Semantic Web

1
Semantic Web

• Hieu Le, Nhung Nguyen, Mayssam
• UIUC - CS511 Fall 2005
• (lots of slides browed from Deborah McGuinness,
  James Hendler, Stefan Decker, Mike Lowndes,
  Mehmet S. Aktas, Steve Cayzer)

2
Roadmap

• Motivation
• Broad picture
• Zoom in to current state
• Zoom in closer to the future
• The Holly Grail A Killer App.
• Discussion
• Conclusion

3
Today Rich Information Source for Human
Manipulation/Interpretation
4
Tomorrow Rich Information Source for Agent
Manipulation/Interpretation
5
Doctors appointmentThe Semantic Web,
Scientific American, May 2001
6
Roadmap

• Motivation
• Broad picture
• Zoom in to current state
• Zoom in closer to the future
• The Holly Grail A Killer App.
• Discussion
• Conclusion

7
The Evolving Web
DATA/PROGRAMS
DOCUMENTS
8
Web Semantics
Semantic Web LayerCake (Berners-Lee,
99Swartz-Hendler, 2001)
9
Cant we just use XML?
This is what a web-page in natural language
looks like for a machine
10
XML helps
XML allows meaningful tags to be added toparts
of the text
11
XML ? machine accessible meaning
But to your machine, the tags look like this.
12
Schemas take a step in the right direction
Schemas help.
lt CV gt
by relating common termsbetween documents
private
13
But other people use other schemas
Someone else has one like this.
?namegt
lteducgt
lt CV gt
ltgt
lt????gt
14
The semantics isnt there
lt CV gt
which dont fit in
private
15
KR provides external referents to merge on
nme
CV
CV
work
vate
CV
educ
educ
SW languages add mappings And structure.
16
Current Activities
Semantic Web LayerCake (Berners-Lee,
99Swartz-Hendler, 2001)
17
Roadmap

• Motivation
• Broad picture
• Zoom in to current state
• Zoom in closer to the future
• The Holly Grail A Killer App.
• Discussion
• Conclusion

18
W3C Web Ontology Working Group

• Web Ontology Working Group in the W3C Semantic
  Web Activity aimed at extending the semantic
  reach of current XML and RDF meta-data efforts.
  
• History
• DAMLOIL is submitted as a joint committee effort
  published as a W3C note .
• W3C WG Announcement in November 2001 -
  http//lists.w3.org/Archives/Public/www-rdf-logic/
  2001Nov/0000.html
• Weekly teleconferences started in November 2001
• First Face to Face Meeting - New Jersey (Lucent),
  Jan 02 2nd - Amsterdam April (W3C) 3rd - CA
  (Fujitsu/Stanford host) July 4th in Bristol UK
  (HP Host) Oct.
• Four Working Drafts to date
• Requirements/Use cases - March 2002
• 3 Technical Documents - July 2002 (Language
  renamed OWL)

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Membership

• Current Working Group includes over 50 members
  from over 30 organizations.
• Chairs
• J. Hendler, MIND Lab UMCP
• G. Schreiber, Univ. of Amsterdam
• Industry including
• Large companies - Daimler Chrysler, IBM, HP,
  Intel, EDS, Fujitsu, Lucent, Motorola, Nokia,
  Philips Electronics, Sun, Unisys
• Newer/smaller companies - IVIS Group, Network
  Inference, Stilo Technology, Unicorn Solutions
• Government and Not-For-Profits
• US Defense Information Systems Agency,
  Interoperability Technology Association for
  Information Processing, Japan (INTAP) ,
  Electricite De France, Mitre, NIST
• Universities and Research Centers
• University of Bristol, University of Maryland,
  University of Southamptom, Stanford University
• DFKI (German Research Center for Artificial
  Intelligence), Forschungszentrum Informatik,
  Ontoweb
• Invited Experts
• Well-known academics from non-W3C members (Hayes,
  Heflin, Stein, Borden)

20
The Semantic Stack and Ontology Languages
B
A
From The Semantic Web technical report by Pierce
The Semantic Language Layer for the Web
A Ontology languages based on XML syntax B
Ontology languages built on top of RDF and RDF
Schema
21
Resource Description Framework (RDF) - I

• Resource Description Framework (RDF) is a
  framework for
• describing and interchanging metadata (data
  describing the web
• resources).
• RDF provides machine understandable semantics for
  metadata.
• This leads,
• better precision in resource discovery than full
  text search,
• assisting applications as schemas evolve,
• interoperability of metadata.

22
Resource Description Framework (RDF)- II

• RDF has following important concepts
• Resource The resources being described by RDF
  are anything that can be named via a URI.
• Property A property is also a resource that has
  a name, for instance Author or Title.
• Statement A statement consists of the
  combination of a Resource, a Property, and an
  associated value.

Example Alice is the creator of the resource
http//www.cs.indiana.edu/Alice.
23
The Dublin Core Definition Standard

• RDF is dependent on metadata conventions for
  definitions.
• The Dublin Core is an example definition standard
  which defines a simple metadata elements for
  describing Web authoring.
• It is named after 1995 Dublin (Ohio) Metadata
  Workshop.
• Following list is the partial tag element list
  for Dublin Core standard.
• Creator the primary author of the content
• Date date of creation or other important life
  cycle events
• Title the name of the resource
• Subject the resource topic
• Description an account of the content
• Type the genre of the content
• Language the human language of the content.

24
Example
Alice is the creator of the resource
http//www.cs.indiana.edu/Alice.
Property
Resource
Property Value
creator
http//purl.org/dc/elements/1.1/creator
http//www.cs.indiana.edu/Alice
Alice

• Property creator refers to a specific
  definition. (in this example by Dublin Core
• Definition Standard). So, there is a structured
  URI for this property. This URI makes this
• property unique and globally known.
• By providing structured URI, we also specified
  the property value Alice as following.
• http//www.cs.indiana.edu/People/auto/b/Alice

Inspired from The Semantic Web technical report
by Pierce
AIST Meeting JPL, CA 2003
25
Example
Why bother to use RDF instead of XML?
Alice is the creator of the resource
http//www.cs.indiana.edu/Alice.

ltrdfRDF xmlnsrdfhttp//www.w3c.org/1999/02/22-
rdf-syntax-ns xmlnsdchttp//purl.org/d
c/elements/1.1 xmlnscglhttp//cgl.indian
a.edu/peoplegt ltrdfDescription about
http//www.cs.indiana.edu/Alicegt ltdccreatorgt
ltcglstaffgt Alice lt/cglstaffgt lt/dccreatorgt lt/r
dfRDFgt

• Information in the graph can be modeled in diff.
  XML organizations. Human readers would
• infer the same structure, however, general
  purpose applications would not.
• Given RDF model enables any general purpose
  application to infer the same structure.

Inspired from The Semantic Web technical report
by Pierce
AIST Meeting JPL, CA 2003
26
RDF Schema (RDFS )
It resembles objected-oriented programming

• RDF Schema is an extension of Resource
  Description Framework.
• RDF Schema provides a higher level of abstraction
  than RDF.
• specific classes of resources ,
• specific properties,
• and the relationships between these properties
  and other resources can be described.
• RDFS allows specific resources to be described as
  instances of more general classes.
• RDFS provides mechanisms where custom RDF
  vocabulary can be developed.
• Also, RDFS provides important semantic
  capabilities that are used by enhanced semantic
  languages like DAML, OIL and OWL.

AIST Meeting JPL, CA 2003
27
Limitations of RDF/RDFS

• No standard for expressing primitive data types
  such as integer, etc. All data types in RDF/RDFS
  are treated as strings.
• No standard for expressing relations of
  properties (unique, transitive, inverse etc.)
• No standard for expressing whether enumerations
  are closed.
• No standard to express equivalence,
  disjointedness etc. among properties

AIST Meeting JPL, CA 2003
28
DAML, OIL and DAMLOIL - I

• RDF\RDFS define a framework, however they have
  limitations. There is a need for new semantic web
  languages with following requirements
• They should be compatible with (XML, RDF/RDFS)
• They should have enough expressive power to fill
  in the gaps in RDFS
• They should provide automated reasoning support
• Ontology Inference Layer (OIL) and DARPA Agent
  Markup Language (DAML) are two important efforts
  developed to fulfill these requirements.
• Their combined efforts formed DAMLOIL
  declarative semantic language.

AIST Meeting JPL, CA 2003
29
DAML, OIL and DAML OIL - II

• DAMLOIL is built on top of RDFS.
• It uses RDFS syntax.
• It has richer ways to express primitive data
  types.
• DAMLOIL allows other relationships (inverse and
  transitivity) to be directly expressed.
• DAMLOIL provides well defined semantics, This
  provides followings
• Meaning of DAMLOIL statements can be formally
  specified.
• Machine understanding and automated reasoning can
  be supported.
• More expressive power can be provided.

AIST Meeting JPL, CA 2003
30
Example
How is DAMLOIL is different than RDF/RDFS?

• Example T. Rex is not herbivore and not a
  currently living species.
• This statement can be expressed in DAMLOIL, but
  not in RDF/RDFS since RDF/RDFS cannot express
  disjointedness.
• DAMLOIL provides automated reasoning by
  providing such expressive power.
• For instance, a software agent can find out the
  list of all the carnivores that wont be any
  threat today by processing the DAMLOIL data
  representation of the example above.
• RDF/RDFS does not express is not relationships
  and exclusions.

From The Semantic Web technical report by Pierce
AIST Meeting JPL, CA 2003
31
Web Ontology Language (OWL)

• Web Ontology Language (OWL) is another effort
  developed by the OWL working group of the
  W3Consorsium.
• OWL is an extension of DAMLOIL.
• OWL is divided following sub languages.
• OWL Lite
• OWL (Description Logics) DL
• OWL Full limited cardinality
• OWL Lite provides many of the facilities of
  DAMLOIL provides. In addition to RDF/RDFS tags,
  it also allows us to express equivalence,
  identity, difference, inverse, and transivity.
• OWL Lite is a subset of OWL DL, which in turn is
  a subset of OWL Full.

AIST Meeting JPL, CA 2003
32
A Note Having an ontology is not enough

• The philosophy of WWW and SW is similar
  decentralized
• Ontologies and data formats are different from
  sources to sources, time to time.
• ? Ontology matching
• ?Data Integration

33
A Note Having an ontology is not enough

• The philosophy of WWW and SW is similar
  decentralized
• Ontologies and data formats are different from
  sources to sources, time to time.
• ? Ontology matching
• ?Data Integration

34
But will it fly?

• DAMLOIL is already the most used ontology
  language ever!!
• http//www.daml.org (3.5M statements on 25,000
  web pages)
• Gaining acceptance by web players
• Semantic Web Track being offered at WWW 2002
• 3x more people attended WWW2002 Developer Day on
  SW than attended KR
• Significant (international) Govt Support
• US DARPA/NSF EU IST Framework 5,6
• Japan, Germany, Australia considering significant
  investments
• US National Cancer Institute to publish cancer
  vocabulary in DAMLOIL
• Much New Startup activity (even in this economic
  climate)
• Many tools being developed
• Many of them aimed at developers, not just AI
  literate types

35
Roadmap

• Motivation
• Broad picture
• Zoom in to current state
• Zoom closer to the future
• The Holly Grail A Killer App.
• Discussion
• Conclusion

36
Moving to the future of the web
Semantic Web LayerCake (Berners-Lee,
99Swartz-Hendler, 2001)
37
Web Agents need Service Descriptions
38
Semantic Web Service Description
39
Services need Web Logics
40
Web of Trust

• Claims can be verified if there is supporting
  evidence from another (trusted) source
• We only believe that someone is a professor at a
  university if the university also claims that
  person is a professor, and the university is on a
  list I trust.

believe(c1) - claims(x, c1) predicate(c1,
professorAt) arg1(c1, x) arg2(c1,
y) claims(c2, y) predicate(c2,
professorAt) arg1(c2, x) arg2(c2,
y) AccreditedUniversity(y) AcknowledgedUniversit
y(u) - link-from(http//www.cs.umd.edu/universit
y-list,u)
Notice this one
41
Roadmap

• Motivation
• Broad picture
• Zoom in to current state
• Zoom closer to the future
• The Holly Grail A Killer App.
• Discussion
• Conclusion

42
FOAFa semweb case study
The Friend of a Friend (FOAF) project is about
creating a Web of machine-readable homepages
describing people, the links between them and the
things they create and do. Distributed RDF/XML
records describing people, who they know,
projects they work on
43
FOAF - motivations

• Augment e-mail filtering by prioritizing mails
  from trusted colleagues
• Locate people with interests similar to yours
• Find an expert in knowledge communities
• Social network analysis
• Photo co-depiction

44
A simple foaf model
foafPerson
rdftype
foafname
Michael Souris
foafmbox
mailtomm_at_example.com
45
.. which can be serialized in XML
ltrdfRDF xmlnsrdf"http//www.w3.org/1999/02/22-r
df-syntax-ns" xmlnsfoaf"http//xmlns.com/foaf/
0.1/"gt ltfoafPersongt ltfoafnamegtMichael
Sourislt/foafnamegt ltfoafmbox
rdfresource"mailtomm_at_example.com" /gt
lt/foafPersongt lt/rdfRDFgt
46
So what?
47
We need more!

• The history of WWW is a lesson
• We see the potential, but
• How to convince people to mark up their pages?
• How to convince organization to export their data
  in SW formats?

? Answer We need a Killer Application
48
We need more!

• The history of WWW is a lesson
• We see the potential, but
• How to convince people to mark up their pages?
• How to convince organization to export their data
  in SW formats?

? Answer We need a Killer Application
49
Semantic Web Challenge Minimum Requirements

• First, the information sources used
• should be geographically distributed,
• should have diverse ownerships (i.e. there is no
  control of evolution),
• should be heterogeneous (syntactically,
  structurally, and semantically), and
• should contain real world data, i.e. are more
  than toy examples.
• Second, it is required that all applications
  assume an open world, i.e. assume that the
  information is never complete.
• Finally, the applications should use some formal
  description of the meaning of the data.

50
Semantic Web Challenge More Requirements

• The application uses data sources for other
  purposes or in another way than originally
  intended
• Using the contents of multi-media documents
• Accessibility in multiple languages
• Accessibility via devices other than the PC
• Other applications than pure information
  retrieval
• Combination of static and dynamic knowledge (e.g.
  combination of static ontologies and dynamic
  work-flows)
• The results should be as accurate as possible
  (e.g. use a ranking of results according to
  validity)
• The application should be scalable (in terms of
  the amount of data used and in terms of
  distributed components working together)

51
For short, a Killer Application must provide

• A service that is not possible or practical under
  more traditional technologies,
• Some clear benefit to developers, data providers,
  and end users with minimum extra costs
• an application that becomes indispensable to a
  user-base much wider than the SW researchers
  community.

52
Roadmap

• Motivation
• Broad picture
• Zoom in to current state
• Zoom closer to the future
• The Holly Grail A Killer App.
• Discussion
• Conclusion

53
How do you think?

• Semantic web Make the web become a huge
  distributed database

54
Roadmap

• Motivation
• Broad picture
• Zoom in to current state
• Zoom closer to the future
• The Holly Grail A Killer App.
• Discussion
• Conclusion

55
Conclusion

• It is no longer a question of whether the
  semantic web will come into being, it is already
  here!
• Were already well past the starting gate
• Web ontologies, term languages, shims to DB and
  services, research in proofs/rules/trust
• Standardization providing a common denominator
  for KR researchers as well as web developers
• Small companies starting to form, Big companies
  starting to move
• Challenges ahead
• Ontology mapping
• Data Integration
• Finally, a Killer Application

56
Thanks
57
An Example
www.cs.washington.edu
www.cs.usyd.edu.au

• Find Prof. Cook, a professor in a Seattle
  college, earlier an assoc. professor at his alma
  mater in Australia

Semantic Mappings allow information processing
across ontologies
58
Solution Relaxation Labeling

• Iterative estimation of most likely label
  assignment

Staff
People
Acad
Staff
Fac
Tech
Prof
Lect.
Assoc. Prof
Asst. Prof
Prof
Snr. Lect.

• Challenges
• Making the computation tractable large number
  of labels
• Combining effects of various constraints

59
Languages for Ontologies E.g. DAMLOIL
Ontology Design Tools E.g. Protégé, Ontolingua,
Semantic Mapping
60
On the Web -- links are critical!
Web page
Any Web Resource
lta href
URIgt
HTML
lta hrefhttp//gt
61
RDF graphs resemble semantic nets
DOC1
ltmindPerson rdfidHendlergt ltmindtitle
jobsProfessorgt ltjobsplaceOfWork
http//www.cs.umd.edugt lt/mindPersongt
Jobs
Mind
Professor
DOC1
Mindtitle
Hendler
Jobs
Web Page http//www
JobsplaceOfWork
62
Semantics on the WEB

• RDF, like the WWW itself, is not separable
• Thinking about the ontologies, without
  considering
• The links to other terms
• The instances that link to them
• The crawling and collecting of ontological
  terminologues
• Is like thinking about the Web without the
  links!!

OtherProfessors
Othertitles
OtherPages
Jobs
Mind
Professor
OtherURIs
DOC1
Mindtitle
Hendler
Jobs
Web Page http//www
JobsplaceOfWork
Otherdescriptions
63
Radically new view of Semantics
some partial mapping
Distributed,partially mapped, inconsistent -- but
SCALEABLE!