Projects
  • 3. Review • Digital scholarship as the work of representing worlds – Expressed by categories – Encoding in symbols – Cultured in communities • Thematic research collections use various devices to produce this representation – Hypertext (intertextuality) – Contextual mass
  • 4. Overview • The horse = the Library – or the book or the shelf – any artifact of this assemblage • The faster horse = Yahoo, VOS, etc. • Unsworth and Shirky represent two approaches to building cars – (old) Ontology vs. (new) Tagging – Humanities Computing vs. New Media • Can we combine Unsworth and Shirky?
  • 5. The tree of nature and logic From Ramon Lull Ars Magna (Great Art), 1305 * Trunk = Aristotle's categories * 10 leaves on the right = questions * 10 leaves on the left = keyed to a system of rotating disks for generating answers. Inspired Leibniz, creator of symbolic logic, and early ancestor of the computer Ontology is the basis of computing
  • 6. What does Unsworth mean by “foolish consistency”?
  • 7. Representing "Innocence"
  • 8. The Rationalization Effect(s): 1. Uncovering tacit categories and worlds 2. A new look at old data
  • 9. “I found myself right back at questions of interpretation and the articulation of an unspoken lifeworld” From Unsworth, 2001, Figure 2, ‘Debugging the Spec’
  • 10. https://dev1.shanti.virginia.edu/fellows/baird/graphs/ https://dev1.shanti.virginia.edu/fellows/baird/
  • 11. The process that one goes through to develop, apply, and compute knowledge representations is unlike anything that humanities scholars have ever been required to do And it’s what we should be doing
  • 12. Shirky’s thesis The ways we're attempting to apply categorization to the electronic world are actually a bad fit  Faster horses!
  • 13. Yet Another Hierarchically Organized Ontology
  • 14. If you've got enough links, you don't need the hierarchy anymore
  • 15. The Method: Tags and URLs • The targets of links have addresses – <a href=“http://somewhere.net”>Click me</a> – Addresses are URLs • Tags can be used to classify these addresses – Delicious – Diigo • Anything can have an address and be tagged – Images in Flickr – Things in the world
  • 16. Examples • Delicious (web pages and tags) • Flickr (images and tags) • Twitter (tweets and hashtags, retweets)
  • 17. Effects • Cool visualizations • Sometimes useful mashups • Scary but interesting Giant Global Graph
  • 18. A visualization of messages referencing the #Aristotle hashtag on Twitter, created by Social Collider. The red lines in the center are the #Aristotle references. http://complexrhetoric.blogspot.com/2009/03/is-aristotle-on-twitter-panel-wrap-up.html
  • 19. “we could mine the tweets surrounding an archived hashtag in order to generate a topic based context that would persist after the event had been long gone” http://blog.ouseful.info/2010/09/09/additional-thoughts-on-tag-powered-context/ -- Scrape tweeting links using the hashtag from the twapperkeeper archive and feed them to a facet of the search engine -- Look to other services, such as delicious, to see who has been bookmarking URLs with the particular tag -- Look to delicious to see who bookmarked the ALTC2010 homepage SEE http://ohttp://ouseful.open.ac.uk/jit/examples/hypertree- demo2.php?mode=tag&url=http://www.alt.ac.uk/altc2010/useful.open. ac.uk/jit/examples/hypertree-demo2.php?mode=tag Tag Powered Context
  • 20. 35,000,000 Flickr Photos, Mapped What happens when images are tagged by location
  • 21. When ontology doesn’t work • Domain – Large corpus – No formal categories – Unstable entities – Unrestricted entities – No clear edges • Participants – Uncoordinated users – Amateur users – Naive catalogers – No Authority
  • 22. Question • Are Unsworth’s and Shirky’s positions compatible? – What are their major differences? – Both approaches want to generate data and produce visualizations … – Both approaches expose classifications that are surprising and interesting
  • 23. Wesch • Why is it important to separate form and content? – Note that ontology is useful here (document markup in RSS)
  • 24. Wesch • How do XML and RSS relate to Shirky’s and Unsworth’s positions? • How is Wesch’s argument similar to Shirky’s? Unsworths? • How is it different from both Unsworth and Shirky?
  • 25. Some concluding observations … • Unsworth pays attention to the consequences of limitations • Shirky and Wesch are as much observers of the Web as users • Wesch exploits a different medium – video • How shall we organize our own collections and tags?