Introduction to Semantic Web Design

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Introduction to Semantic Web Design

• B. Ramamurthy

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Introduction

• Web in its current form is an application on the
  internet that delivers information. Ex browsing
  daily news
• Current applications involving the web integrate
  data and information. Ex online shopping
• Next generation web is expected integrate a
  variety of resources and devices and support
  knowledge sharing among machines.
• Exploit the economies of scale possible by
  machines processing of knowledge.
• How to tell the machines about the resources and
  how to specify concepts? How can machines acquire
  knowledge? How to share knowledge among machines?
  How to enable them to make decisions based on
  these?
• Need to specify resources, concepts, knowledge
  and other artifacts used in human decision making
  in a form usable by machines.
• Machines can then integrate and analyze
  information and make decisions and collect
  knwolegde.
• In this lecture we will examine technology,
  tools, frameworks, and applications enabling the
  next generation web, the semantic web.
• We will also discuss an intelligent search engine
  serving municipal services in a real semantic web
  application (Chapter 4)

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References for todays discussion

• W3C schools tutorials (http//www.w3schools.com)
• Taxonomies and the semantic web by Alistair
  Miles, CISTRANA workshop, Feb 2006, Rutherford
  Appleton Lab

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HTML, XML, RDF, and OWL

• HTML
• HTML stands for Hyper Text Markup Language
• An HTML file is a text file containing small
  markup tags
• The markup tags tell the Web browser how to
  display the page
• XML
• XML stands for eXtensible Markup Language
• XML is a markup language much like HTML
• XML was designed to carry data, not to display
  data
• XML tags are not predefined. You must define your
  own tags
• XML is designed to be self-descriptive
• XML is a W3C Recommendation

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HTML, XML RDF, ..

• RDF
• RDF stands for Resource Description Framework
• RDF is a framework for describing resources on
  the web
• RDF provides a model for data, and a syntax so
  that independent parties can exchange and use it
• RDF is designed to be read and understood by
  computers
• RDF is not designed for being displayed to people
  
• RDF is written in XML
• RDF is a part of the W3C's Semantic Web Activity
• RDF is a W3C Recommendation
• Lets discuss the details.

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HTMLOWL

• OWL
• OWL stands for Web Ontology Language
• OWL is built on top of RDF
• OWL is for processing information on the web
• OWL was designed to be interpreted by computers
• OWL was not designed for being read by people
• OWL is written in XML
• OWL has three sublanguages
• OWL is a web standard

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Web ontology
Natural language Ex English
Natural language Ontology
Programming language Ex Pascal
Web ontology
Programming language is a strict syntaxed
language for expressing algorithms (steps) for
execution by a computing device. Web ontology is
for expressing web related concepts. Web ontology
language (OWL) is a technology for accomplishing
this. Protégé-OWL is a tool that implements OWL.
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Taxonomy and web ontology

• Taxonomy is a science of classification. F
  Taxonomy
• Ontology is specification of conceptualization.
  F Ontology
• XML allows for meaningful tags. T XML
• Resource Definition Framework is an XML language
  for defining resources on the web (www). T RDF
• Web Ontology Language (OWL) TOWL
• RDF is an assertional language intended to be
  used to express propositions using precise formal
  vocabularies, particularly those specified using
  RDFS RDF-VOCABULARY, for access and use over
  the World Wide Web, and is intended to provide a
  basic foundation for more advanced assertional
  languages with a similar purpose. The overall
  design goals emphasize generality and precision
  in expressing propositions about any topic,
  rather than conformity to any particular
  processing model.

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RDF and OWL

• OWL is a semantic extension of RDF it allows for
  specification of logical dependencies between
  information structures. (as defined by Miles ref
  2)
• OWL works on structured information
• RDF is for structuring information.
• OWL is an information model.9

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Semantic stack
OWL
Semantic web
RDFS
RDF
URI
XML
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Intelligent Search Engine for online access to
municipal services (Ch 4) problem definition

• Citizens can perform 80 of the city services
  from home
• When somebody is looking for a service one must
  be able to locate it easily.
• You can collect, categorize and list all the
  services (.. Taxonomy)
• However searching through this list may not yield
  expected results using traditional search
  engines.
• Search results are based on the description of
  the services and co-occurrence of the words in
  the query.
• Ex A citizen want to dispose a washing machine
  should search for special collection of large
  items
• Cannot force citizens to learn government
  language
• When a service is looked upon a set of related
  services should be made available
• Search engine is a first step in the roadmap to
  citizen self-service

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Zaragoza Municipal services roadmap (Fig. 4.1)
Positioning
Intelligent search Engine
Citizen channels
Citizen self-service
Interface
Functionality
Content Scope
Technology
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Application of semantic web

• Three ways that Zaragosa used semantic web are
• Statistical approach to interpretation of citizen
  requests. (fig. 4.3)
• Enhanced-keyword based approach to interpretation
  of citizen requests. (fig. 4.4)
• Applying semantic distance to interpreting
  citizen requests. (fig. 4.5)

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Usage of the three methods

• First approach is cheapest and consumes less
  resources and the semantic web approach is the
  most expensive.
• Zaragosa architecture arranges the three in a
  pipeline architecture where each stage is
  triggered only when previous stage did not result
  is satisfactory results.

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How does it work?

• Traditional search engines retrieve documents
  based on occurrences of keyboards vs. Zaragosa
  SOA (ZS) has understanding of its services,
  information and data.
• ZS knows persons can change addresses, car owners
  pay taxes, construction work requires permits,
  building bars near schools is not good etc.
• All this information is stored in an ontology a
  computer understandable description of what
  e-services are.
• This ontology allows ZS to understand citizenss
  query and thus returns meaningful results.
• ZS also uses natural language understanding
  software to translate free text queries of
  citizens into the ontology. (see fig. 4.6)

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Citizen-city government interaction (Fig. 4.6
modified)
Natural language query
Semantic Query
Result
Knowledge Tagger (KT)
NLP
Semantic Distance Analyzer (SD)
ZS domain ontology
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Search vs. Intelligent Search

• Search for keywords
• Result in ranked list of documents
• Users need to invest time and effort to filter
  the right piece of information out of the overall
  results

• Search for keywords, semantic concepts.
• Results in actual relevant document
• Perceived as search engine that understands the
  user.

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ZS Domain Ontology

• Development of an ontology starts with detailed
  study of the services offered by the city.
• Objective is to extract all relevant terms
  belonging to this domain from existing documents.
• ZS ontology contains four main classes agent,
  process, event, object

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ZS Domain Ontology (contd.)

• Agent entity participating in an action
• Process A series of actions that a citizen can
  do using the online services offered by the city
  government.
• Event any social gathering or activity.
• Object any entity that exists in the city which
  can be used for or by a service offered by the
  city government.

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Using the ontology

• Approach is to establish a semantic similarity
  between a question provided by a citizen and the
  FAQs already available.
• Ontology needs to be complete in order to contain
  all the necessary terms to satisfy the requests.
• Ontology is completed with a number of thesauri
  to identify synonyms. Ex baby and infant
• Context information is used to tackle any
  ambiguity.

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Natural Language Process for ZS

• Knowledge tagger automatically annotates text
  according to domain ontology
• Series of linguistic analyzers, sentence
  splitters, simple tokenizers, spell checkers and
  morphological databases.
• Outcome of this analysis is a annotated text
  equivalent of the query.
• Then the query is synthesized in terms of domain
  ontology RDQL, SPARQL, SQL

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Semantic Annotation of city services

• Collect and index the information about services
• Semantic processing results in ontological
  entities concepts, instances, attributes, and
  relations
• Output of this process is semantically described
  services that can checked against citizens
  queries.

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Overall Architecture of ZS
Search clients
Search Systems web services
Ontology Systems Ontology cache Ontology
Subsytem Web services
NLP systems NLP cache NLP subsystem Web services
Persistence RDBMS
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Summary

• Zaragosa is an powerful SOA that uses semantic
  knowledge to better serve its citizens.
• Its roadmap is open with ability to extend the
  system through its WS interface.

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Networked SOA for Zaragosa
Enterprise Layer
Intermediary layer
Semantic Search