Earth Sciences Sector
Semantic Web
…vers l’interopérabilité sur le Web
Jean Brodeur
Journée INNOVATION en Géomatique
-
6e Édition
Centre d’information topographique
-
Sherbrooke
8 novembre 2007
2
Déroulement de la présentation
•
Contexte
•
Description
•
Ontologie
•
Technologies du W3C
•
Conclusion
Earth Sciences Sector
Web Sémantique
Contexte
4
Interoperability of information
•
Concerns the
understanding and usage of information
•
Increases the
availability
,
access
,
integration
, and
sharing
of information
•
Concerns the establishment of
data infrastructures
at
local, regional and global level
5
…between people
•
Is based on
–
the communication process;
–
People knowledge and the commonness.
6
… through the communication paradigm
<Factory>
<name>FactoryA</name>
…
User’s request with his own
concepts in memory
(e.g. Factory, Mill,
Plant, etc.)
(Communication channel)
“Factories
within
Kyoto?”
<Factory>
<name>FactoryA</name>
…
5. Data encoding
(message production)
6. Data
transmission
7. Data
reception
8. Data decoding
(message recognition)
R
R’’’’
R’’
R’’’
R’
2. Request
transmission
1. Request encoding
(message production)
Cr =
f
(C)
Provider
User
Administrative area
(Kyoto)
Building (factory)
(Communication channel)
<Factory>
<name>FactoryA</name>
<location>
<GPL_CoordinateTuple>
<tuple
CrsName="urn:EPSG::21418">
1259753 18503245
…
Interoperability =
correspondence of received data with
the initial request.
= T
|
S
|
-
FactoryA
-
EPSG:21418
-
1259753, 18503245
-
Factory
-
Kyoto
-
Factory
-
Kyoto
4. Request decoding
(message recognition)
3. Request
reception
-
Building (factory)
-
Factory
-
Administrative
-
Kyoto
area (Kyoto)
|
S
|
= T
Request recognition from database’s
geographic concepts
then search of corresponding
geographic information.
Recognition =
f
(
{
C
1
, ... ,C
n
}
, Cr)
7
Heterogeneity of information
•
A major barrier to interoperability
•
Types of heterogeneity
–
System
(i.e. interaction between computers of
different OS and databases of
different
DBMS
)
–
Syntactic
(i.e.
differences between formats
such as a GML document and a Shapefile)
–
Schematic
(i.e.
differences in conceptual
schemas
such as
street
may be defined as a
class or as a value of an attribute of a
road
class)
–
Semantic
(i.e.
difference of meaning
given to
a signal, e.g.
chair
means either a seat or a
position of authority, or the various signal
that have a similar meaning, e.g.
watercourse
vs.
river/stream
)
8
Current Web
•
Information is mainly based on
Web documents
•
A Google search lists Web documents that correspond to
keywords
–
e.g. “
Semantic Web
”
•
Web documents are intended to
human beings
, which
have to figure out the nature and usefulness of their
contents
•
It is not designed for the use of information by software
Earth Sciences Sector
Web Sémantique
Une description
10
Semantic Web
•
An idea introduced by
T. Burners
-
Lee
•
From a Web of
documents
for
humans to a Web of
data and
information
processable by
computers
•
Published the first time in
2001
–
T. Berners
-
Lee, J. Hendler, and O.
Lassila, “The Semantic Web,” Scientific
Am., May 2001, pp. 34
–
43.
11
Semantic Web
•
Is about
a Web that answers questions
instead of
returning Web pages about topics of interests
•
Is about
data
that is
application independent
,
composeable
,
classified
, and
part of a larger information
structure
•
Is about
data
that is
understandable and processable by
machines
–
Needs to make the data smarter
Text and DB records
XML with
mixed vocabularies
XML and single
domain vocabularies
Ontologies and rules
12
Data, information, and knowledge pyramid
from semanticweb.org
13
Semantic Web
•
Is seen as a
solution
to
–
information overload
specially with the propagation of
the Internet
–
breaking stovepipe systems and allowing
sharing
information
–
aggregating information
from multiple sources
–
enabling users to
retrieve the data they need
more
efficiently
based on their own vocabulary (concepts) and
data specific vocabulary (concepts)
14
Semantic Web deals with…
•
Common formats
–
XML is the syntactic foundation
(RDF, RDF
-
S, OWL,
RIF
,
SPARQL)
–
Oriented toward integration and
combination of data from various
sources (Web)
–
As opposed to the original Web
that is oriented toward the
interchange of documents
•
Language
–
Capturing how the data relates to
real world objects (RDF
-
S and
OWL).
Berners
-
Lee, T., 2006.
Artificial Intelligence and the Semantic Web
,
AAAI Conference keynote,
2006
-
07
-
18.
http://www.w3.org/2006/Talks/0718
-
aaai
-
tbl/Overview.html
15
Semantic Web… What is needed?
•
Logical assertions
–
connect subject to an object with a verb
–
RDF
•
Classification of concepts
–
Taxonomies/ontologies
•
Formal models
–
Concepts, their properties, and relationships
–
OWL
–
For reasoning
•
Rules
–
Inference rules to derive conclusion
–
RIF
•
Trust
–
Provide access to resources only to trusted agents. An agent can be asserted
“trusted” from another via a digital signature
16
Web services and Semantic Web
•
Based on URI
•
XML
•
Smart data
•
Semantic Web to discover Web services (Semantic Web
-
enabled Web services)
•
Semantic Web to support interaction between Web
services
17
Geospatial Semantic Web
•
Developed by
–
Max J. Egenhofer
, 2002.
Toward the Semantic Geospatial Web
, Proceedings of the
10th ACM international symposium on Advances in geographic information systems,
p.1
-
4, November 08
-
09, 2002, McLean, Virginia, USA
–
Frederico Fonseca and Amit Sheth
, 2002.
The Geospatial Semantic Web
, UCGIS
White Paper, 2002. http://www.ucgis4.org/priorities/research/
2002researchagenda.htm
•
Challenges
–
Ontologies of spatial concepts use across disciplines
geospatial
-
relations ontology
Geospatial feature ontology
–
Ontology management: designing, developing, storing, registering,
discovering, browsing, maintaining and querying
–
Canonical form for geospatial data queries
–
Matching concepts to ontologies
–
Ontology integration
Earth Sciences Sector
Web Sémantique
Ontologie
19
Ontology
•
What is an ontology?
–
Taxonomy?
XML schema?
–
Thesaurus?
Conceptual model?
–
UML, RDF/S, OWL?
Description logic?
–
Logical theory?
•
What is the purpose or role of an ontology?
20
Ontology
•
A
foundation
for the success of the
Semantic Web
•
Meaning of data
in a format that machine can
understand
•
Data derived its
semantics
from ontology
•
To support
integration of heterogeneous data
across
communities
21
Semantics
Concept
•
Thoughts that give
meaning
to signs and
phenomena;
referent
signifier
signified
•
Links between signs and
real world phenomena.
(Frege, Peirce, Ogden & Richards, Eco)
Phenomenon
Colosseum,
Rome,
N41
°
53'25" Latitude
E12
°
29'32" Longitude
Sign
22
Ontology
•
Philosophy
•
Artificial intelligence
23
Ontology… A philosophical account
•
Study or science of being (or existence)
•
Description of the world in itself
•
Type of entities, properties, categories, and relationships
that compose the reality
•
Philosophy consider that there is only one ontology
24
Ontology… An artificial intelligence account
•
“An explicit specification of a conceptualisation”
(Gruber 1993)
•
“A logical theory accounting for the intended meaning
of a vocabulary” (Guarino 1995)
•
A layer enabling the definition of concepts of reality
•
Meaning of a subject area or an area of knowledge
•
A
formal representation of phenomena
with an
underlying
vocabulary
including
definitions
and
axioms
that make the intended meaning explicit and
describe
phenomena and their interrelationships
(Brodeur 2003)
25
Ontology… An artificial intelligence account
•
Represented by classes, relations, properties, attributes,
and values
•
AI considers that
reality may be abstracted differently
depending on the context
from which “things” are
perceived
•
AI recognizes that
multiple ontologies
about the same
part of reality
may exist
26
Ontology… an example
•
Common conceptualization
•
Living structure
–
Static
–
Volatile
•
Explicit commitment to shared meaning among an
interested community
•
Can be re
-
used and extended
27
Ontology
Spectrum
Daconta, M. et al., 2003.
The semantic web
, Wiley.
28
Multiple ontology levels
•
Global or top
-
level ontology:
general concepts independent
of a specific domain (e.g. space,
time, …)
•
Domain ontology: concepts
specific to a domain (e.g.
transportation, geology, land
cover, …)
•
Application ontology: concepts
that are specialised in a given
context and use (e.g. parcel
delivery, ambulance
dispatching, rescue, …)
29
Role of ontology
•
Knowledge base that supports interpretation, reasoning,
and inference
–
Description logic:
river/stream
watercourse
–
Notion of similarity/proximity: the concept
watercourse
contains
the concept
river/stream
–
Joe is passenger of Train 1234; Train 1234 goes to
Rome; Joe goes to Rome
–
…
30
Reasoning and inference
•
Possible through the relation that exist between concepts
–
Subsumption:
isA
,
isSuperclassOf
–
Meronymy:
part of
–
GeoSemantic Proximity: Based on a 4 intersection matrix between intrinsic
and extrinsic properties of two concepts.
intrinsic properties provide the literal meaning of the concept
extrinsic properties provide meaning through the influence that other concepts
have on a concept (e.g. behaviours and relationships)
–
Matching distance: a distance between concepts in a graph
–
…
31
Subsumption relations
32
GeoSemantic Proximity
Intrinsic Properties
(C
K
°
)
Extrinsic
properties
(
C
K
)
C
K
33
Geosemantic Proximity
Common
extrinsic
properties
Common
intrinsic
properties
No common
intrinsic
properties
No common
extrinsic
properties
The geosemantic proximity of
Road
with
Street
is then
GsP_fftt
ou
contains
Road
vs.
Street
:
•
Street
participates in a relationship with other types of
Road
•
Then, the intersection of extrinsic properties of
Street
with intrinsic properties of
Road
is not empty
Road
vs.
Street
:
•
Street
corresponds to a value of the attribute
classification
of
Road
•
Both have the same geometry
•
Then, the intersection of intrinsic properties of
Road
and
Street
is not empty
34
Context
•
Provides concepts with
real
-
world semantics
•
About
how phenomena are perceived and abstracted
resulting in various classes, properties (thematic, spatial,
temporal), and relationships
•
About
how data is captured
in databases including
constraints such as on object dimension
•
Provide details on:
–
Use:
user ID, user profile, user location, type of uses
–
Data:
source, geospatial entities, meaning, scale, date of validity, etc.
–
Association:
relationships (spatial, semantic, etc.)
–
Procedure:
process steps to capture the data, query to get the data, etc.
•
Metadata
constitutes a valuable source of contextual
details
•
Can be captured by the way of intrinsic and extrinsic
properties
35
Interoperability, Semantics, and Ontologies
<Factory>
<name>FactoryA</name>
…
(Communication channel)
“Factories
within
Kyoto?”
<Factory>
<name>FactoryA</name>
…
R
R’’’’
R’’
R’’’
R’
Provider
User
(Communication channel)
<Factory>
<name>FactoryA</name>
<location>
<GPL_CoordinateTuple>
<tuple
CrsName="urn:EPSG::21418">
1259753 18503245
…
-
Factory
-
Kyoto
-
Factory
-
Kyoto
Ontologies
Earth Sciences Sector
Web Sémantique
Technologies du W3C
37
W3C Technologies
•
Resource Description Framework (RDF)
–
http://www.w3.org/RDF/
•
Resource Description Framework Schema (RDF
-
S)
–
http://www.w3.org/TR/rdf
-
schema/
•
Web Ontology Language (OWL)
–
http://www.w3.org/2004/OWL/
38
RDF
•
Is based on the triple:
Subject
-
Predicate
–
Object
•
Subject:
the resource, the
thing
about which
something is asserted
•
Predicate:
the
relation
that
binds the
subject
to the
object
•
Object:
either a
literal
value
or a
resource
referred to the
subject
by
the
predicate
Subject
Object
Literal Value
Predicate
Predicate
Example:
<rdf:Description rdf:about="
#colosseum
">
<ex:
isLocatedIn
>
<rdf:Description rdf:about="
#Rome
">
</rdf:Description>
</ex:
isLocatedIn
>
</rdf:Description>
39
RDF
-
S
•
Based on
RDF
•
Set of
standard RDF resources
to create application/user
community
specific RDF vocabularies
•
Allows to create
classes
of data
•
Class instances are then created in RDF
•
Relations are introduces as property
40
RDF
-
S, an example
CI_Address
CitationAndResponsibleParty
+ addressAdministrativeArea
+ addressCity
41
OWL
•
Language
for knowledge representation
•
Initiated in November 2001
•
Is an evolution of DAML+OIL
–
DAML: DARPA Agent Markup Language
–
DARPA: Defence Advanced Research Projects Agency
–
OIL: Ontology Inference Layer
•
Three levels from low to high expressivity
–
Lite:
intended mainly for the description of classification hierarchy with
attributes, cardinalities are limited to 0 or 1
–
DL:
stands for description logics, add knowledge representation that
improves reasoning, allows much flexibility on cardinality restrictions
–
Full:
allows
maximum expressiveness and the syntactic freedom of RDF.
As such a class may be either a collection of individuals or an individual in
itself
42
OWL , an example
CI_Address
CitationAndResponsibleParty
+ addressAdministrativeArea
+ addressCity
43
Tools
•
Jena 2 Toolkit:
–
RDF/OWL API
–
http://jena.sourceforge.net/
•
Protégé 2000
–
Editor for ontology
–
http://protege.stanford.edu/
•
Tools at Network Inference
–
http://www.networkinference.com/
•
OilEd:
–
http://oiled.man.ac.uk/
–
Editor for ontologies
–
Mostly for DAML+OIL, exports OWL but not a current representation
•
OWL Validator:
–
http://owl.bbn.com/validator/
–
Web
-
based or command
-
line utility
–
Performs basic validation of OWL file
•
OWL Ontology Validator:
–
http://phoebus.cs.man.ac.uk:9999/OWL/Validator
–
a "species validator" that checks use of OWL Lite, OWL DL, and OWL Full constructs
•
Euler:
–
http://www.agfa.com/w3c/euler/
–
an inference engine which has been used for a lot of the OWL Test Cases
•
Chimaera:
–
http://www.ksl.stanford.edu/software/chimaera/
–
Ontology evolution environment (diagnostics, merging, light editing)
–
Mostly for DAML+OIL, being updated to export and inport current OWL
•
Extensive list of tools,
–
http://www.w3.org/2001/sw/WebOnt/impls
Earth Sciences Sector
Web Sémantique
Conclusion
45
Conclusion
•
Semantic Web from T. Burners
-
Lee perspective is:
•
Data interoperability
across applications and
organizations (for IT)
•
A set of
interoperable standards for knowledge exchange
•
An
architecture for interconnected communities and
vocabularies
•
Importance of
URIs and ontologies
•
One URI denotes one concept
46
Conclusion
•
Similitudes importantes entre le Web Sémantique et les
travaux sur l’interopérabilité des données
géographiques
•
ISO/TC 211 amorce un réalignement de ses activités de
normalisation dans le but de profiter des effets du Web
Sémantique et par le fait même d’y contribuer
–
Revue du modèle de référence (ISO19101)
–
Description des modèles UML en OWL
–
Mise à jour du langage de schéma conceptuel (ISO/TS19103)
–
…
Earth Sciences Sector
Questions
Merci
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