Ontology Work Guide for Web Contents Principle and Methods proposal for new work item in ISO TC37

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Ontology Work Guide for Web Contents- Principle
and Methods(proposal for new work item in ISO
TC37)

• ISO TC37/SC4 N435
• Nov 12, 2007
• Presented by Miran Choi/ETRI
• Written by Jae Sung Lee/Chungbuk National Univ.

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• Contents
• Motivation
• Ontology Construction for Web Contents
• Related Standards and Ontology Work Scope

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Motivation
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Semantic search

• Limit of keyword search
• ambiguous keywords in query and docs
• retrieves too many redundant documents
• waste time on finding what we want
• Semantic search
• Ideally no ambiguity in query and text
• retrieve docs with more accuracy by use of
  semantic information
• need to solve technical problems
• Query method
• Semantic tagging
• Globally common ontology construction

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Various ontologies

• Various ontologies are being built
• in many areas and applications
• Classification of ontology is various
• Different levels of ontologies
• Lightweight ontology
• Simple metadata level, or concepts with
  hierarchy, or small number of axioms
• E.g. term list, MDR, ISOCat, Topic Map, SUMO
• Heavyweight ontology
• Delicate definitions and first order logic for
  inference
• E.g. BFO, DOLCE

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Evolving ontologies

• Ontologies are growing in their own ways
• Various collections of ontology
• Ontology library
• e.g. SWAG, DAML ontology library
• Ontology registry
• e.g. MDR, ISOCat
• Etc.
• For the global search
• Semantic harmonization methods are needed by
  sharing standard principle and methods
• Global coordination is needed for the various
  standards

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Standardization of construction procedure

• Needs
• To make ontologies consistent and compatible each
  other
• To promote reuse of existing ontologies
• To avoid conflicting definitions
• To lessen confusion in semantic contents search
• The sooner, the less confusion!

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Ontology construction for web contents
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Web contents for semantic search

• Web contents characteristic
• Various topics and technical levels
• But, target to the general, less technical, not
  too specific contents.
• Ontology for semantic search
• Less strict meaning definition than the ontology
  for interoperability
• A little semantic difference is tolerable
• Lightweight ontology is enough
• Use controlled vocabulary or shared terms
• Include some basic relationship if needed
• But no complicated relationship

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Using other ontologies

• A guide is needed to use existing ontologies
• May need a ontology for ontologies to look up.
• May need to filter out only lightweight
  features except other complex relations or
  axioms.
• Consulting existing ontologies
• ontology library
• E.g. Daml ontology library, Semantic Web
  Agreement Group
• ontology registry
• E.g. Meta data registry, Data category registry
  (ISOcat)
• ontology homepage/document
• E.g. SUMO

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Construction of new ontology

• General construction guide can be derived from
  other guides
• Terminology work(ISO 704)
• Building ontologies and knowledge elicitation
  (Rector et al)
• And others
• General steps of ontology construction
• Classify the target objects
• Define the concept of the objects
• Concepts are defined by only essential
  characteristics
• Define relationship between concepts
• Implementations and evaluation

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Ontology formats/languages

• Standard Ontology Language
• Choose one of the languages
• RDF(S), OWL, UML, SCL, DL etc
• Or, define mapping between them by using the
  following standards
• Ontology Definition Metamodel (by OMG)
• Metamodel Framework (MMF)
• Naming convention (designations)
• Terms
• sometimes ambiguity problem
• Numbers
• E.g. Published Semantic Indicators
• Concatenated terms (ISO/IEC 11179)
• E. g. PersonGivenName
• Harmonized method?

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Publicity

• Central ontology registry
• All new ontologies should be known to
  applications and other users.
• Central registry keeps the ontologeis or
  reference points.
• Central registry can be accessed by all.
• Need to keep all other compatible ontologies list.

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Related standardsand ontology work scope
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Semantic Web

• Represent semantic information using URI triples.
• A triple represents subject, property (relation)
  and object.
• Make inference based on the triples
• Notation 3 example
• ltgt lthttp/purl.org/dc/elements/1.1/creatorgt
  _x0.
• _x0 lthttp//xmlns.com/0.1/foaf/namegt Jae
  Sung Lee.
• Ontology is built by using URI triples.
• Interoperable among agents sharing ontology
• Problem various ontology metadata
• use their own triples with various ontology
  (namespace)
• interoperable in a domain, but not in a global
  scale.

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Common Ontology

• One universe common ontology for interoperability
• Ideal but not practical now
• No global ontology
• Web is not static
• Needs semantic reconciliation because...
• agreed standard only address a small body of
  knowledge
• must accommodate prior resources to standard
• new work will have to go beyond standard
• Consensus ontology
• if have sufficient overlap under the same
  universe of discourse
• then reconcile ontologies
• Merging ontology is difficult
• concept mapping will happen 1-1, n-1, n-n
• value mapping is not always consistent

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W3C Ontology

• Ontology languages for standard format
• RDF
• represents graph for structure
• RDFS
• use specialized vocabulary and primitive classes
  and properties
• OWL
• more precise expressive than RDFS
• Evolutionary ontology
• Keep systems interoperable using partial
  understanding and transformability
• For common understandable terms, third party
  databases are needed eg. SWAG (Semantic Web
  Agreement Group)
• SWAG keeps namespaces rdf, foaf, dc and etc.
• DAML ontology library keeps various ontologies.

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IEEE SUO/SUMO

• IEEE SUO
• limited to concepts that are meta, generic,
  abstract and philosophical
• general enough to address (at a high level) a
  broad range of domain areas
• provide a structure and a set of general concepts
  upon which domain ontologies could be
  constructed.
• IEEE SUMO/MILO
• Largest formal public ontology
• Suggested Upper Merged Ontology
• MId-Level Ontology
• Communications, Countries and Regions,
  distributed computing, Economy, Finance,
  Engineering components, Geography, Government...
• domain ontologies could be constructed based on
  this.

source http//www.ontologyportal.org
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Topic Map

• For interoperability between ontologies
• Naive approach
• make a new vocabulary not practical
• PSI approach (Published Subject Indicators)
• maps equivalent terms to a unique ID.
• OASIS
• builds large PSI database for interoperability

source http//www.xml.com/pub/a/2002/09/11/topicm
aps.html
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ISOCat

• ISO TC37 standards
• DCR keeps all data categories.
• Each app DCS can select subset of fields.
• Each apps DCS can select subset data units.

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ISO/IEC 11179 and MDR

• MDR (meta data registry)
• stores data elements (both semantics and
  representations)
• The semantic areas describe precise definitions
• The representational areas define how the data is
  represented in a specific format such as XML
• ISO/IEC 11179 for data elements
• Registration guidelines
• Naming and Identification Principles
• Formulation of Data Definitions rules
• Classification Scheme

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Small Business Vocabulary and Business Rules

• SBVR is targeted at business rules and business
  vocabularies
• Model Driven Architecture
• SBVR meta model is automatically generated from
  SBVR vocabularies
• SBVR meta model provide standardized data
  interfaces and data interchange.
• A business vocabulary contains all the terms and
  concepts in business.

source SBVR adopted specification
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Metamodel Framework (MMF)(ISO 19763)

• Software engineering approach
• Ontology is represented in application model
• Model driven ontology build
• Goal
• to harmonize metamodel technology and contents of
  metamodel
• provide interoperability by using reference
  ontology
• Core model of the MMF
• provides a mechanism for describing each
  different metamodel in local registries
• enables registration of those to the registry
• MMF model mapping
• register mapping rules
• enable the federation among different registries

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Metamodel Framework Architecture
source ISO/IEC CD 19763-01200x(E)
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OMG ODM(Ontology Definition Metamodel)

• Includes metamodels and defines mapping between
  them
• RDFS, OWL, UML, SCL, ER, TM, DL metamodels
• Concentrates on most widely applicable and most
  readily achievable goals
• use case analysis to 3 major clusters of apps
  business, analytic, engineering app.

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Structure of ODM
source OMG/RFP ad/05-01-01
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Relation between ODM and MMF

• Each ODM metamodel is registered to MMF

source OKABE, Masao presentation in KIPONTO 2005
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Position of standards and our workscope
Meta level
MMF
ODM
SUO/SUMO MILO
TM
Ontology work guide for web contents
MDR
Domain specific
SBVR
ISOCat
General and language based
Application model driven
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Thank you very much! ?????!