1. Ontology is Overrated
Prof. Alvarado
MDST 3703
16 October 2012

2. Business
 Midterms next Thursday …
 Assignment:
– See Assignments > Final Projects—Homework 1

3. Review
 Manovich’s thesis: the database is a symbolic
form
– Produces a figure/ground reversal between
paradigmatic resources and syntagmatic products
– Between process of production and finished
product
 How is this reversal represented in Vertov’s
film?
– How does Vertov “solve” the problem of relating
paradigm to syntagm?

4. Overview
 Today we look at the development of the
database as symbolic form on the web
– Symbolic forms shape cognition
 In particular, we look at changes in new media
associated with Web 2.0
– Web 2.0 is, roughly, the web after Google
 In many ways, the Web 2.0 revolution is the
result of the “databasing of the web”

5. Each of these are made possible by the application of database logic

6. Clay Shirky is one of
the most important
theorists of the post-
Google web
American media theorist. Studied fine arts at Yale.
Teacher, writer, consultant. Books include Here
Comes Everybody and Cognitive Surplus.

7. What are some differences between Shirky’s
view of ontology and others we have read?

8. All of the theorists interested in models have
assumed that there is a model in the text
that can be retrieved by scholars (experts)
Shirky embraces the network effects of Web
2.0, in which user participation outstrips the
capacity for experts to control content
The text emerges as a site of competing
interpretations

9. David Weinberger

10. This is the biggest rationalization effect so
far:
That our view of knowledge itself is an effect
of how we organize the documents that
store it
As Wesch says, we will have to rethink some
of our deepest notions

11. For example …
The tree of
nature and logic
From Ramon Lull
Ars Magna (Great
Art), 1305

12. What is the advantage of this kind of structure?

13. Trees can be easily navigated by people

15. What is the advantage of this kind of structure?

16. Content can be classified in as many
ways as there are perspectives
But this kind of organization follows
from information stored in databases

17. URL 1 TAG 1
URL 1 TAG 2
URL 1 TAG 3
URL 2 TAG 2
URL 2 tAG 3
URL 3 TAG 1
URL 4 TAG 5

19. The Method: Tags and URLs
 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

20. Examples
 Delicious (web pages and tags)
 Flickr (images and tags)
 Twitter (tweets and hashtags, retweets)

21. Effects
 Cool visualizations
 Sometimes useful mashups
 The web itself becomes a large, socially
constructed database

22. http://complexrhetoric.blogspot.com/2009/03/is-aristotle-on-twitter-panel-wrap-up.html
A visualization of messages referencing the #Aristotle hashtag on Twitter, created by
Social Collider. The red lines in the center are the #Aristotle references.

23. “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”
Tag Powered Contex
-- 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.op
en.ac.uk/jit/examples/hypertree-demo2.php?mode=tag
http://blog.ouseful.info/2010/09/09/additional-thoughts-on-tag-powered-context/

24. 35,000,000 Flickr Photos, Mapped
hat happens when images are tagged by locatio

26. With Web 2.0 and social media, the
web itself becomes a big database

27. 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

28. 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

29. Michael Wesch is a UVA-trained cultural
anthropologist at Kansas State. The video you saw
propelled him into superstar status . . .

31. Wesch
 Why is it important to separate form and
content?
 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?

32. Brad Pasanek is a Stanford trained UVA professor of
English who has used a simple database approach to
study metaphor.