Internet Engineering Course

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Internet Engineering Course

• Semantic Web,
• Web Services,
• Semantic Web Services

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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

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Vision of Next Generation Web Technologies

• 500 million users
• more than 3 billion pages

WWW URI, HTML, HTTP
Static
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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
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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
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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
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Semantic Web
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Semantic Web Outline

• Todays Web
• The Semantic Web Impact
• Semantic Web Technologies
• A Layered Approach

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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

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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

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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

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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, . . .

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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

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Semantic Web Outline

• Todays Web
• The Semantic Web Impact
• Semantic Web Technologies
• A Layered Approach

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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)

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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

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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.

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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

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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

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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

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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

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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

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Semantic Web Outline

• Todays Web
• The Semantic Web Impact
• Semantic Web Technologies
• A Layered Approach

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Semantic Web Technologies

• Explicit Metadata
• Ontologies
• Logic and Inference
• Agents

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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

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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.

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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.

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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

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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

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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

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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

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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

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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
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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

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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.

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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

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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)

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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

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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)

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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

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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

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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

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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

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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

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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

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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.

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Semantic Web Outline

• Todays Web
• The Semantic Web Impact
• Semantic Web Technologies
• A Layered Approach

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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

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The Semantic Web Layer Tower
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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

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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 .

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Web Services
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Agenda

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

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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
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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".

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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.

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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.

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Web Services Architecture

• Components
• Service Providers
• Service Brokers
• Service Requestors
• Operations
• Publish / Unpublish
• Find
• Bind

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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.

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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.
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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

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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.

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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

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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

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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

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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

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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

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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

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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

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UDDI

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

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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

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Web Service Composition

• Definition Technique of composing the
  functionalities of relatively simpler services to
  produce a meaningful arbitrarily complex
  application.

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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

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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.

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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

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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.

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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.

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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
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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)

• Dipanjan Chakraborty, Technical Report
  TR-CS-01-19 Dynamic Service composition
  State-of-the-Art and Research Directions.
  University of Maryland, Baltimore County, 2001.
• Anans Rajamam, Overview of UDDI, Online, 2001.
• 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.
• 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.
• WSDL Specification, Online at http//www.w3c.org/T
  R/wsdl.
• Steve Vinoski, Web Services and Dynamic
  Discovery, Online at http//www.webservices.org/ar
  ticle.php?sid389, 2001.
• UDDI Specification, Online at http//uddi.org/.
• Sheila A. McIlaith, Tran Cao Son, Honglei Zeng,
  Semantic Web Services, IEEE Intelligent Systems,
  2001
• Vladimir Tosic, Bernard Pagurek, Babak
  Esfandiari, Kruti Patel, On the Management of
  Composition of Web Services, Carleton University,
  Canada.
• Tom Clements, Overview of SOAP. Online at
  http//dcb.sun.com/practices/webservices/overviews
  /overview_soap.jsp
• Deitel,Web Services A technical Introduction,
  Prentice Hall, 2002.

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