Web Principles, Hopes and Fears

Richard E. Snyder President's Lecture
March 28, 2006
Tufts University

http://www.w3.org/2006/Talks/0328-tufts-tbl/

MIT Computer Science & Artificial Intelligence Laboratory (CSAIL)
Southampton University, School of Electronics and Computer Science (ECS)
Director, World Wide Web Consortium

This talk

Philosophical engineering
The Web and Semantic Web
Universality
Decentralization
Scale-free structure

but not necessarily in that order.

Philosophical Engineering

cf. Experimental Philosophy
Microscopic rules
Macroscopic behavior
Connection between them
Synthesis vs Analysis
Rules are social as well as technical

"Web Science"

Example: eMail

Technical Rules: store & forward, no trust infrastructure
Social Rules: don't bother people
Scales in academic environment
Doesn't scale in commercial environment

Web rules

Technical:

Use URIs for documents and anchors
Ladder of authority to interpret
Use standards (HTTP. xHTML, SVG, CSS, DOM, XSLT, ...)

Social:

Serve useful stuff
Make useful links
Intellectual property, libel & fraud laws

Wiki

micro: A simple editor
micro: Citizen's responsibility
Macro: Wikipedia

Blogs

Micro: Trackback
Macro: The blogosphere

Semantic Web

Technical:

Use URIs for documents and concepts
Same ladder of authority
Standards: (RDF, OWL, SPARQL*, RIF**)

Social:

Serve useful stuff
Make useful links
Share ontologies
Agree on ontologies

Universality of the Web

Information independent of

Hardware platform
Software platform - OS
Application Software
Network access
Public, Group, or Personal scope
Quality - Scribbled idea to polished publication
Language and culture
Disability
Data for machines or Documents for people
Scale
Time

Independence of Hardware

Originally: Mainframes vs mini vs PC
Later: VGA vs 800x600
Now: Laptop vs handheld vs LCDTV
Technique: Separation of content and form
Example: Cascading Style Sheets

Independence of Operating system

Was: VM-CMS vs VAX/VMS vs Unix
Now: OSX vs Windows VS Linux vs series 60 etc
Technique: Standards, open standards

Independence of application software

Was: WorldWideWeb, Erwise, ViolaWWW, Mosaic, Lynx etc
Now: Firefox vs Internet Explorer vs Opera etc
Technique: Open Standards

Independence of Network

Was: Decnet vs Internet protocol vs CERNnet etc
Now: IP on RCN vs Verizon vs ...
Technique: Common Internet Protocol and API
Technique: Internet "cloud" mimics single connection point
Concern: IP carrier deals link specific producer-consumers

Public/Private scope

Must be able to links public and private info
Systems spread faster behind firewalls
Intra and internets must be compatible
Internal and external data must be linkable

Independence of Quality

Quality is subjective

A universal system can't use one person's criterion
Example: Nudity and violence ratings internationally
Example: Religious material
Technique: Metadata, and parent choice
"Anyone can say Anything about Anything"
Technique: Annotation, tagging, etc
Google algorithm finds clusters
Hope: Censorship gives way to openness
Hope: Peer review systems and distributed democracy

Independence of Language and Culture

Techniques: Unicode, W3C character model
Techniques: xml:lang attributes
A lot more than characters

Independence of Disability

20% have some disability
50% make some adaptation
Web Accessibility Initiative
Guidelines for making web sites
Guidelines for making software to make web pages
International harmonization
Not just visual impairment!

Data vs Documents

Data is currently pre-web

Model your data --> ontology
Map your data to ontology
Publish it as [virtual] RDF
Query using SPARQL Protocol And RDF Query Language
Aim for serendipitous reuse

Independence of Scale

What shape should the WWW be?

Decentralization

No central bottleneck (net)
No conceptual bottleneck (censor)
No cultural bottleneck (ratings)
No single root of a tree (ontology)
Concern: DNS
Concern: 'net' is tree-like

Graph structure

Allows many trees to be expressed
Allows tables to be expressed
Doesn't go back in the tree
Needs some structure

Semantic web includes tables,...

...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

RDF data...

a set of circles and arrows

...merges just like that.

more circles and arrows superim

Subject and object node using same URIs

Communities and Vocabularies

Universal WWW must include communities on many scales

Communities communicate with languages
Languages form barriers
Barriers are essential to the community
Communicting with other communities is expensive
Developing wider languages is expensive
For data web, communities map to ontologies

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, Sideran Seamark and Oracle 10g]

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!

The fractal tangle

Communities will be of many sizes.
There will be very many small ones (6.10^9 of size 10^0) and a few global ones (e.g. W3C Rec'n)
Kleinberg shows that fractal (1/f) distribution is optimal under some assumptions
Swoogle results for example (right)
We have less experience when fractal is not constrained to a 2D surface.

Goal: Wide depolyment of data

Personal informatuion management
Common Scientific data
Lab notebook details
Ecomonic and Financial
Regulatory, Tax etc

Impact of Semantic Web

Much more data integration power
- much more policy awareness required
- systems with transparency ("Why? How do you know that?")
Computer analysis of data much more powerful
- work needed on emergent properties, stability, and
- in general relationship of µrules to Mphenomena<.li>