The Semantic Web Revisited

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1

The Semantic Web Revisited


Nigel Shadbolt and Wendy
Hall,
University of Southampton

Tim Berners
-
Lee,
Massachusetts
Institute of Technology


IEEE INTELLIGENT SYSTEMS

1541
-
1672/06/$20.00 © 2006 IEEE

2

WWW in 2006


The World Wide Web links
10 billion
pages
, and search engines can divine
themes embodied in the links to
serve useful and relevant content
almost instantaneously.


3

From documents to data and
information


Scientific American
article in 2001 by
Tim Berners
-
Lee


evolution of a Web that consisted largely
of
documents for humans to read to one
that included data and information for
computers to manipulate


T. Berners
-
Lee, J. Hendler, and O.
Lassila, “The Semantic Web,”
Scientific
Am.
, May 2001, pp. 34

43.

4

Semantic Web


is a
Web of actionable
information


information derived from data
through a
semantic theory for
interpreting the symbols
.


The semantic theory
--


meaning



Logical connection of terms
establishes
interoperability
between systems
.


5

A Web of data and information


let us recruit the right data to a
particular use context


opening a
calendar

and seeing
business
meetings
,
travel arrangements
,
photographs
, and
financial transactions

appropriately placed on a time line.


Tim Berners
-
Lee
Scientific American
article assumed that this would be
straightforward, but it’s still difficult to
achieve in today’s Web.


handcrafted for particular tasks
;


little ability to interact with
heterogeneous data and information
types
.

6


Because we haven’t yet delivered
large
-
scale, agent
-
based mediation
,
some commentators argue that the
Semantic Web has
failed

to deliver.



The authors argue that


agents can only flourish when
standards

are well established


Web standards

for expressing shared
meaning have
progressed steadily

over
the past five years.


use of
ontologies
in the
e
-
science

community presagingultimate success for
the Semantic Web



7

A growing need for data
integration


need has increased for shared semantics
and a web of data and information derived
from it.


major driver


e
-
science (
IEEE Intelligent
Systems
, special issue on e
-
science, Jan.
2004)


life sciences research demands the integration of
diverse and heterogeneous data sets that
originate from distinct communities of scientists
in separate subfields.

8


Scientists, researchers, and
regulatory authorities in


genomics,


proteomics,


clinical drug trials,


and epidemiology


Use “
ontologies


9

Ontologies


Used a lot in


Biology (
http://obo.sourceforge.net

http://obofoundry.org/

),


medicine,


genomics,


and related fields


10


Environmental science is
looking to integrate data
from


hydrology,


climatology,


ecology,


and oceanography

http://marinemetadata.org/exampl
es/mmihostedwork/ontologieswo
rk


11

e
-
government initiatives


The United Kingdom has developed
an Integrated Public Sector
Vocabulary
(
www.esd.org.uk/standards/ipsv
)



http://www.esd.org.uk/standards/ips
v/resourcediagram.aspx



12

Progress


Internet Engineering Task Force and
the World Wide Web Consortium
(W3C)


directed major efforts at


specifying, developing, and deploying
languages

for sharing meaning.


provide a foundation for semantic
interoperability

13

Resource Description Framework
(RDF)


RDF

provided a
simple but powerful
triple
-
based representation language

for
Universal Resource Identifiers

(URIs)


W3C recommendation by 1999




enhance the Web’s functionality and
interoperability


RDF Schema became a
recommendation in February 2004

14

Resource Description
Framework

individuals

such as Eric Miller,

identified by http://www.w3.org/

People/EM/contact#me;

• kinds of things

such as Person,

identified by http://www.w3.org/

2000/10/swap/pim/contact#Perso
n;

• properties of those things

such

as mailbox, identified by http://

www.w3.org/2000/10/swap/pim/

contact#mailbox; and

• values of those properties

such
as mailto:em@w3.org as

the value of the mailbox property
(RDF also uses character

strings such as “Eric Miller” and
values from other data

types such as integers and dates
as property values).

15

16

Universal Resource Identifiers

(URI)


URIs
identify resources


Using a
global naming convention


URIs provide the grounding for both
objects and relations


underpin the Semantic Web, allowing
machines to process data directly


Much of the motivation for the
Semantic Web comes from the
value
locked in relational databases

17

Examples of URI references


http://example/resource.txt#frag01


http://somehost/absolute/URI/with/ab
solute/path/to/resource.txt


/relative/URI/with/absolute/path/to/re
source.txt


http://en.wikipedia.org/wiki/Universal_Resource_Identifier#Syntax

18

Triple stores


repositories that can store RDF
content


http://jena.sourceforge.net/

--

look at
this!


http://sourceforge.net/projects/threestor
e



www.oracle.com/technology/tech/seman
tic_technologies/index.html


http://www.oracle.com/technology/tech/
semantic_technologies/htdocs/what_orac
le_brings.html

--

look at this!



19

RDF translation


GRDDL Gleaning Resource
Descriptions from Dialects of
Languages
-

www.w3.org/2004/01/rdxh/spec



extract RDF from XML and XHTML
documents using transformations
expressed in XSLT (Extensible
Stylesheet Language) and associated
with the original content

20

Web Ontology Language


OWL (Web Ontology Language)

www.w3.org/TR/2004/REC
-
owl
-
features
-
20040210



OWL’s core idea is to enable efficient
representation of ontologies that are
alsoamenable to decision procedures.


It checks an ontology to see whether it’s
logically consistent or to determine whether
a particular concept falls within the
ontology.


OWL uses the linking provided by RDF to
allow ontologies to be distributed across
systems

21

Rules and inference


rule
-
based formalisms


uncleof(X,Z) <
--

male(X), siblingof(X,Y),
parentof(Y,Z).


for every X,Y and Z, X is the uncle of Z, if X is a
male who has a sibling Y which is the parent of
Z


Horn
-
clause logics


sqr(X,Y) <
--

Y is } X*X

every X and Y, Y is the sqr of X if Y is X*X


higher
-
order logics,


production systems



22

Ontology development and

management

The ontologies that will furnish the
semantics for the Semantic Web must
be developed, managed, and
endorsed by
practice communities
.



Ontologies are attempts to more
carefully
define parts of the data
world

and to
allow interactions
between data held in different
formats
.

23

Deep ontologies



Deep ontologies are often those
encountered in science and
engineering, where considerable
efforts go into building and
developing the conceptualization.

Proteomics and medicine, the ontology
is in a very real sense the data of
interest


24

Shallow ontologies


comprise relatively few unchanging
terms that organize very large
amounts of data


E.g., customer
,
account number
, and
overdraft
used in banking and
financial contexts or the basic
relations



25

Semantic Web contribute to a new
Web Science


Challenges:


the
developments, methodologies, challenges, and
techniques


New Science
-

Web Science


a science that seeks to develop, deploy, and understand
distributed information systems, systems of humans and
machines, operating on a global scale
.


AI

will be one of the contributing disciplines.



ways to understand
distributed systems
,
pattern detection
and data mining tools,


approaches to inference, ontological engineering and
knowledge representation