Web Science 2007-10-22 Tim Berners-Lee 965c47c5a70db7407210cef6e4e6f5374a525c5c MIT NE20, Room 336 Conference Room (3 Cambridge Center) Cambridge Massachusetts Center for Collective Intelligence 2007 keynote

The Fractal Web

http://www.w3.org/2007/Talks/1022-fractal-tbl/

Tim Berners-Lee

MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)

University of Southampton School of Electronics and Computer Science

This talk

Philosophical Engineering

Designing a system...

process of web science

involves social conventions too.

process of web science

Microscopic system

process of web science

Macroscopic effect

process of web science

Analyse the result

process of web science

Is this what we want?

process of web science

The process of web science

process of web science

Science and engineering

process of web science

Magic

process of web science magic = stuff you don't understand

More magic

magic = stuff you don't understand yet process of web science

Second guessing

Second guessing

(More slides on Web science)

Web Science: multidisciplinary

Many people are doing Web Science already

Web Science Research Initiative

WSRI

For example...

process of web science

Email

process of web science

WWW - as envisaged

process of web science: WWW

WWW

process of web science: WWW

Semantic Web

process of web science

SW: Everything has a URI

Don't say "colour" say <http://example.com/2002/std6#col>

(More slides on Semantic Web)

Semantic Web Technical

architectural layers

The element of the Semantic Web

arrow tail, body and head are l are subject, property and value.

Semantic web includes tables,...

Arrows can make a table, an arrow from each row to each value

...trees

Arrows can make a table, an arrow from each row to each value

... everything

Arrows can make a table, an arrow from each row to each value

Shapes of data

Cultures, Groups and boundaries

Extreme 1: Monoculture

Extreme 2: Extreme diversity

The shape of the web

Society includes communities on many scales

Universal WWW must include communities on many scales

Applications connected by concepts

Its like a metro, the way the lines of common concepts
connect the stations of different applications

For example in biopax

Venn diagram showing ontologies overlapping by certain common terms

[Diagram: Joanne Luciano, Predictive Medicine Drug discovery demo using RDF, Siderian Seamark and Oracle 10g]

The fractal tangle


Total Cost of Ontologies (TCO)

Assume :-) ontologies evenly spread across orders of magnitude; committee size as log(community), time as committee^2, cost shared across community.
Scale Eg Committee size Cost per ontology (weeks) My share of cost
0 Me 1 1 1
10 My team 4 16 1.6
100 Group 7 49 0.49
1000 10 100 0.10
10k Enterprise 13 169 0.017
100k Business area 16 256 0.0026
1M 19 361 0.00036
10M 22 484 0.000048
100M National, State 25 625 0.000006
1G EU, US 28 784 0.000001
10G Planet 31 961 0.000000

Total cost of 10 ontologies: 3.2 weeks. Serious project: 30 ontologies, TCO = 10 weeks.
Lesson: Do your bit. Others will do theirs.
Thank those who do working groups!

Engineering for scale-free systems

Allow groups to form

User interface for adding data

  1. Prompt for well-known terms
  2. Allows discovery and selection of local group terms
  3. Allow creation of new terms

Message mixes vocabulary from many cultures

Data mixing: Term by term

dc:titleData Integration and Transparency
cc:license <http://creativecommons.org/licenses/by-nc/3.0/>
dc:creator
foaf:nameTim Berners-Lee
foaf:homepage<http://ww.w3.org/People/Berners-Lee>
foaf:email<mailto:timbl@w3.org>
tk:event
dt:start2007-06-12T09:00
dt:end2007-06-12T10:00
dt:summaryW3C-WSRI eGovernment workshop
geo:lat38.9
geo:long-77
tk:slides<http://www.w3.org/2007/Talks/0618-egov-tbl>
tim:slideCount12

One item may involve data from many ontologies

The tradeoff

LocalWider
Local reuse onlyWider reuse
Local termsGlobal or shared terms
FastTakes effort

Semantic Web optimizes the tradeoff

Data owners should

  1. Take inventory
  2. Decide priorities, most likely benefits
  3. Look for existing ontologies
  4. Don't change the way data is crrently managed
  5. Set up standard (RDF, SPARQL) portals onto existing data
  6. Where necessary, adapt or write new ontology bits

Linked Data

Linking out is to use in your data URIs for objects as described on sites

Incentive: kudos, reuse

Web Science Challenges

Challenge: Collective Decision making

Challenge: Collective Creativity

Thank You

More:

WSRI: webscience.org

Thank you for your attention

http://www.w3.org/2007/Talks/1022-fractal-tbl/