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Semantic Web: State of the Art and Opportunities

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Title: Semantic Web: State of the Art and Opportunities


1
Semantic Web State of the Art and Opportunities
Industrial Ontologies Group
  • Vagan Terziyan
  • Compiled, partly based on various online
    tutorials and presentations, with respect to
    their authors
  • Industrial Ontologies Group
  • http//www.cs.jyu.fi/ai/OntoGroup/index.html

University of Jyväskylä
2
Web of Everything Summary (EaaS4E beyond
Cloud Computing)
  • While the academic and business communities are
    exited with the new Cloud Computing and SOA
    slogan EaaS Everything-as-a-Service !
    spending to it huge resources without full
    understanding of what everything actually
    means, our group since 2003 with extremely modest
    resources is actively working on GUN technology
    and Web 5.0 (Web of Everything), which much
    more challenging slogan (based on ?-projection
    technological vision) is EaaS4E
    Everything-as-a-Service for Everything!, meaning
    Really Everything-as-a- Proactive, Semantic and
    Intelligent Web Service Provider and Consumer!.

October 2009 Vagan Terziyan Head of Industrial
Ontologies Group
3
2020 And Beyond ..
Middle Agent
Praffuls Agent Contacts A Middle Agent to find
out some hospital in powai having a recently
admitted patient named Hansa.
Agent Your wife is admitted at New Powai
Hospital Ward No. 9
Agent Your meeting is re-scheduled to tomorrow
500 PM
Phone Your wife had an accident she is admitted
at some hospital in powai
New Powai Hospital
Prafful I still dont know where is she
admitted in powai . I should use my agent .
Prafful I have a meeting with my boss and I am
late .
Prafful I should inform my agent to reschedule
meeting
Praffuls Agent Negotiates With Bosss Agent and
re-schedule meeting to tomorrow.
4
Motivation for Semantic Web
5
i.e. the Syntactic Web is
  • A place where
  • computers do the presentation (easy) and
  • people do the linking and interpreting (hard).
  • Why not get computers to do more of the hard
    work?

Goble 03
6
Hard Work using the Syntactic Web
  • Complex queries involving background knowledge
  • Find information about animals that use sonar
    but are not either bats, dolphins or whales
  • Locating information in data repositories
  • Travel enquiries
  • Prices of goods and services
  • Results of human genome experiments
  • Delegating complex tasks to web agents
  • Book me a holiday next weekend somewhere warm,
    not too far away, and where they speak French or
    English

Almost impossible for machines and too hard for
people without automation
7
Limitations of the Web today
Machine-to-human, not machine-to-machine
8
Summarizing the Problem Computers dont
understand Meaning
  • My mouse is broken. I need a new one

Use of ontology My mouse is broken vs. My
mouse is dead
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14
Approach Semantic Web
  • The Semantic Web is a vision the idea of
    having data on the Web defined and linked in a
    way that it can be used by machines not just for
    display purposes,
  • but for automation, integration and reuse
  • of data across various applications
  • http//www.w3.org/sw/
  • The Semantic Web is an initiative with the
    goal of extending the current Web and
    facilitating Web automation, universally
    accessible web resources, and the 'Web of Trust',
    providing a universally accessible platform that
    allows data to be shared and processed by
    automated tools as well as by people.

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22
Tim Berners-Lee's Vision of Semantic Web
(IJCAI-01)
23
Semantic Web Stack (updated, W3C, 2006)
24
Semantic Web New Users
applications
agents
25
Semantic Web Annotations
applications
agents
Semantic annotations are specific sort of
metadata, which provides information about
particular domain objects, values of their
properties and relationships, in a
machine-processable, formal and standardized way.
26
Semantic Web Ontologies
applications
agents
Ontologies make metadata interoperable and ready
for efficient sharing and reuse. It provides
shared and common understanding of a domain, that
can be used both by people and machines.
Ontologies are used as a form of agreement-based
knowledge representation about the world or some
part of it and generally describe domain
individuals, classes, attributes, relations and
events.
27
Semantic Web Rules
applications
agents
Logical support in form of rules is needed to
infer implicit content, metadata and ontologies
from the explicit ones. Rules are considered to
be a major issue in the further development of
the semantic web. On one hand, they can be used
in ontology languages, in conjunction with or as
an alternative to description logics. And on the
other hand, they will act as a means to draw
inferences, to configure systems, to express
constraints, to specify policies, to react to
events/changes, to transform data, to specify
behavior of agents, etc.
28
Semantic Web Languages
applications
agents
Languages are needed for machine-processable
formal descriptions of metadata (annotations)
like e.g. RDF ontologies like e.g. OWL. rules
like e.g. RuleML. The challenge is to provide a
framework for specifying the syntax (e.g. XML)
and semantics of all of these languages in a
uniform and coherent way. The strategy is to
translate the various languages into a common
'base' language (e.g. CL or Lbase) providing them
with a single coherent model theory.
29
Semantic Web Tools
applications
agents
User-friendly tools are needed for metadata
manual creation (annotating content) or automated
generation, for ontology engineering and
validation, for knowledge acquisition (rules),
for languages parsing and processing, etc.
30
Semantic Web Applications and Services
applications
agents
Utilization of Semantic Web metadata, ontologies,
rules, languages and tools enables to provide
scalable Web applications and Web services for
consumers and enterprises" making the web
'smarter' for people and machines.
31
The Semantic Web
The Ontology Articulation Toolkit helps agents to
understand unknown ontologies
32
Cant we just use XML?
This is what a web-page in natural language
looks like for a machine
J. Hendler
33
XML helps
XML allows meaningful tags to be added to parts
of the text
J. Hendler
34
XML ? machine accessible meaning
But to your machine, the tags look like this.
J. Hendler
35
Schemas take a step in the right direction
Schemas help.
lt CV gt
by relating common terms between documents
private
J. Hendler
36
But other people use other schemas
Someone else has one like this.
?namegt
lteducgt
lt CV gt
ltgt
lt????gt
J. Hendler
37
The semantics isnt there
lt CV gt
which dont fit in
private
J. Hendler
38
KR provides external referents to merge on
nme
CV
CV
work
vate
CV
educ
educ
Semantic Web languages add mappings and structure.
J. Hendler
39
Semantic Web basics
  • RDF
  • is a W3C standard, which provides tool to
    describe Web resources
  • provides interoperability between applications
    that exchange machine-understandable information
  • RDF Schema
  • is a W3C standard which defines vocabulary for
    RDF
  • organizes this vocabulary in a typed hierarchy
  • capable to explicitly declare semantic relations
    between vocabulary terms

40
Where we are Today the Syntactic Web
Hendler Miller 02
41
Most of the Current Web (dumb links)
42
Semantic Web (data connected by relationships)
43
RDF Semantic Web over Web Resources
John
has_homepage
Director
has_job
to_be_in_love_with
Ontology
has_job
has_homepage
Secretary
Mary
44
Resources
  • All things being described by RDF expressions are
    called resources
  • entire Web page
  • a specific XML element
  • whole collection of pages
  • an object that is not directly accessible via the
    Web.

45
Semantic Predicate
Lk
Aj
Ai
Relation (i ? j)
Ai
Property (i j)
Lk
46
Semantic Function
Variables
Name of Function
Value of property
Lk
Aj
Ai
Relation
Ai
Property
Lk
47
Different Ways to Represent properties
in RDF
in RDFS
in semantic network
48
RDF Statement
Property_k
Resource_i
Value_n
OR
Property_r
Resource_i
Resource_ j
49
Semantic Relation as RDF statement (so called
object property)
Lk
Relation
Aj
Resource
Ai
Resource
Relation (i ? j)
Subject
object
Predicate
Personal web page of Terziyan V.
Web page of Agora Center
http//www.cs.jyu.fi/ai/vagan/index.html
http//www.jyu.fi/agora-center/indexEng.html
refers_to
employed_by
URI of Terziyan V.
URI of Agora Center
http//www.cs.jyu.fi/ai/vagan/vagan
http//www.jyu.fi/agora-center/AC
Dereferenceable URI (Hash vs. Slash)
Dereferenceable URI (Hash vs. Slash)
50
Semantic Property as RDF statement (so called
datatype property)
Property
Literal
Resource
Subject
object
Predicate
Personal web page of Terziyan V.
http//www.cs.jyu.fi/ai/vagan/index.html
Literal
has_birthday
15.02.2000
Birthday of the web-page
Birthday of Terziyan V.
has_birthday
27.12.1958
URI of Terziyan V.
http//www.cs.jyu.fi/ai/vagan/vagan
Dereferenceable URI (Hash vs. Slash)
51
Semantic Network of Web Resources
Personal web page of Terziyan V.
Web page of Agora Center
http//www.cs.jyu.fi/ai/vagan/index.html
http//www.jyu.fi/agora-center/indexEng.html
refers_to
isWebPageOf
isWebPageOf
27.12.1958
hasWebPage
has_birthday
hasWebPage
employed_by
URI of Terziyan V.
URI of Agora Center
http//www.cs.jyu.fi/ai/vagan/vagan
http//www.jyu.fi/agora-center/AC
52
From Hyperlinks to Semantic Web
http//www.kture.kharkov.ua/
http//www.cs.jyu.fi/ai/
university
international_contacts
http//www.cs.jyu.fi/ai/contacts.html
53
Resources and URIs
  • A resource can be anything that has identity
  • Uniform Resource Identifiers (URI) provide a
    simple and extensible means for identifying a
    resource
  • Not all resources are network "retrievable"
    e.g., human beings, corporations, and books in a
    library can also be considered resources

The term "Uniform Resource Locator" (URL)
refers to the subset of URI that identify
resources via a representation of their primary
access mechanism (e.g., their network
"location"), rather than identifying the resource
by name or by some other attribute(s) of that
resource.
54
URI
Venn diagram of Uniform Resource Identifier
(URI) scheme categories. Schemes in the URL
(locator) and URN (name) categories both function
as resource IDs, so URL and URN are subsets of
URI. They are also, generally, disjoint sets.
However, many schemes can't be categorized as
strictly one or the other, because all URIs can
be treated as names, and some schemes embody
aspects of both categories or neither.
55
Dereferenceable URI
The term Linked Data is used to describe a method
of exposing, sharing, and connecting data via
dereferenceable URIs on the Web. Linked Data is
about using the Web to connect related data that
wasnt previously linked, or using the Web to
lower the barriers to linking data currently
linked using other methods. More specifically,
Wikipedia defines Linked Data as a term used to
describe a recommended best practice for
exposing, sharing, and connecting pieces of data,
information, and knowledge on the Semantic Web
using URIs and RDF. Linked Data aims to extend
the Web with a data commons by publishing various
open datasets as RDF on the Web and by setting
RDF links between data items from different data
sources.
A dereferenceable Uniform Resource Identifier or
dereferenceable URI is a resource retrieval
mechanism that uses any of the internet protocols
(e.g. HTTP) to obtain a copy or representation of
the resource it identifies. In the context of
traditional HTML web pages, this is the normal
and obvious way of working A URI refers to the
page, and when requested the web server returns a
copy of it. In other non-dereferenceable
contexts, such as XML Schema, the namespace
identifier is still a URI, but this is simply an
identifier (i.e. a namespace name). There is no
intention that this can or should be
dereferenced. There is even a separate attribute,
schemaLocation, which may contain a
dereferenceable URI that does point to a copy of
the schema document. In the case of Linked Data,
the representation takes the form of a document
(typically HTML or XML) that describes the
resource that the URI identifies. In either case,
the mechanism makes it possible for a user (or
software agent) to "follow your nose" to find out
more information related to the identified
resource.
http//www.ted.com/talks/tim_berners_lee_on_the_ne
xt_web.html
56
RDF Statement
  • Subject of an RDF statement is a resource
  • Predicate of an RDF statement is a property of a
    resource
  • Object of an RDF statement is the value of a
    property of a resource

57
Example of RDF Statement
Ora Lassila is the creator of the resource
http//www.w3.org/Home/Lassila.
Subject (resource)
http//www.w3.org/Home/Lassila
Predicate (property)
Creator
Object (literal)
Ora Lassila
58
RDF Example (subject of statement)
Ora Lassila is the creator of the resource
http//www.w3.org/Home/Lassila.
Subject
ltrdfRDFgt ltrdfDescription about
"http//www.w3.org/Home/Lassila"gt
ltsCreatorgtOra Lassilalt/sCreatorgt
lt/rdfDescriptiongt lt/rdfRDFgt
59
RDF Example (predicate of statement)
Ora Lassila is the creator of the resource
http//www.w3.org/Home/Lassila.
ltrdfRDFgt ltrdfDescription about
"http//www.w3.org/Home/Lassila"gt
ltsCreatorgtOra Lassilalt/sCreatorgt
lt/rdfDescriptiongt lt/rdfRDFgt
Predicate
60
RDF Example (object of statement)
Ora Lassila is the creator of the resource
http//www.w3.org/Home/Lassila.
ltrdfRDFgt ltrdfDescription about
"http//www.w3.org/Home/Lassila"gt
ltsCreatorgtOra Lassilalt/sCreatorgt
lt/rdfDescriptiongt lt/rdfRDFgt
Object
61
RDF Example (reference to ontology)
Ora Lassila is the creator of the resource
http//www.w3.org/Home/Lassila.
ltrdfRDFgt ltrdfDescription about
"http//www.w3.org/Home/Lassila"gt
ltsCreatorgtOra Lassilalt/sCreatorgt
lt/rdfDescriptiongt lt/rdfRDFgt
a specific namespace prefix as reference to
ontology where predicates are defined, e.g.
xmlns s"http//description.org/schema/"
62
Full XML Document for the Example
Namespaces as attributes of RDF element in XML
lt?xml version"1.0"?gt ltrdfRDF xmlnsrdf"http//
www.w3.org/1999/02/22-rdf-syntax-ns xmlnss"ht
tp//description.org/schema/"gt ltrdfDescription
about "http//www.w3.org/Home/Lassila"gt
ltsCreatorgtOra Lassilalt/sCreatorgt
lt/rdfDescriptiongt lt/rdfRDFgt
63
XML Document for the Example with default
namespace syntax
lt?xml version"1.0"?gt ltRDF xmlnss"http//des
cription.org/ schema/"gt ltDescription
about "http//www.w3.org/Home/Lassila"gt
ltsCreatorgtOra Lassilalt/sCreatorgt
lt/Descriptiongt lt/RDFgt
64
RDF Abbreviated Syntax
  • While the serialisation syntax shows the
    structure of an RDF model most clearly, often it
    is desirable to use a more compact XML form.
  • The RDF abbreviated syntax accomplishes this.

65
RDF Abbreviated Syntax
2a description 'ltrdfDescription'
idAboutAttr? propAttr '/gt'
'ltrdfDescription' idAboutAttr?
propAttr 'gt'
propertyElt 'lt/rdfDescriptiongt'
typedNode 6a
propertyElt 'lt' propName 'gt' value 'lt/'
propName 'gt'
'lt' propName resourceAttr? propAttr '/gt' 16
propAttr propName '"' string '"'
(with embedded quotes
escaped) 17 typedNode 'lt' typeName
idAboutAttr? propAttr '/gt'
'lt' typeName idAboutAttr? propAttr
'gt'
property 'lt/' typeName 'gt'
66
Abbreviated Syntax Example (1)
Ora Lassila is the creator of the resource
http//www.w3.org/Home/Lassila.
ltrdfRDFgt ltrdfDescription about"http//www.w3
.org/Home/Lassila"
sCreator"Ora Lassila" /gt lt/rdfRDFgt
67
Abbreviated Syntax Example (2)
Ora Lassila is the creator of the resource
http//www.w3.org/Home/Lassila.
Subject
ltrdfDescription about"http//www.w3.org/Home/Las
sila"
sCreator"Ora Lassila" /gt
68
Abbreviated Syntax Example (3)
Ora Lassila is the creator of the resource
http//www.w3.org/Home/Lassila.
ltrdfDescription about"http//www.w3.org/Home/Las
sila" sCreator
"Ora Lassila" /gt
Predicate
69
Abbreviated Syntax Example (4)
Ora Lassila is the creator of the resource
http//www.w3.org/Home/Lassila.
ltrdfDescription about"http//www.w3.org/Home/Las
sila"
sCreator"Ora Lassila" /gt
Object
70
Serialisation vs. Abbreviated Syntax Example (1)
The individual referred to by employee id 85740
is named Ora Lassila and has the email address
lassila_at_w3.org. The resource http//www.w3.org/Hom
e/Lassila was created by this individual.
ltrdfRDFgt ltrdfDescription about"http//www.w
3.org/Home/Lassila"gt ltsCreatorgt
ltrdfDescription about"http//www.w3.org/staffId/
85740"gt ltvNamegtOra Lassilalt/vNamegt
ltvEmailgtlassila_at_w3.orglt/vEmailgt
lt/rdfDescriptiongt lt/sCreatorgt
lt/rdfDescriptiongt lt/rdfRDFgt
Serialisation syntax used
71
Serialisation vs. Abbreviated Syntax Example (2)
The individual referred to by employee id 85740
is named Ora Lassila and has the email address
lassila_at_w3.org. The resource http//www.w3.org/Hom
e/Lassila was created by this individual.
ltrdfRDFgt ltrdfDescription about"http//www.w
3.org/Home/Lassila"gt ltsCreator
rdfresource"http//www.w3.org/staffId/85740"
vName"Ora Lassila"
vEmail"lassila_at_w3.org" /gt
lt/rdfDescriptiongt lt/rdfRDFgt
Abbreviated syntax used
72
RDF N3 syntax
  • Notation3, or N3 as it is more commonly known, is
    a shorthand non-XML serialization of RDF models,
    designed with human-readability in mind N3 is
    much more compact and readable than XML RDF
    notation. The format is being developed by Tim
    Berners-Lee and others from the Semantic Web
    community.

RDF sample in XML notation
RDF sample in N3 notation
73
RDF N3 examples
  • Simple statement
  • John Loves Mary
  • Reified statement
  • John Loves Mary accordingTo Bill
  • Goal statement
  • gbI gbwant John Loves Mary
  • The prefix gb is used here to denote the
    ontology of S-APL.

74
Some N3 syntax specifics
75
Containers
  • Frequently it is necessary to refer to a
    collection of resources. RDF containers are used
    to hold such lists of resources or literals.
    There are three types of a container
  • bag
  • sequence
  • alternative

76
Containers. Bag.
  • An unordered list of resources or literals.
  • Bags are used to declare that a property has
    multiple values and that there is no significance
    to the order in which the values are given.
  • Bag might be used to give a list of part numbers
    where the order of processing the parts does not
    matter. Duplicate values are permitted.

77
Bag Example (1)
The students in course 6.001 are Amy, Tim, John,
Mary, and Sue
78
Bag Example (2)
The graph has eight nodes and seven arcs. The
first node is the resource /courses/6.001. An arc
labelled students connects this node to an
unnamed node. An arc labelled rdftype connects
the unnamed node to a node labelled rdfBag. Five
additional arcs labelled rdf_1, rdf_2, rdf_3,
rdf_4, and rdf_5 connect the unnamed node to
nodes labelled, respectively, /Students/Amy,
/Students/Tim, /Students/John, /Students/Mary,
and /Students/Sue. All the nodes are represented
as ovals.
79
Bag Example (3)
The students in course 6.001 are Amy, Tim, John,
Mary, and Sue
ltrdfRDFgt ltrdfDescription about"http//mycol
lege.edu/courses/6.001"gt ltsstudentsgt
ltrdfBaggt ltrdfli
resource"http//mycollege.edu/students/Amy"/gt
ltrdfli resource"http//mycollege.edu/s
tudents/Tim"/gt ltrdfli
resource"http//mycollege.edu/students/John"/gt
ltrdfli resource"http//mycollege.edu/
students/Mary"/gt ltrdfli
resource"http//mycollege.edu/students/Sue"/gt
lt/rdfBaggt lt/sstudentsgt
lt/rdfDescriptiongt lt/rdfRDFgt
80
Containers. Sequence.
  • An ordered list of resources or literals.
  • Sequence is used to declare that a property has
    multiple values and that the order of the values
    is significant.
  • Sequence might be used, for example, to preserve
    an alphabetical ordering of values.
  • Duplicate values are permitted.

81
Containers. Alternative.
  • A list of resources or literals that represent
    alternatives for the (single) value of a
    property.
  • An application using a property whose value is an
    Alternative collection is aware that it can
    choose any one of the items in the list as
    appropriate.

82
Alternative Example (1)
The source code for X11 may be found at
ftp.x.org, ftp.cs.purdue.edu, or ftp.eu.net
83
Alternative Example (2)
The graph has six nodes and five arcs. The first
node is the resource http//x.org/packages/X11.
An arc labelled DistributionSite connects this
node to an unnamed node. An arc labelled rdftype
connects the unnamed node to a node labelled
rdfAlt. Three additional arcs labelled rdf_1,
rdf_2, and rdf_3 connect the unnamed node to
nodes labelled, respectively, ftp.x.org,
ftp.cs.purdue.edu, and ftp.eu.net. All the nodes
are represented as ovals
84
Alternative Example (3)
The source code for X11 may be found at
ftp.x.org, ftp.cs.purdue.edu, or ftp.eu.net
ltrdfRDFgt ltrdfDescription about"http//x.org
/packages/X11"gt ltsDistributionSitegt
ltrdfAltgt ltrdfli resource"ftp//ftp.x
.org"/gt ltrdfli resource"ftp//ftp.cs.p
urdue.edu"/gt ltrdfli resource"ftp//ftp
.eu.net"/gt lt/rdfAltgt
lt/sDistributionSitegt lt/rdfDescriptiongt
lt/rdfRDFgt
85
Containers vs. Repeated Properties (1)
Sue has written "Anthology of Time", "Zoological
Reasoning", "Gravitational Reflections".
There is no stated relationship between the
publications other than that they were written
by the same person
86
Containers vs. Repeated Properties (2)
The committee of Fred, Wilma, and Dino approved
the resolution.
three committee members as a whole voted in a
certain manner it does not necessarily state
that each committee member voted in favour of
the resolution.
87
Statements about Statements (1)
  • For example, let us consider the sentence
  • Ora Lassila is the creator of the resource
    http//www.w3.org/Home/Lassila.
  • RDF would regard this sentence as a fact. If,
    instead, we write the sentence
  • Ralph Swick says that Ora Lassila is the creator
    of the resource http//www.w3.org/Home/Lassila
  • we have said nothing about the resource
    http//www.w3.org/Home/Lassila instead, we have
    expressed a fact about a statement Ralph has made.

88
Statements about Statements (2)
  • To model statements RDF defines the following
    properties
  • subject
  • The subject property identifies the resource
    being described by the modelled statement that
    is, the value of the subject property is the
    resource about which the original statement was
    made (e.g., http//www.w3.org/Home/Lassila).
  • predicate
  • The predicate property identifies the original
    property in the modelled statement. The value of
    the predicate property is a resource representing
    the specific property in the original statement
    (in our example, creator).
  • object
  • The object property identifies the property value
    in the modelled statement. The value of the
    object property is the object in the original
    statement (in our example, "Ora Lassila").
  • type
  • The value of the type property describes the type
    of the new resource. All reified statements are
    instances of RDFStatement that is, they have a
    type property whose object is RDFStatement.

89
Statements about Statements (3)
Ralph Swick says that Ora Lassila is the creator
of the resource http//www.w3.org/Home/Lassila
90
Statements about Statements (4)
An unnamed node is the source of all five arcs.
The first arc is labelled rdftype and points to
the node identified as rdfStatement. The second
arc is labelled rdfpredicate and points to the
node identified as sCreator. The third arc is
labelled rdfsubject and points to a node
labelled http//www.w3.org/Home/Lassila. The
fourth arc is labelled rdfobject and points to a
node containing the string value "Ora Lassila".
The fifth and final arc is labelled
aattributedTo and points to a node containing
the string value "Ralph Swick".
91
Statements about Statements (5)
Ralph Swick says that Ora Lassila is the creator
of the resource http//www.w3.org/Home/Lassila
ltrdfRDF xmlnsrdf"http//w3.org/TR/1999/PR-r
df-syntax-19990105" xmlnsa"http//descripti
on.org/schema/"gt ltrdfDescriptiongt
ltrdfsubject resource"http//www.w3.org/Home/Lass
ila" /gt ltrdfpredicate resource"http//desc
ription.org/schemaCreator" /gt
ltrdfobjectgtOra Lassilalt/rdfobjectgt
ltrdftype resource"http//w3.org/TR/1999/PR-rdf-s
yntax-
19990105Statement"
/gt ltaattributedTogtRalph
Swicklt/aattributedTogt lt/rdfDescriptiongt
lt/rdfRDFgt
92
Statements about containers
ltrdfDescription about"http//www.cs.jyu.fi/vag
an/courses/ITKS544"gt ltslecturesgt
ltrdfBag ID"pages"gt ltrdfli
rdfresource" http//www.cs.jyu.fi/vagan/courses/
ITKS544/Lecture_1.ppt"gt ltrdfli
rdfresource" http//www.cs.jyu.fi/vagan/courses/
ITKS544/Lecture_2.ppt"gt
ltrdfli rdfresource"
http//www.cs.jyu.fi/vagan/courses/ITKS544/Lecture
_8.ppt"gt lt/rdfBaggt
lt/slecturesgt lt/rdfDescriptiongt ltrdfDescription
about"pages"gt ltdccreatorgt Vagan
Terziyan lt/dccreatorgt lt/rdfDescriptiongt
93
Sharing Values between Sequences (1)
Consider the case of specifying 3 collected works
of an author, sorted once by publication date and
sorted again alphabetically by subject.
94
Sharing Values between Sequences (2)
ltRDF xmlns"http//w3.org/TR/1999/PR-rdf-syntax-19
990105"gt ltSeq ID"JSPapersByDate"gt
ltli resource"http//www.dogworld.com/Aug96.doc"/gt
ltli resource"http//www.webnuts.net/Jan97
.html"/gt ltli resource"http//www.carchat.c
om/Sept97.html"/gt lt/Seqgt ltSeq
ID"JSPapersBySubj"gt ltli
resource"http//www.carchat.com/Sept97.html"/gt
ltli resource"http//www.dogworld.com/Aug96.d
oc"/gt ltli resource"http//www.webnuts.net/
Jan97.html"/gt lt/Seqgt lt/RDFgt
95
Ternary Relation (1)
John Smiths weight is 200 pounds
96
Ternary Relation (2)
John Smiths weight is 200 pounds
ltRDF xmlns"http//w3.org/TR/1999/PR-rdf-synta
x-19990105" xmlnsrdf"http//w3.org/TR/1999/
PR-rdf-syntax-19990105" xmlnsn"http//www.n
ist.gov/units/"gt ltDescription
about"John_Smith"gt ltnweight
rdfparseType"Resource"gt
ltrdfvaluegt200lt/rdfvaluegt ltnunits
rdfresource"http//www.nist.gov/units/Pounds"/gt
lt/nweightgt lt/Descriptiongt lt/RDFgt
97
Statements about Statements (1)
Ralph Swick says that Ora Lassila is the creator
of the resource http//www.w3.org/Home/Lassila
An unnamed node is the source of all five arcs.
The first arc is labelled rdftype and points to
the node identified as rdfStatement. The second
arc is labelled rdfpredicate and points to the
node identified as sCreator. The third arc is
labelled rdfsubject and points to a node
labelled http//www.w3.org/Home/Lassila. The
fourth arc is labelled rdfobject and points to a
node containing the string value "Ora Lassila".
The fifth and final arc is labelled
aattributedTo and points to a node containing
the string value "Ralph Swick".
98
Statements about Statements (2)
Ralph Swick says that Ora Lassila is the creator
of the resource http//www.w3.org/Home/Lassila
ltrdfRDF xmlnsrdf"http//w3.org/TR/1999/PR-r
df-syntax-19990105" xmlnsa"http//descripti
on.org/schema/"gt ltrdfDescriptiongt
ltrdfsubject resource"http//www.w3.org/Home/Lass
ila" /gt ltrdfpredicate resource"http//desc
ription.org/schemaCreator" /gt
ltrdfobjectgtOra Lassilalt/rdfobjectgt
ltrdftype resource"http//w3.org/TR/1999/PR-rdf-s
yntax-
19990105Statement"
/gt ltaattributedTogtRalph
Swicklt/aattributedTogt lt/rdfDescriptiongt
lt/rdfRDFgt
99
What is RDFS ?
  • RDF Schema
  • Defines vocabulary for RDF
  • Organizes this vocabulary in a typed hierarchy
    (Class, subClassOf, type, Property,
    subPropertyOf)
  • Rich, web-based publication format for declaring
    semantics (XML for exchange)
  • Capability to explicitly declare semantic
    relations between vocabulary terms

100
RDF Schema
  • Semantic network on the Web
  • Nodes are identified by URIs
  • rdfsClass
  • rdfsProperty
  • rdfssubClassOf

101
Class Hierarchy of the RDFS
Class hierarchy is shown using a "nodes and arcs"
graph representation of the RDF data model. If
one class is a subset of another, then there is
an rdfssubClassOf arc from the node representing
the first class to the node representing the
second.
If a resource is an instance of a class, then
there is an rdftype arc from the resource to the
node representing the class.
102
Example (1)
Example expresses the following class hierarchy.
We first define a class MotorVehicle. We then
define three subclasses of MotorVehicle, namely
PassengerVehicle, Truck and Van. We then define a
class Minivan which is a subclass of both Van and
PassengerVehicle.
103
Example (2)
ltrdfRDF xmllang"en"
xmlnsrdf"http//www.w3.org/1999/02/22-rdf-syntax
-ns" xmlnsrdfs"http//www.w3.o
rg/2000/01/rdf-schema"gt lt!-- Note this
RDF schema would typically be used in RDF
instance data by referencing it with
an XML namespace declaration, for example
xmlnsxyz"http//www.w3.org/2000/03/example/
vehicles". This allows us to use
abbreviations such as xyzMotorVehicle to refer
unambiguously to the RDF class
'MotorVehicle'. --gt ltrdfDescription
ID"MotorVehicle"gt ltrdftype
resource"http//www.w3.org/2000/01/rdf-schemaCla
ss"/gt ltrdfssubClassOf
rdfresource"http//www.w3
.org/2000/01/rdf-schemaResource"/gt
lt/rdfDescriptiongt ...
104
Example (3)
ltrdfDescription ID"PassengerVehicle"gt
ltrdftype resource"http//www.w3.o
rg/2000/01/rdf-schemaClass"/gt
ltrdfssubClassOf rdfresource"MotorVehicle"/gt
lt/rdfDescriptiongt ltrdfDescription
ID"Truck"gt ltrdftype
resource"http//www.w3.org/2000/01/rdf-schemaCla
ss"/gt ltrdfssubClassOf
rdfresource"MotorVehicle"/gt
lt/rdfDescriptiongt ...
105
Example (4)
ltrdfDescription ID"Van"gt
ltrdftype resource"http//www.w3.org/2000/01/rdf
-schemaClass"/gt ltrdfssubClassOf
rdfresource"MotorVehicle"/gt
lt/rdfDescriptiongt ltrdfDescription
ID"MiniVan"gt ltrdftype
resource"http//www.w3.org/2000/01/rdf-schemaCla
ss"/gt ltrdfssubClassOf
rdfresource"Van"/gt
ltrdfssubClassOf rdfresource"PassengerVehicle"/
gt lt/rdfDescriptiongt lt/rdfRDFgt
106
Dublin Core
  • A set of fifteen basic properties for describing
    generalised Web resources
  • ISO Standard 15836-2003 (February 2003)
    http//www.niso.org/international/SC4/n515.pdf

The Dublin Core Metadata Initiative is an open
forum engaged in the development of interoperable
online metadata standards that support a broad
range of purposes and business models.
http//dublincore.org/
107
Dublin Core (15 basic properties)
  • Type
  • Format
  • Identifier
  • Source
  • Language
  • Relation
  • Coverage
  • Rights
  • Title
  • Creator
  • Subject
  • Description
  • Publisher
  • Contributor
  • Date

108
Dublin Core Example
lt?xml version"1.0"?gt ltrdfRDF
xmlnsrdfhttp//www.w3.org/1999/02/22-rdf-syntax
-ns xmlnsdc"http//purl.org/dc/element
s/1.0/"gt ltrdfDescription rdfabout"http//w
ww.ukoln.ac.uk/metadata/resources/dc/

datamodel/WD-dc-rdf/"gt ltdctitlegt
Guidance on expressing the Dublin Core within the
Resource Description
Framework (RDF) lt/dctitlegt
ltdccreatorgt Eric Miller lt/dccreatorgt
ltdccreatorgt Paul Miller lt/dccreatorgt
ltdccreatorgt Dan Brickley lt/dccreatorgt
ltdcsubjectgt Dublin Core Resource Description
Framework RDF eXtensible
Markup Language XML lt/dcsubjectgt
ltdcpublishergt Dublin Core Metadata
Initiative lt/dcpublishergt
ltdccontributorgt Dublin Core Data Model Working
Group lt/dccontributorgt ltdcdategt
1999-07-01 lt/dcdategt ltdcformatgt
text/html lt/dcformatgt ltdclanguagegt en
lt/dclanguagegt lt/rdfDescriptiongt lt/rdfRDFgt

109
Where to look next
  • RDF http//www.w3.org/RDF/
  • RDF Schema http//www.w3.org/TR/rdf-schema/

110
Traditional RDF Statement
  • Subject of an RDF statement is a resource
  • Predicate of an RDF statement is a property of a
    resource
  • Object of an RDF statement is the value of a
    property of a resource (either literal or
    resource)

Property_k
Resource_i
Literal
OR
Property_r
Resource_i
Resource_ j
111
New semantics of RDF Statement in S-APL (object -
executable resource)
Property_m
exe Resource_ j
Resource_i
Semantics of such statement means that the value
of the Property_m of the Resource_i can be
obtained as a result of execution of the
procedure (query, service, function, etc.)
represented as Resource_ j
executable resource
Semantic Agent Programming Language (Designed by
Industrial Ontologies Group)
112
Ontological Vision of Semantic Web
  • Semantic Web needs ontologies
  • An ontology is
  • document or file that formally and in a
    standardized way defines the hierarchy of classes
    within the domain, semantic relations among terms
    and inference rules
  • Use of ontologies
  • Sharing semantics of your data across distributed
    applications

113
Ontologies the foundation of Semantic Web
Ontologies are key enabling technology for the
Semantic Web ..explicit specification of
conceptualization.. Ontology is formal and rich
way to provide shared and common understanding of
a domain, that can be used by people and machines
comment
__Thing__
Author
public
private
is-a
Location
Access Rights
Document
Related to
name
Report
is-a
is-a
uri
Web-page
Subject
Instance-of
Instance-of
O. Kononenko
V. Terziyan
public
Author
Author
Access rights
doc1
doc2
name
Related to
Semantic Web
uri
Location
Subject
comment
http//www.ontogroup.net
\\AgServ\vagan\InBCT_1.doc
comment
3.1 analysis
Home page
draft
Query 1 get all documents from location X, but
not web-pages Query 2 get documents related to
Y, with more then one author, one of which is
Terziyan Query 3 are there web-pages of Z with
private access related to documents with
subject S?
114
Semantic Web Interoperability
Common (shared) ontology
System 2
System 1
A commitment to a common ontology is a guarantee
of a consistency and thus possibility of data
(and knowledge) sharing
115
Query Today
WWW Hotbot
What is Al Qaeda?
The answer may be somewhere in this list of URLs
116
Semantic Query
What is Al Qaeda?
A terrorist organization Would you like
additional information on?
  • Membership
  • Locations
  • Structure
  • Finances
  • Tactics
  • Other terrorist organizations

117
Example Ontology
These ontologies accessed at remote locations
118
RDF-Based Inference
ltdamlClass rdfIDBin Laden"gt
ltrdfssubClassOf rdfresource"terrorist"/gt lt/dam
lClassgt
Implies
  • If x is Bin Laden, he must be a terrorist
  • If x is a terrorist, then he may or may not be
    Bin Laden
  • If x is not a terrorist, then he is not Bin Laden
  • If x is not Bin Laden, he may or may not be a
    terrorist

119
Communication between people
120
What is an ontology?
Studer(98) Formal, explicit specification of a
shared conceptualization
121
What is an Ontology?
From Ian Horrocks OWL 2 The Next Generation
122
What is an Ontology?
From Ian Horrocks OWL 2 The Next Generation
  • A model of (some aspect of) the world

123
What is an Ontology?
From Ian Horrocks OWL 2 The Next Generation
  • A model of (some aspect of) the world
  • Introduces vocabulary relevant to domain, e.g.
  • Anatomy

124
What is an Ontology?
From Ian Horrocks OWL 2 The Next Generation
  • A model of (some aspect of) the world
  • Introduces vocabulary relevant to domain, e.g.
  • Anatomy
  • Cellular biology

125
What is an Ontology?
From Ian Horrocks OWL 2 The Next Generation
  • A model of (some aspect of) the world
  • Introduces vocabulary relevant to domain, e.g.
  • Anatomy
  • Cellular biology
  • Aerospace

126
What is an Ontology?
From Ian Horrocks OWL 2 The Next Generation
  • A model of (some aspect of) the world
  • Introduces vocabulary relevant to domain, e.g.
  • Anatomy
  • Cellular biology
  • Aerospace
  • Dogs

127
What is an Ontology?
From Ian Horrocks OWL 2 The Next Generation
  • A model of (some aspect of) the world
  • Introduces vocabulary relevant to domain, e.g.
  • Anatomy
  • Cellular biology
  • Aerospace
  • Dogs
  • Hotdogs

128
What is an Ontology?
From Ian Horrocks OWL 2 The Next Generation
  • A model of (some aspect of) the world
  • Introduces vocabulary relevant to domain
  • Specifies meaning of terms
  • Heart is a muscular organ that is part of the
    circulatory system

129
What is an Ontology?
From Ian Horrocks OWL 2 The Next Generation
  • A model of (some aspect of) the world
  • Introduces vocabulary relevant to domain
  • Specifies meaning of terms
  • Heart is a muscular organ that is part of the
    circulatory system
  • Formalised using suitable logic

130
DL Semantics
From Ian Horrocks OWL A Description Logic
Based Ontology Language
  • Semantics given by standard FO model theory

Interpretation domain ?I
Interpretation function I
Individuals iI 2 ?I John Mary Concepts CI µ
?I Lawyer Doctor Vehicle Roles rI µ ?I
?I hasChild owns
Individual Resources
Classes of Resources
Properties of Resources
(Lawyer u Doctor)
131
Benefits
Knowledge sharing and reuse
Building an ontology is not a goal in itself.
132
Ontology Elements
  • Concepts(classes) their hierarchy
  • Concept properties (slots/attributes)
  • Property restrictions (type, cardinality, domain)
  • Relations between concepts (disjoint, equality)
  • Instances

133
How to build an ontology?
  • Steps
  • determine domain and scope
  • enumerate important terms
  • define classes and class hierarchies
  • define slots
  • define slot restrictions (cardinality,
    value-type)

134
Step 1 Determine Domain and Scope
Application route planning agent
Possible questions Distance between two
cities? What sort of connections exist between
two cities? In which country is a city? How many
borders are crossed?
135
Step 2 Enumerate Important Terms
136
Step 3 Define Classes and Class Hierarchy
137
Step 4 Define Slots of Classes
Step 5 Define slot constraints
  • Slot-cardinality
  • Ex Borders_with multiple, Start_point single
  • Slot-value type
  • Ex Borders_with- Country

138
OWL became standard
  • 10 February 2004 the World Wide Web Consortium
    announced final approval of two key Semantic Web
    technologies, the revised Resource Description
    Framework (RDF) and the Web Ontology Language
    (OWL).
  • Read more in
  • http//www.w3.org/2004/01/sws-pressrelease.html.en

139
OWL Introduction
  • What is OWL?
  • OWL is a language for defining Web Ontologies and
    their associated Knowledge Bases
  • The OWL language is a revision of the DAMLOIL
    web ontology language incorporating learning from
    the design and application use of DAMLOIL.

140
Example
  • There are two types of animals, Male and Female.
  • ltrdfsClass rdfID"Male"gt
  • ltrdfssubClassOf rdfresource"Animal"/gt
  • lt/rdfsClassgt
  • The subClassOf element asserts that its subject -
    Male - is a subclass of its object -- the
    resource identified by Animal.
  • ltrdfsClass rdfID"Female"gt
  • ltrdfssubClassOf rdfresource"Animal"/gt
  • ltowldisjointWith rdfresource"Male"/gt
  • lt/rdfsClassgt
  • Some animals are Female, too, but nothing can be
    both Male and Female (in this ontology) because
    these two classes are disjoint (using the
    disjointWith tag).

141
OWL Example in Protégé (1)
  • Class
  • Person superclass
  • Man, Woman subclasses
  • Properties
  • isWifeOf, isHusbandOf
  • Property characteristics, restrictions
  • inverseOf
  • domain
  • range
  • Cardinality
  • Class expressions
  • disjointWith

142
OWL Example in Protégé (2)
143
OWL Example in Protégé (3)
144
OWL on one Slide
  • Symmetric if P(x, y) then P(y, x)
  • Transitive if P(x,y) and P(y,z) then P(x, z)
  • Functional if P(x,y) and P(x,z) then yz
  • InverseOf if P1(x,y) then P2(y,x)
  • InverseFunctional if P(y,x) and P(z,x) then yz
  • allValuesFrom P(x,y) and yallValuesFrom(C)
  • someValuesFrom P(x,y) and ysomeValuesFrom(C)
  • hasValue P(x,y) and yhasValue(v)
  • cardinality cardinality(P) N
  • minCardinality minCardinality(P) N
  • maxCardinality maxCardinality(P) N
  • equivalentProperty P1 P2
  • intersectionOf C intersectionOf(C1, C2, )
  • unionOf C unionOf(C1, C2, )
  • complementOf C complementOf(C1)
  • oneOf C one of(v1, v2, )
  • equivalentClass C1 C2
  • disjointWith C1 ! C2
  • sameIndividualAs I1 I2

Legend Properties are indicated by P, P1, P2,
etc Specific classes are indicated by x, y,
z Generic classes are indicated by C, C1,
C2 Values are indicated by v, v1, v2 Instance
documents are indicated by I1, I2, I3, etc. A
number is indicated by N P(x,y) is read as
property P relates x to y
145
An Example
  • Woman Person ? Female
  • Man Person ? ?Woman
  • Mother Woman ? ?hasChild.Person
  • Father Man ? ?hasChild.Person
  • Parent Father ? Mother
  • Grandmother Mother ? ?hasChild.Parent
  • We can further infer (though not explicitly
    stated)
  • ? Grandmother ? Person
  • Grandmother ? Man ? Woman
  • etc.

146
Resources
  • W3C Documents
  • Guide http//www.w3.org/TR/owl-guide/
  • Reference http//www.w3.org/TR/owl-ref/
  • Semantics and Abstract Syntax http//www.w3.org/T
    R/owl-semantics/
  • OWL Tutorials
  • Ian Horrocks, Sean Bechhofer http//www.cs.man.ac
    .uk/horrocks/Slides/Innsbruck-tutorial/
  • Roger L. Costello, David B. Jacobs
    http//www.xfront.com/owl/
  • Example Ontologies, e.g. here
  • http//www.daml.org/ontologies/

147
Tutorial Designing Ontologies with Protégé
PLEASE !!! Download version Protégé 3.4.4.
  • Protégé is an ontology editor and a
    knowledge-base editor (download from
    http//protege.stanford.edu ).
  • Protégé is also an open-source, Java tool that
    provides an extensible architecture for the
    creation of customized knowledge-based
    applications.
  • Protégé's OWL Plug-in now provides support for
    editing Semantic Web ontologies.

http//www.cs.jyu.fi/ai/vagan/Ontologies.ppt
http//www.cs.man.ac.uk/horrocks/Teaching/cs646/
http//www.co-ode.org/resources/tutorials/ProtegeO
WLTutorial.pdf
148
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
149
Rules on top of Semantic Web (Metasemantics)
Metasemantics
Production Rules
Temporal Rules
Semantic Rules
Semantic Web
150
State of a Semantic Net
151
Production Rules
152
Production-Based Reasoning
State after n transformations
Initial state
S(t0nt)
S(t0)
Set of Production Rules
153
Example (not formalised rules)
1. Mary will love John if he loves her and if he
is not abusing Pete. 2. Pete will consider Mary
as his friend if she is not in love with John. 3.
Pete will not consider Mary as his friend if she
is in love with John who is abusing him. 4. John
will stop loving Mary if she does not love him or
she is a friend of Pete. 5. Mary will stop loving
John if he is abusing Pete. 6. John being in bad
mood will abuse Pete. 7. John gets rid of bad
mood if Mary loves him or if she is not a friend
of Pete. 8. John will fall in a bad mood if he
loves Mary and she does not love him or vice
versa. 9. John will stop abusing Pete if he
(John) does not love Mary any more or if she is
not a friend of Pete.
154
Example (names of objects and relations)
Names of objects A1 John A2 Mary A3 Pete
Names of relations (or properties) L1 to
love L2 to have a friend L3 to abuse L4 to
have a bad mood
155
Example (relations and properties)
P1 P(A1, L1, A2) - John loves Mary P2
P(A2, L1, A1) - Mary loves John P3 P(A3,
L2, A2) - Pete has a friend Mary P4
P(A1, L3, A3) - John is abusing Pete P5
P(A1, L4, A1) - John has a bad mood.
156
Example (initial state)
1. John loves Mary. 2. Mary does not love
John. 3. Mary is a friend of Pete. 4. John is not
abusing Pete. 5. John is not in a bad mood.
157
Example (formalised rules)
1. Mary will love John if he loves her and if he
is not abusing Pete. 2. Pete will consider Mary
as his friend if she is not in love with John. 3.
Pete will not consider Mary as his friend if she
is in love with John who is abusing him. 4. John
will stop loving Mary if she does not love him or
she is a friend of Pete. 5. Mary will stop loving
John if he is abusing Pete. 6. John being in bad
mood will abuse Pete. 7. John gets rid of bad
mood if Mary loves him or if she is not a friend
of Pete. 8. John will fall in a bad mood if he
loves Mary and she does not love him or vice
versa. 9. John will stop abusing Pete if he
(John) does not love Mary any more or if she is
not a friend of Pete.
P1 P(A1, L1, A2) - John loves Mary P2
P(A2, L1, A1) - Mary loves John P3 P(A3,
L2, A2) - Pete has a friend Mary P4
P(A1, L3, A3) - John is abusing Pete P5
P(A1, L4, A1) - John has a bad mood.
158
Example (reasoning, 1-st step)
to love
John
Mary
to have a friend
Pete
159
Example (reasoning, 2-nd step)
to love
John
Mary
to have a friend
to have a bad mood
Pete
160
Example (reasoning, 3-rd step)
to love
John
Mary
to abuse
to have a friend
Pete
161
Example (reasoning, 4-th step)
John
Mary
to have a bad mood
Pete
162
Example (reasoning, 5-th step)
John
Mary
to abuse
to have a friend
Pete
163
Example (reasoning, reaching terminal state)
John
Mary
to have a friend
Pete
terminal state
164
Example (final terminal state)
1. John does not love Mary. 2. Mary does not
love John. 3. Mary is a friend of Pete. 4. John
is not abusing Pete. 5. John is not in a bad mood.
165
Example (another initial and in the same time
terminal state)
to love
John
Mary
1. John loves Mary. 2. Mary loves John. 3. Mary
is not a friend of Pete. 4. John is not abusing
Pete. 5. John is not in a bad mood.
to love
Pete
terminal state
166
Example (two possible terminal states of the
love triangle)
to love
John
Mary
to love
Pete
Mary
John
to have a friend
Pete
167
Example (asynchronous reasoning tree)
R1
R8
R4
R1
R4
R4
R6
R4
R6
R4
R8
R9
R6
R9
R5
R8
R7
R3
R9
R5
R3
R9
R5
R7
R8
R9
R6
R7
R9
R2
R9
R7
R5
R8
R6
R2
R9
R2
R7
R2
168
Temporal Rules
  • Lifetime of a relation
  • Restoration time of a relation

169
Lifetime of a Relation
Lifetime of relation Lk, which means that since
appearance in the network this relation is valid
T units of time
170
Example (Initial state of the network)
171
Example (Network evolution)
172
Restoration Time of a Relation
Restoration (relaxation) time of relation Lk,
which means that since removal from the network
this relation will be restored and become valid
again after T units of time

173
Example
174
Example (Network evolution)
t t0
t t0 t
t t0 2t
t t0 3t
175
Semantic Pendulum (Cyclic)
176
Cyclic Pendulum Example
t t0
t t0 2t
t t0 5t
t t0 7t
177
Semantic Pendulum (Semaphore)
178
Semantic Semaphore Example
t t0
t t0 t
t t0 5t
t t0 11t
t t0 10t
t t0 6t
179
Semantic Rules in SWRL
180
Metasemantic Networks
181
A Metasemantic Network
Metasemantic Network (Semantic Metanetwork) is
considered formally as the set of semantic
networks, which are put on each other in such a
way that links of every previous semantic network
are in the same time nodes of the next network
182
An Example of a Semantic Metanetwork
183
How it Works
  • In a Semantic Metanetwork every higher level
    controls semantic structure of the lower level.
  • Simple controlling rules might be, for example,
    in which contexts certain link of a semantic
    structure can exist and in which context it
    should be deleted from the semantic structure.
  • Such multilevel network can be used in an
    adaptive control system which structure is
    automatically changed following changes in a
    context of the environment.
  • The algebra for reasoning with a semantic
    metanetwork is also developed.

184
Published and Further Developed in
Terziyan V., Multilevel Models for Knowledge
Bases Control and Their Applications to Automated
Information Systems, Doctor of Technical Sciences
Degree Thesis, Kharkov State Technical University
of Radioelectronics, 1993.
Terziyan V., Puuronen S., Reasoning with
Multilevel Contexts in Semantic Metanetworks, In
P. Bonzon, M. Cavalcanti, R. Nossun (Eds.),
Formal Aspects in Context, Kluwer Academic
Publishers, 2000, pp. 107-126.
185
Metasemantic Algebra of Contexts
186
Metasemantic Algebra A Semantic Predicate
Semantic predicate describes a piece of knowl
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