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Internet Engineering Course

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The Semantic Web will gradually evolve out of the existing Web, it is not a competition to the current WWW. Semantic Web Outline. Today s Web. The Semantic Web Impact. – PowerPoint PPT presentation

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Title: Internet Engineering Course


1
Internet Engineering Course
  • Semantic Web,
  • Web Services,
  • Semantic Web Services

2
Agenda
  • Vision of Next Generation Web Technology
  • Semantic Web
  • Todays Web
  • The Semantic Web Impact
  • Semantic Web Technologies
  • A Layered Approach
  • Web Services
  • Why Web Services?
  • Enabling Technologies
  • Web Service Composition
  • Main Issues concerning the composition
  • Semantic Web Services

3
Vision of Next Generation Web Technologies
  • 500 million users
  • more than 3 billion pages

WWW URI, HTML, HTTP
Static
3
4
Vision of Next Generation Web Technologies
  • Serious Problems in
  • information finding,
  • information extracting,
  • information representing,
  • information interpreting and
  • and information maintaining.

WWW URI, HTML, HTTP
Semantic Web RDF, RDF(S), OWL
Static
4
5
Vision of Next Generation Web Technologies
Web Services UDDI, WSDL, SOAP
Dynamic
  • Bringing the computer back as a device for
    computation

WWW URI, HTML, HTTP
Semantic Web RDF, RDF(S), OWL
Static
5
6
Vision of Next Generation Web Technologies
  • Bringing the web to its full potential

Semantic Web Services
Web Services UDDI, WSDL, SOAP
Dynamic
WWW URI, HTML, HTTP
Semantic Web RDF, RDF(S), OWL
Static
6
7
Semantic Web
8
Semantic Web Outline
  1. Todays Web
  2. The Semantic Web Impact
  3. Semantic Web Technologies
  4. A Layered Approach

9
Todays Web
  • Most of todays Web content is suitable for human
    consumption
  • Even Web content that is generated automatically
    from databases is usually presented without the
    original structural information found in
    databases
  • Typical Web uses today peoples
  • seeking and making use of information, searching
    for and getting in touch with other people,
    reviewing catalogues of online stores and
    ordering products by filling out forms

10
Keyword-Based Search Engines
  • Current Web activities are not particularly well
    supported by software tools
  • Except for keyword-based search engines (e.g.
    Google, AltaVista, Yahoo)
  • The Web would not have been the huge success it
    was, were it not for search engines

11
Problems of Keyword-Based Search Engines
  • High recall, low precision.
  • Low or no recall
  • Results are highly sensitive to vocabulary
  • Results are single Web pages
  • Human involvement is necessary to interpret and
    combine results
  • Results of Web searches are not readily
    accessible by other software tools

12
The Key Problem of Todays Web
  • The meaning of Web content is not
    machine-accessible lack of semantics
  • It is simply difficult to distinguish the meaning
    between these two sentences
  • I am a professor of computer science.
  • I am a professor of computer science,
  • you may think. Well, . . .

13
The Semantic Web Approach
  • Represent Web content in a form that is more
    easily machine-processable.
  • Use intelligent techniques to take advantage of
    these representations.
  • The Semantic Web will gradually evolve out of the
    existing Web, it is not a competition to the
    current WWW

14
Semantic Web Outline
  1. Todays Web
  2. The Semantic Web Impact
  3. Semantic Web Technologies
  4. A Layered Approach

15
The Semantic Web Impact Knowledge Management
  • Knowledge management concerns itself with
    acquiring, accessing, and maintaining knowledge
    within an organization
  • Key activity of large businesses internal
    knowledge as an intellectual asset
  • It is particularly important for international,
    geographically dispersed organizations
  • Most information is currently available in a
    weakly structured form (e.g. text, audio, video)

16
Limitations of Current Knowledge Management
Technologies
  • Searching information
  • Keyword-based search engines
  • Extracting information
  • human involvement necessary for browsing,
    retrieving, interpreting, combining
  • Maintaining information
  • inconsistencies in terminology, outdated
    information.
  • Viewing information
  • Impossible to define views on Web knowledge

17
Semantic Web Enabled Knowledge Management
  • Knowledge will be organized in conceptual spaces
    according to its meaning.
  • Automated tools for maintenance and knowledge
    discovery
  • Semantic query answering
  • Query answering over several documents
  • Defining who may view certain parts of
    information (even parts of documents) will be
    possible.

18
The Semantic Web Impact B2C Electronic
Commmerce
  • A typical scenario user visits one or several
    online shops, browses their offers, selects and
    orders products.
  • Ideally humans would visit all, or all major
    online stores but too time consuming
  • Shopbots are a useful tool

19
Limitations of Shopbots
  • They rely on wrappers extensive programming
    required
  • Wrappers need to be reprogrammed when an online
    store changes its outfit
  • Wrappers extract information based on textual
    analysis
  • Error-prone
  • Limited information extracted

20
Semantic Web Enabled B2C Electronic Commerce
  • Software agents that can interpret the product
    information and the terms of service.
  • Pricing and product information, delivery and
    privacy policies will be interpreted and compared
    to the user requirements.
  • Information about the reputation of shops
  • Sophisticated shopping agents will be able to
    conduct automated negotiations

21
The Semantic Web Impact B2B Electronic Commerce
  • Greatest economic promise
  • Currently relies mostly on EDI
  • Isolated technology, understood only by experts
  • Difficult to program and maintain, error-prone
  • Each B2B communication requires separate
    programming
  • Web appears to be perfect infrastructure
  • But B2B not well supported by Web standards

22
Semantic Web Enabled B2B Electronic Commerce
  • Businesses enter partnerships without much
    overhead
  • Differences in terminology will be resolved using
    standard abstract domain models
  • Data will be interchanged using translation
    services.
  • Auctioning, negotiations, and drafting contracts
    will be carried out automatically (or
    semi-automatically) by software agents

23
Semantic Web Outline
  1. Todays Web
  2. The Semantic Web Impact
  3. Semantic Web Technologies
  4. A Layered Approach

24
Semantic Web Technologies
  • Explicit Metadata
  • Ontologies
  • Logic and Inference
  • Agents

25
On HTML
  • Web content is currently formatted for human
    readers rather than programs
  • HTML is the predominant language in which Web
    pages are written (directly or using tools)
  • Vocabulary describes presentation

26
An HTML Example
  • lth1gtAgilitas Physiotherapy Centrelt/h1gt
  • Welcome to the home page of the Agilitas
    Physiotherapy Centre. Do
  • you feel pain? Have you had an injury? Let our
    staff Lisa Davenport,
  • Kelly Townsend (our lovely secretary) and Steve
    Matthews take care
  • of your body and soul.
  • lth2gtConsultation hourslt/h2gt
  • Mon 11am - 7pmltbrgt
  • Tue 11am - 7pmltbrgt
  • Wed 3pm - 7pmltbrgt
  • Thu 11am - 7pmltbrgt
  • Fri 11am - 3pmltpgt
  • But note that we do not offer consultation during
    the weeks of the
  • lta href". . ."gtState Of Originlt/agt games.

27
Problems with HTML
  • Humans have no problem with this
  • Machines (software agents) do
  • How distinguish therapists from the secretary,
  • How determine exact consultation hours
  • They would have to follow the link to the State
    Of Origin games to find when they take place.

28
A Better Representation
  • ltcompanygt
  • lttreatmentOfferedgtPhysiotherapylt/treatmentOffered
    gt
  • ltcompanyNamegtAgilitas Physiotherapy
    Centrelt/companyNamegt
  • ltstaffgt
  • lttherapistgtLisa Davenportlt/therapistgt
  • lttherapistgtSteve Matthewslt/therapistgt
  • ltsecretarygtKelly Townsendlt/secretarygt
  • lt/staffgt
  • lt/companygt

29
Explicit Metadata
  • This representation is far more easily
    processable by machines
  • Metadata data about data
  • Metadata capture part of the meaning of data
  • Semantic Web does not rely on text-based
    manipulation, but rather on machine-processable
    metadata

30
Ontologies
  • The term ontology originates from philosophy
  • The study of the nature of existence
  • Different meaning from computer science
  • An ontology is an explicit and formal
    specification of a conceptualization

31
Typical Components of Ontologies
  • Terms denote important concepts (classes of
    objects) of the domain
  • e.g. professors, staff, students, courses,
    departments
  • Relationships between these terms typically
    class hierarchies
  • a class C to be a subclass of another class C' if
    every object in C is also included in C'
  • e.g. all professors are staff members

32
Further Components of Ontologies
  • Properties
  • e.g. X teaches Y
  • Value restrictions
  • e.g. only faculty members can teach courses
  • Disjointness statements
  • e.g. faculty and general staff are disjoint
  • Logical relationships between objects
  • e.g. every department must include at least 10
    faculty

33
Ontology Example
name
email
  • Concept
  • conceptual entity of the domain
  • Property
  • attribte describing a concept
  • Relation
  • relationship between concepts or properties
  • Axiom
  • coherency description between Concepts /
    Properties / Relations via logical expressions

Person
Field
research field
isA hierarchy (taxonomy)
Student
Professor
attends
holds
Lecture
topic
Syllabus
holds(Professor, Lecture) gt Lecture.topic
Professor.researchField
34
The Role of Ontologies on the Web
  • Ontologies provide a shared understanding of a
    domain semantic interoperability
  • overcome differences in terminology
  • mappings between ontologies
  • Ontologies are useful for the organization and
    navigation of Web sites

35
The Role of Ontologies in Web Search
  • Ontologies are useful for improving the accuracy
    of Web searches
  • search engines can look for pages that refer to a
    precise concept in an ontology
  • Web searches can exploit generalization/
    specialization information
  • If a query fails to find any relevant documents,
    the search engine may suggest to the user a more
    general query.
  • If too many answers are retrieved, the search
    engine may suggest to the user some
    specializations.

36
Web Ontology Languages
  • RDF Schema
  • RDF is a data model for objects and relations
    between them
  • RDF Schema is a vocabulary description language
  • Describes properties and classes of RDF resources
  • Provides semantics for generalization hierarchies
    of properties and classes

37
Web Ontology Languages (2)
  • OWL
  • A richer ontology language
  • relations between classes
  • e.g., disjointness
  • cardinality
  • e.g. exactly one
  • richer typing of properties
  • characteristics of properties (e.g., symmetry)

38
Logic and Inference
  • Logic is the discipline that studies the
    principles of reasoning
  • Formal languages for expressing knowledge
  • Well-understood formal semantics
  • Declarative knowledge we describe what holds
    without caring about how it can be deduced
  • Automated reasoners can deduce (infer)
    conclusions from the given knowledge

39
An Inference Example
  • prof(X) ? faculty(X)
  • faculty(X) ? staff(X)
  • prof(michael)
  • We can deduce the following conclusions
  • faculty(michael)
  • staff(michael)
  • prof(X) ? staff(X)

40
Logic versus Ontologies
  • The previous example involves knowledge typically
    found in ontologies
  • Logic can be used to uncover ontological
    knowledge that is implicitly given
  • It can also help uncover unexpected relationships
    and inconsistencies
  • Logic is more general than ontologies
  • It can also be used by intelligent agents for
    making decisions and selecting courses of action

41
Tradeoff between Expressive Power and
Computational Complexity
  • The more expressive a logic is, the more
    computationally expensive it becomes to draw
    conclusions
  • Drawing certain conclusions may become impossible
    if non-computability barriers are encountered.
  • Our previous examples involved rules If
    conditions, then conclusion, and only finitely
    many objects
  • This subset of logic is tractable and is
    supported by efficient reasoning tools

42
Inference and Explanations
  • Explanations the series of inference steps can
    be retraced
  • They increase users confidence in Semantic Web
    agents Oh yeah? button
  • Activities between agents create or validate
    proofs

43
Typical Explanation Procedure
  • Facts will typically be traced to some Web
    addresses
  • The trust of the Web address will be verifiable
    by agents
  • Rules may be a part of a shared commerce ontology
    or the policy of the online shop

44
Software Agents
  • Software agents work autonomously and proactively
  • They evolved out of object oriented and
    compontent-based programming
  • A personal agent on the Semantic Web will
  • receive some tasks and preferences from the
    person
  • seek information from Web sources, communicate
    with other agents
  • compare information about user requirements and
    preferences, make certain choices
  • give answers to the user

45
Semantic Web Agent Technologies
  • Metadata
  • Identify and extract information from Web sources
  • Ontologies
  • Web searches, interpret retrieved information
  • Communicate with other agents
  • Logic
  • Process retrieved information, draw conclusions

46
Semantic Web Agent Technologies (2)
  • Further technologies (orthogonal to the Semantic
    Web technologies)
  • Agent communication languages
  • Formal representation of beliefs, desires, and
    intentions of agents
  • Creation and maintenance of user models.

47
Semantic Web Outline
  1. Todays Web
  2. The Semantic Web Impact
  3. Semantic Web Technologies
  4. A Layered Approach

48
A Layered Approach
  • The development of the Semantic Web proceeds in
    steps
  • Each step building a layer on top of another
  • Principles
  • Downward compatibility
  • Upward partial understanding

49
The Semantic Web Layer Tower
50
Semantic Web Layers
  • XML layer
  • Syntactic basis
  • RDF layer
  • RDF basic data model for facts
  • RDF Schema simple ontology language
  • Ontology layer
  • More expressive languages than RDF Schema
  • Current Web standard OWL

51
Semantic Web Layers (2)
  • Logic layer
  • enhance ontology languages further
  • application-specific declarative knowledge
  • Proof layer
  • Proof generation, exchange, validation
  • Trust layer
  • Digital signatures
  • recommendations, rating agencies .

52
Web Services
53
Agenda
  • What are Web Services?
  • Why Web Services?
  • Enabling Technologies?
  • What is Web Service Composition?
  • Main Issues concerning the composition?

53
54
Web Evolution
XML
HTML
Technology
TCP/IP
Programmability
Presentation
Connectivity
FTP, E-mail, Gopher
Innovation
Web Pages
Web Services
Browse the Web
Program the Web
54
55
What are Web Services?
  • Definition from W3C
  • "Web Service is a software application
    identified by a URI, whose interfaces and
    bindings are capable of being defined, described,
    and discovered by XML artifacts and which
    supports direct interactions with other software
    applications using XML-based messages via
    internet-based protocols".

55
56
What are Web Services?
  • Every component that
  • works in a network,
  • is modular
  • is self-descriptive,
  • provides services independent of platform and
    application,
  • conforms to an open set of standards and
  • follows a common structure for description and
    invocation.

56
57
Why Web Services
  • Interoperability.
  • Any WS can interact with any other WS.
  • Ubiquity.
  • Any device which supports HTTP XML can host
    access WS.
  • Effortless entry in this concept.
  • easily understood free toolkits
  • Industry Support.
  • major vendors support surrounding technology.

57
58
Web Services Architecture
  • Components
  • Service Providers
  • Service Brokers
  • Service Requestors
  • Operations
  • Publish / Unpublish
  • Find
  • Bind

58
59
59
60
Enabling technologies
  • They encapsulate a set of standards that allow
    the developers to implement distributed
    applications.
  • SOAP (Simple Object Access Protocol),
  • XML messaging protocol for basic service
    interoperability
  • WSDL (Web Service Description Language)
  • Common grammar for describing services
  • UDDI (Universal Description Discovery and
    Integration)
  • infrastructure required to publish and discover
    services.

60
61
SOAP
  • Uniform way of
  • passing XML-encoded data.
  • performing RPCs over SMTP, FTP, TCP/IP, HTTP
  • The requestor sends a msg to the service
  • The service processes the msg.
  • The service sends back a response.

The requestor has no knowledge of how the service
is implemented.
61
62
SOAP Example
  • ltSOAP-ENVEnvelope xmlnsSOAP-ENV"http//schemas.
    xmlsoap.org/soap/envelope/" SOAP-ENVencodingStyle
    "http//schemas.xmlsoap.org/soap/encoding/"/gt
  • ltSOAP-ENVBodygt
  • lteBookgt lttitlegtMy Life and Worklt/titlegt
  • ltfirstauthor href"Person-1"/gt
  • ltsecondauthor href"Person-2"/gt
  • lt/eBookgt
  • ltePerson id"Person-1"gtltnamegtHenry
    Fordlt/namegt
  • ltaddress xsitype"mElectronic-address"gt
    ltemailgtmailtohenryford_at_hotmail.comlt/emailgt
    ltwebgthttp//www.henryford.comlt/webgt
  • lt/addressgt
  • lt/ePersongt
  • ltePerson id"Person-2"gt ltnamegtSamuel
    Crowtherlt/namegt ltaddress xsitype"nStreet-addre
    ss"gt
  • ltstreetgtMartin Luther King Rdlt/streetgt
  • ltcitygtRaleighlt/citygt
  • ltstategtNorth Carolinalt/stategt
  • lt/addressgt
  • lt/ePersongt
  • lt/SOAP-ENVBodygt lt/SOAP-ENVEnvelopegt

62
63
SOAP - RPC
  • Must define an RPC protocol
  • How will types be transported (in XML) and how
    application represents them.
  • RPC parts (object id, operation name, parameters)
  • ?SOAP assumes a type system based on XML-schema.

63
64
SOAP Example - doGoogleSearch
  • ltSOAP-ENVEnvelope xmlnsSOAP-ENV
    http//schemas.xmlsoap.org/soap/envelope/
    xmlnsxsi"http//www.w3.org/1999/XMLSchema-instan
    ce" xmlnsxsd"http//www.w3.org/1999/XMLSchema"gt
  • ltSOAP-ENVBodygt
  • ltns1doGoogleSearch xmlnsns1"urnGoogleSearch"
    SOAP-ENVencodingStyle"http//schemas.xmlsoap.or
    g/soap/encoding/"gt
  • ltkey xsitype"xsdstring"gt000000000000000
    00000000000000000lt/keygt
  • ltq xsitype"xsdstring"gtmy querylt/qgt
  • ltstart xsitype"xsdint"gt0lt/startgt
  • ltmaxResults xsitype"xsdint"gt10lt/maxR
    esultsgt
  • ltfilter xsitype"xsdboolean"gttruelt/filte
    rgt
  • ltrestrict xsitype"xsdstring"/gt
  • ltsafeSearch xsitype"xsdboolean"gtfal
    selt/safeSearchgt
  • ltlr xsitype"xsdstring"/gt
  • ltie xsitype"xsdstring"gtlatin1lt/iegt
  • ltoe xsitype"xsdstring"gtlatin1lt/
    oegt
  • lt/ns1doGoogleSearchgt
  • lt/SOAP-ENVBodygt
  • lt/SOAP-ENVEnvelopegt

64
65
SOAP Example - doGoogleSearchResult
  • ltSOAP-ENVEnvelope xmlnsSOAP-ENV"http//schemas.
    xmlsoap.org/soap/envelope/" ..
  • ltSOAP-ENVBodygt
  • ltns1doGoogleSearchResponse xmlnsns1"urnGoogle
    Search" SOAP- ENVencodingStyle"http//schemas.xm
    lsoap.org/soap/encoding/"gt
  • ltreturn xsitype"ns1GoogleSearchResult"gt
  • ltdocumentFiltering xsitype"xsdboolean"gtfalselt
    /documentFilteringgt
  • ltestimatedTotalResultsCount
    xsitype"xsdint"gt3lt/estimatedTotalResultsCou
    ntgt
  • ltdirectoryCategories xmlnsns2"http//schemas.x
    mlsoap.org/soap/encoding/" xsitype"ns2Array"
    ns2arrayType"ns1DirectoryCategory0"/gt
  • ltsearchTime xsitype"xsddouble"gt0.194871lt/sear
    chTimegt
  • ltresultElements xmlnsns3"http//schemas.xmlsoa
    p.org/soap/encoding/" xsitype"ns3Array"
    ns3arrayType"ns1ResultElement3"gt
  • ltitem xsitype"ns1ResultElement"gt
  • ltcachedSize xsitype"xsdstring"gt12klt/cachedSiz
    egt
  • ltdirectoryCategory xsitype"ns1DirectoryCatego
    ry"gtCategorylt/directoryCategorygt
  • ltrelatedInformationPresent xsitype"xsd
    boolean"gttruelt/relatedInformationPresentgt
  • ltdirectoryTitle xsitype"xsdstring"/gt
  • ltsummary xsitype"xsdstring"/gt
  • ltURL xsitype"xsdstring"gthttp//hci.stanford.e
    du/cs147/example/shrdlu/lt/URLgt
  • lttitle xsitype"xsdstring"gtltbgtSHRDLUlt
    /bgtlt/titlegt
  • lt/itemgt

65
66
WSDL
  • IDL of Web Services
  • XML format developed by IBM MS.
  • Provides two types of information
  • Abstract interface Application-level service
    description
  • Protocol dependent details

66
67
WSDL - Abstract interface
  • Messages exchanged in an interaction.
  • Components
  • Vocabulary (XSD for type definition)
  • Message abstract, typed data definition sent to
    and from services.
  • Interaction

67
68
Vocabulary
  • ltwsdltypesgt
  • ltxsdschema xmlns"http//www.w3.org/2001/XMLSc
    hema" targetNamespace"urnGoogleSearch"gt
  • ltxsdcomplexType name"GoogleSearchResult"gt
  • ltxsdallgt
  • ltxsdelement name"documentFiltering"
    type"xsdboolean"/gt
  • ltxsdelement name"searchComments"
    type"xsdstring"/gt
  • ltxsdelement name"estimatedTotalResultsCount"
    type"xsdint"/gt
  • ltxsdelement name"estimateIsExact"
    type"xsdboolean"/gt
  • ltxsdelement name"resultElements"
    type"typensResultElementArray"/gt
  • ltxsdelement name"searchQuery"
    type"xsdstring"/gt
  • ltxsdelement name"startIndex"
    type"xsdint"/gt
  • ltxsdelement name"endIndex" type"xsdint"/gt
  • ltxsdelement name"searchTips"
    type"xsdstring"/gt
  • ltxsdelement name"directoryCategories"
    type"typensDirectoryCategoryArray"/gt
  • ltxsdelement name"searchTime"
    type"xsddouble"/gt
  • lt/xsdallgt
  • lt/xsdcomplexTypegt

68
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Message
  • ltmessage name"doGoogleSearch"gt
  • ltpart name"key" type"xsdstring"/gt
  • ltpart name"q" type"xsdstring"/gt
  • ltpart name"start" type"xsdint"/gt
  • ltpart name"maxResults" type"xsdint"/gt
  • ltpart name"filter" type"xsdboolean"/gt
  • ltpart name"restrict" type"xsdstring"/gt
  • ltpart name"safeSearch" type"xsdboolean"/gt
  • ltpart name"lr" type"xsdstring"/gt
  • ltpart name"ie" type"xsdstring"/gt
  • ltpart name"oe" type"xsdstring"/gt
  • lt/messagegt
  • ltmessage name"doGoogleSearchResponse"gt
  • ltpart name"return" type"typensGoogleSearchRes
    ult"/gt
  • lt/messagegt

69
70
Interaction
  • ltbinding name"GoogleSearchBinding"
    type"typensGoogleSearchPort"gt
  • ltsoapbinding style"rpc transport"http//schem
    as.xmlsoap.org/soap/http"/gt
  • ltoperation name"doGetCachedPage"gt
  • ltsoapoperation soapAction"urnGoogleSearchActi
    on"/gt
  • ltinputgt
  • ltsoapbody use"encoded"
  • encodingStyle"http//schemas.xmlsoap.org/soap/
    encoding/" namespace"urnGoogleSearch"/gt
  • lt/inputgt
  • ltoutputgt
  • ltsoapbody use"encoded" encodingStyle"htt
    p//schemas.xmlsoap.org/soap/encoding/"
    namespace"urnGoogleSearch"/gt
  • lt/outputgt
  • lt/operationgt

70
71
UDDI
  • Global business registry
  • Root under www.uddi.org
  • Three types of information
  • White pages
  • Yellow pages
  • Green pages

71
72
UDDI information model
  • BusinessEntity
  • Info about business that publishes
  • Info about service
  • PublisherAssertion
  • Info about relationshipbetween 2 parties

encapsulates
  • BusinessService
  • Descriptive info abouta service

encapsulates
  • tModel
  • Descriptions on specifications ofservices
  • BindingTemplate
  • Technical info about a serviceend point

72
73
Web Service Composition
  • Definition Technique of composing the
    functionalities of relatively simpler services to
    produce a meaningful arbitrarily complex
    application.

73
74
WS composition - Classification
  • Proactive Composition Reactive Composition
  • Proactive offline composition of available
    services
  • When services are stable and always running
  • Example ticket reservation service
  • Reactive dynamically creating a composite
    service.
  • When composite service not often used and
    service processes not stable.
  • Example tour manager where the itinerary is not
    predefined

74
75
WS composition Classification (2)
  • Mandatory Optional-Composite Services
  • Mandatory all subcomponents must participate to
    yield a result
  • Example service that calculates the averages of
    stock values for a company.
  • Optional subcomponents are not obligated to
    participate for a successful execution.
  • Example services that include a subcomponent
    that is an optimizer.

75
76
Important issues on WS composition
  • Service Discovery
  • Service Coordination and Management
  • Uniform Information Exchange Infrastructure
  • Fault Tolerance and Scalability
  • Adaptiveness
  • Reliability Transactions
  • Security
  • Accountability
  • Testing

76
77
Service Discovery
  • An efficient discovery structure should be able
  • find out all services implementing some
    functionality (ontology)
  • semantic level reasoning (discover most
    appropriate service).
  • scalable.
  • Most of existing discovery infrastructures use a
    central lookup server (Jini, UPnP)
  • Semantic Language DAML-S, a process modelling
    language for computer-interpretable description
    of services.
  • AI inspired description logic-based language,
    built on top of XML RDF for well-defined
    semantics and a set of language constructs and
    properties.

77
78
Service Discovery - DAML-S
  • Enables automatic Web Service discovery.
    automatic location of services with required
    functionality.
  • Currently performed manually
  • DAML-S expressed in computer interpretable
    semantic markup.

78
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Service Discovery - Example of DAML-S
  • ltdamlClass rdf IDCompositeProcessgt
  • ltdamlintersectionOf rdfgtparseType
    damlcollectiongt
  • ltdamlClass rdfaboutProcess/gt
  • ltdamlRestriction damlminCardinality1gt
  • ltdamlonProperty rdfresourcecomposedOf/gt
  • lt/damlRestrictiongt
  • lt/damlintersectionOfgt
  • lt/damlClassgt
  • ltrdfProperty rdfIDcomposedOfgt
  • ltrdfs domain rdfresourceCompositeProcess/gt
  • ltrdfs range rdfresourceControlConstruct/gt
  • lt/rdfPropertygt

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Reliability Transactions
  • How we can measure reliability?
  • WS descriptions may lie!
  • Transactions are fundamental to reliable
    distributed computing.
  • Traditional transaction systems support ACID
    semantics, use a two-phase commit approach all
    participating resources are locked until entire
    transaction is completed.
  • Only in close environments where transactions are
    short-lived
  • Not on an open environment (flexibility in how it
    is attained)
  • MS XLANG compensating transactions.
  • Split the model into concurrent sub-transactions
    that can commit independently (requires
    compensation over committed sub transactions in
    case of abortion).

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Security
  • Basic security HTTP over SSL
  • Authorisation control.
  • Existing authorisation control frameworks not
    applicable to WS (designed for some services e.g.
    network access control (DIAMETER) or not well
    designed to access different administrative
    domains (.NET Passport))
  • Proposal generic authorisation control protocol
    based on SOAP/XML. Supports credential
    transformation.
  • Need for CA in each domain. It will issue users
    and services with certificate and secret key
    pairs used for user authentication and request
    signing.
  • Credentials described in an XML-based language.
    Authorisation server validates the certificate,
    credentials etc. If everything is successfully
    validated, the authorisation server sends back a
    SOAP response containing the result.

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Semantic Web Services
83
Semantic Web Services
  • Semantic Web Technology
  • Web Service Technology
  • allow machine supported data interpretation
  • ontologies as data model

automated discovery, selection, composition, and
web-based execution of services
gt Semantic Web Services as integrated solution
for realizing Vision of Next Generation Web
Technologies of the next generation of the Web
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Semantic Web Services
  • define exhaustive description frameworks for
    describing Web Services and related aspects (Web
    Service Description Ontologies)
  • support ontologies as underlying data model to
    allow machine supported data interpretation
    (Semantic Web aspect)
  • define semantically driven technologies for
    automation of the Web Service usage process (Web
    Service aspect)

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Semantic Web Services
  • Usage Process
  • Publication Make available the description of
    the capability of a service
  • Discovery Locate different services suitable for
    a given task
  • Selection Choose the most appropriate services
    among the available ones
  • Composition Combine services to achieve a goal
  • Mediation Solve mismatches (data, protocol,
    process) among the combined
  • Execution Invoke services following programmatic
    conventions

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Semantic Web Services
  • Execution support
  • Monitoring Control the execution process
  • Compensation Provide transactional support and
    undo or mitigate unwanted effects
  • Replacement Facilitate the substitution of
    services by equivalent ones
  • Auditing Verify that service execution occurred
    in the expected way

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Additional Reading (Semantic Web)
Dieter Fensel Ontologies A Silver Bullet for
Knowledge Management and Electronic Commerce,
Springer Verlag, 2001
Johan Hjelm, Creating the Semantic Web with
RDF, John Wiley, 2001
John Davies, Dieter Fensel Frank van Harmelen,
Towards the Semantic WEB Ontology Driven
Knowledge Management, John Wiley, 2002
Dieter Fensel, Wolfgang Wahlster, Henry
Lieberman, James Hendler (Eds.) Spinning the
Semantic Web Bringing the World Wide Web to Its
Full Potential, MIT Press, 2002
Michael C. Daconta, Leo J. Obrst, Kevin T. Smith
The Semantic Web A Guide to the Future of XML,
Web Services, and Knowledge Management, John
Wiley, 2003
Thomas B. Passin, "Explorer's Guide to the
Semantic Web", ISBN 1932394206, June 2004
Jeff Pollock and Ralph Hodgson, "Adaptive
Information Improving Business Through Semantic
Interoperability, Grid Computing, and Enterprise
Integration, Wiley Computer Publishing,
September 2004
M. Klein and B. Omelayenko (eds.), Knowledge
Transformation for the Semantic Web, Vol. 95,
Frontiers in Artificial Intelligence and
Applications, IOS Press, 2003
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Additional Reading (Web Services)
  1. Dipanjan Chakraborty, Technical Report
    TR-CS-01-19 Dynamic Service composition
    State-of-the-Art and Research Directions.
    University of Maryland, Baltimore County, 2001.
  2. Anans Rajamam, Overview of UDDI, Online, 2001.
  3. F.Curbera and al, Unraveling the Web Services
    Web An Introduction to SOAP, WSDL, and UDDI.
    IEEE Internet Computing March-April 2002,
    p.86-93.
  4. DAML Service Coalition, DAML-S Semantic Markup
    for Web Services. Online at http//www.daml.org/se
    rvices/daml-s/2001/10/daml-s.html, 2001.
  5. WSDL Specification, Online at http//www.w3c.org/T
    R/wsdl.
  6. Steve Vinoski, Web Services and Dynamic
    Discovery, Online at http//www.webservices.org/ar
    ticle.php?sid389, 2001.
  7. UDDI Specification, Online at http//uddi.org/.
  8. Sheila A. McIlaith, Tran Cao Son, Honglei Zeng,
    Semantic Web Services, IEEE Intelligent Systems,
    2001
  9. Vladimir Tosic, Bernard Pagurek, Babak
    Esfandiari, Kruti Patel, On the Management of
    Composition of Web Services, Carleton University,
    Canada.
  10. Tom Clements, Overview of SOAP. Online at
    http//dcb.sun.com/practices/webservices/overviews
    /overview_soap.jsp
  11. Deitel,Web Services A technical Introduction,
    Prentice Hall, 2002.

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