CS690L Semantic Web and Knowledge Discovery: Concept, Technologies, Tool

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CS690LSemantic Web and Knowledge Discovery
Concept, Technologies, Tool

• Yugi Lee
• STB 555
• [phone]
• leeyu_at_umkc.edu
• www.sice.umkc.edu/leeyu
• This presentation was designed based on
• SWWS-01 symposium report and Farquhars Ontology
  tutorial.

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Semantic Web?

• "The Semantic Web is an extension of the current
  web in which information is given well-defined
  meaning, better enabling computers and people to
  work in cooperation." -- Tim Berners-Lee, James
  Hendler, Ora Lassila, The Semantic Web,
  Scientific American, May 2001

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Semantic Interoperability

• Ihe interoperability layer to migrate from the
  syntactic to the semantic!
• From Data space to Knowledge space
• Integration and composition

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Interoperability

• Object Interoperability
• This is the layer at which the current middleware
  products are aimed in the industry.
• However these objects are primarily defined as
  containers for software and for streamlining the
  software development process.
• The CORBA, EJB object models are examples of
  standards at this layer.

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Interoperability

• Meta-Model Interoperability
• This is the layer at which the cross-over from
  the "data" space to the "knowledge" space takes
  place.
• The objects here are viewed as containers of
  knowledge to be fleshed out by upper layers.
• The OKBC and RDF(S) core models are examples of
  standards at this layer.

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Interoperability

• Ontology Interoperability
• This is the layer where ontologies, schemas and
  classifications are built upon common underlying
  standardized meta-models.
• The ability to use different ontologies to
  specify and query information constitutes
  interoperability at this layer.
• Ontology Standardization

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Interoperability

• Meta-Data (View/Query) Interoperability
• Semantic metadata descriptions can be constructed
  from one or more underlying ontologies.
• Issues at this layer would be to decompose
  information requests into those supported by the
  individual semantic metadata descriptions
  corresponding to the information sources.
• Ontology Query Language

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Interoperability

• Process/Services Interoperability
• Semantic process/service descriptions can be
  constructed from resources on the Web and one or
  more underlying ontologies.
• Issues at this layer would be to enable a better
  discovery, selection, composition, monitoring,
  and interoperability of services/process.
• A resource description, informally called its
  semantics, includes that information about the
  resource that can be used by computers - not just
  for display purposes, but for using it for
  automatic processing in various applications.
• Service Ontology, Semantic web service workflow,
  Web Service Discovery, addressing semantic
  heterogeneity handling, QoS specification for Web
  Services and Processes.

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Practical Motivation Semantic Web/Application

• The Semantic Web is more than simply some sort of
  academic foolishness or rewarmed AI vision.
• The applications showed real technology and tools
  are being built in the Semantic web community,
  and that there is a lot of interest in these
  technologies on the part of industry and
  government.
• The web services community showed one area where
  there is tremendous industrial interest and where
  semantic web technology could be an important
  part of the work.

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Challenging Example Query Answering

• How many acres of cotton are planted in China?
• Response from todays Web Some documents --
  some of which may contain the answer -- somewhere
  
• Response from the Semantic Web of the future
  15,485,000 in 2000, says the USDA
• Deductive query answering rather than document
  retrieval
• Ontologies will be a primary source of knowledge
  for reasoning enable derivation of answers not
  explicitly on a Web site
• Even simple Web sites may reference large and
  distributed ontologies a challenge to
  query-answering reasoners
• Ontologies could include special purpose
  query-answering reasoners
• For proving instances of atomic formulas in the
  ontologys vocabulary and making inferences from
  sentences in the ontologys vocabulary
• Requires an API for special purpose reasoners

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Challenging Example Semantic Search

• Taps Semantic Search (Stanford University)
• Retrieves real-time data relevant to a quer
  Determines the semantic type of individuals in
  the query, Uses models of relevancy based on
  types
• Uses a background ontology and large KB of
  individuals
• 3,000 class and 72,000 individuals,
  Downloadable in RDF-S or DAMLOIL
• Can be augmented with use-specific and
  user-specific ontologies and used to retrieve
  data relevant to a task being performed

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Ontology - What Is an Ontology? A. Farquhar

• To communicate, plan, think we need
  aconceptualization of the world
• What kinds of things are there? What are their
  properties? What are their relationships?
• These things define our ontology
• We all have ontologies (e.g., of organizations,
  computers, animals)
• Some are very idiosyncratic. Some are shared!
• Communication and interaction require common
  shared ontologies.

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Ontology - Problems in Communication

• People, organizations, software programs must
  communicate
• Different needs and backgrounds imply different
  viewpoints, assumptions, jargon
• This divergence is natural and valuable
• But leads to problems in communication,
  interaction, and understanding

• Explicit ontologies are crucial for
• Communication
• Education
• Interoperation
• Integration
• Adaptive agents

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Ontology - Example

• Researchers in molecular biology need to
• share results and check consistency between their
  models, data, and reported models and data
• The Riboweb project (Stanford, SMI)
• Building an ontology for ribosomes, models, data,
  reports
• Molecular structure, experimental data, tests,
• Encoding (by hand) relevant literature

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Ontology - Example

• Doctors, clinics, hospitals, insurance companies,
  government agencies need to share information
• Clinical guidelines, drug interactions, covered
  procedures, best practices
• Several efforts are addressing aspects of this
  problem
• UMLS (unified medical language system)
• SNOMED (standard nomenclature for medicine)

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Ontology - Example

• There are many workflow management systems
  available
• In order to share information across them and
  support interoperation, we need to define an
  integrated ontology that covers
• Processes, resources, products, services,
  organizations
• Several groups are involved in such an effort
• NIST, WfMC, PIF, TOVE

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Ontology - Example

• Collaborative engineering projects need to
  communicate across discipline boundaries
• Several projects (e.G., PACT, Boeing) have worked
  to build ontologies for the subdisciplines and
  span them
• Goals include
• Automated notifications on design modifications
• Cross-disciplinary simulation
• Improved design process

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Ontology - Benefits

• Explicit ontologies support
• Shared understanding among people
• Interoperability between tools
• Systems engineering
• Reusability
• Declarative specification

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Semantic Web Language

• XML
• Language for describing the structure of document
  content e.g., declare data to be a retail price,
  a sales tax, a book title, ...
• Uniform method for describing and exchanging data
  using HTTP
• Provides a syntactic schema
• ltPublication URL "ftp//db.stanford xml.psgt
• ltTitlegt From Semistructured Data ... Language
  lt/Titlegt
• ltAuthorgt R. Goldman lt/Authorgt
• ltPublishedgt Proceedings of ... Databases
  lt/Publishedgt
• ltLocationgt Location of
  what?
• ltCitygt Philadelphia lt/Citygt
• ltStategt Pennsylvania lt/Stategt
• lt/Locationgt
• ltDategt
• ltMonthgt June lt/Monthgt
• ltYeargt 1999 lt/Yeargt
• lt/Dategt
• lt/Publicationgt

When in June?
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Semantic Web Language

• XML Is Not Enough
• Ontologies enable independently developed
  programs to exchange data XML provides
  syntactic schema
• Ontologies specify intended meaning in a computer
  interpretable form XML provides no means of
  specifying intended meaning of tags
• XML is like HTML, where you make up your own
  tags.
• But in XML, you cant say what your tags mean.

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W3C Semantic Web Activity

• Semantic Web Activity (http//www.w3.org/2001/sw/)
  
• Established to serve a leadership role, in both
  the design of enabling specifications and the
  open, collaborative development of technologies
  that support the automation, integration and
  reuse of data across various applications.
• Successor to the W3C Metadata Activity
• RDF Core Working Group (http//www.w3.org/2001/sw/
  RDFCore/)
• Responsible for the Resource Description
  Framework (RDF)
• Web Ontology Working Group (http//www.w3.org/2001
  /sw/WebOnt/)
• Charter Build upon the RDF Core work a language
  for defining structured web based ontologies
  which will provide richer integration and
  interoperability of data among descriptive
  communities
• Developing Ontology Web Language (OWL)
• Based on DAMLOIL, developed in DARPAs Agent
  Markup Language program

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Open Issues

• What can we do as individuals and as part of the
  semantic web community?
• Everyone was frustrated by the "waiting around"
  for Semantic Web infrastructure to appear,
• that creating "some" infrastructure was more
  important that resolving the remaining
  "expressivity vs. tractability" dilemmas (for
  example).
• there is always risk solving the easy parts of
  problems first, because that can make it harder
  to solve the harder parts later. Nevertheless,
  the consensus was "forge ahead!"

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Open Issues

• Do we need to standardize on foundational models
  first?
• agree on minimalist semantics (expressivity) and
  a syntax in which to represent units of meaning,
• leaving for distributed, incremental, and local
  development the problem of creating actual
  ontologies
• that would be expressed, represented and
  communicated using the foundational model.

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Open Issues

• Is the current Semantic Web standards development
  process adequate?
• This addresses the dilemma posed by a general
  acknowledgement that the Semantic Web poses new
  challenges
• The current standards process may be the best
  that we know how to create, and it still may be
  inadequate - because, for instance, it deals with
  distributed semantics.
• At worst, it needs field-testing and feedback
  from actual use.

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Open Issues

• Do we need Semantic Web glossaries? ("pumpkins?")
• Even if there was not consensus on the
  definitions, all agreed that Semantic Web
  glossaries would be a big help
• they would be something to disagree with, and
  catalyze alternative definitions for important
  concepts.
• Do we need some ontology ontologies?
• Everyone recognized the "ontology ontology"
  problem and that it's lack of resolution was an
  impediment to progress, and that "we are all part
  of the problem."
• That is, it's hard to find out what ontologies
  exist, and whether they are worth using, etc.
  This is part, but not all, of the deep ontology
  re-use challenge.

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Open Issues

• How do we deal with the diversity of languages
  and tools that are starting to emerge for
  semantic content.
• Currently XML, XML schema, RDF(S), DAMLOIL,
  WebML, and various other tools are available for
  metadata storage, querying, etc.
• It is clear that there is a need for unifying
  frameworks, toolkits, etc.
• Do we need well-defined semantics in the metadata
  languages?
• Many of the applications were using ontology
  languages like DAML, or extensions of RDF(S).
• Consensus was that completing the RDFS standard,
  and moving to a web ontology standard that
  extended RDFS and XML Schema was important for
  these applications.

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Open Issues

• Do we all believe that experimentation should
  continue?
• expressivity vs. tractability
• We have no proof that proposed Semantic Web
  standards and tools are useful or even work at
  all.
• The chicken/egg problem
• Without semantic markup, there's not a lot of
  motivation for the industrial base to pay
  attention to the semantic web.
• Without industry investment/support, the W3C and
  others have trouble developing standards and
  getting sources marked up.
• Current government funding helps to jump start
  this level, but the semantic web community needs
  to figure out how to both publicize these efforts
  and increase the dissemination of this
  technology.

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Discussion

• What will make the semantic web have a life of
  its own?
• What are key ontologies that need to be created?
• What are the killer apps for the semantic web?
• Do you have ontologies you could contribute?