Developing Ontologies for Knowledge Management

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Developing Ontologies for Knowledge Management

• Atilla ELÇI
• Dept. of Computer Engineering
• Eastern Mediterranean University

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Knowledge Management Topics

• Motivation
• Terms Definitions
• Roles of ontologies
• PROTON ontology as bases for KM / SemWeb Apps

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Motivation

• Knowledge Representation (KR)
• A world view Building models of a
  domain/problem which allow for automatic
  reasoning and interpretation.
• gt Formal semantics (Ontology!)
• gt Machine-interpretable meaning
• Semantic repository
• Storage, querying, and management of structured
  data
• DBMS vs Ontology-based
• O-B provides depth of meaning not available
  through DBMS

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Terminology KM views

• What Is Knowledge Management by the The Knowledge
  Management Forum (KMForum)
• Read through these personal views on K KM
• Note the diversity of views interests
• Contrast cross-check definitions of some
  viewers.

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Terminology

• Dublin Core Metadata Initiative (DCMI, DC)
  interoperable online metadata standards
• Dataset a set of structured data (list, table,
  DB, etc.) useful for direct software processing
• Ontology
• Paradigm for KR in AI.
• Conceptual schemata
• Formal ontology as logical formalism as in OWL
• Schemata or inteligent views over information
  resources
• For indexing, querying, and referencing
  non-ontological datasets
• For DB, Document Mngt Sys, Catalog, OLAP,

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Terminology (continued)

• Ontology classification based on generality of
  conceptualization
• Upper-level ontology
• A general model suitable for large variety of
  tasks, domains, and application areas. Can be
  used to line up independently developed
  ontologies if linked to it.
• Domain ontology
• For specific domain of interest
• App / Task ontology
• For a specific range of applications / tasks.
• Knowledge base (KB)
• A dataset with formal semantics and knowledge
  representation allowing automatic inference.
• Ontology OltC, R, I, Agt where
• C is the set of classes
• R is the set of relations among the classes
• I is the set of instances from the domain.
  Instances belong to classes
• A is the set of axioms (say, business rules).

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Terminology (continued)

• Ref ontology definition as O-grammar, the issue
  of what is instance what is schema definition may
  not always easily resolved.
• Data qualia A data quale is an orthogonal
  quality of data that may be used for independent
  classification
• Semantics whether it is formally represented
• Structure if the data is formally structured
• Schema data that determines shape and/or meaning
  of ontology data.
• Sorts of data (_ stands for any value not
  determined)
• Data (_,_,_), ie. Any sort of collection of data
• Dataset (_,structured,_)
• Knowledge Base (semantic,structured,_)
• Ontology (semantic,structured,schema)
• Non-semantic schemata (nonsemantic,structured,sch
  ema)
• Database (nonsemantic,structured,schema)
• Mixed datasets (_,structured,schemanon-schema)
• Content (_,non-structured,_)
• Metadata data on data, annotation, ... How to
  represent in (?,?,?)?
• Semi-structured data

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Terminology (continued)

• Sorts of data (continued)
• Semi-structured data
• KR/NLP ? Docs containing free text fragments in
  structured according to some schema
• DB ? Data of non-relational data model.
• Ref. Fig. 7.2- Structured vs semantic positioning
  of various sorts of data.

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Roles of Ontologies

• Ontology as Database Schema
• May not contain instance data.
• Such as RDBMS schema.
• Ontology as Topic Hierarchy
• Classification for various purposes
• DCMI and library classification
• Yahoo DMoz taxonomies for Web data
• See Section 4 in this for depth of Yahoo!
  Directory.
• Compare Topic-Ontology versus Schema-Ontology
  (Sect. 7.5)
• Ontology as Enterprise Resource Model
• Ref. Ontolog Database Ontology Mini-Series.

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Mapping Querying Disparate Knowledge Bases

• Self study Davies 6.3

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PROTON (PROTo ONtology) Ontology

• A light-weight uppper-level ontology to serve as
  model bases for information science community
  for, for example
• Seed for ontology generation
• Automatic entity recognition information
  extraction
• Metadata generation / semantic annotation.
• Design Rationale
• For usage in KM SemWeb appls
• Light-weight for being unrestrictive
• Prefers not to deal with time space
• Low-cost of adoption maintenance
• Scalable reasoning

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PROTON (contiuned)

• Consists of 300 classes 100 properties for
• Semantic annotation
• Indexing, and retrieval.
• Design principles
• Domain independence
• Light-weight logical definitions
• Alignment with popular metadata standards
• Good collection of named entity types (people,
  organizations, locations, numbers, dates,
  addresses.
• Structure
• In OWL Lite
• In four modules System, Top, Upper, and
  Knowledge Management (KM)
• Organized á la DILIGENT Methodology,

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PROTON (contiuned)

• Scope
• Developed in the SEKT Project through sampling of
  a corpus of general news.
• General entity types appearing commonly (Person,
  Location, Organization, Money, Date, ...) are in
  PROTON Top.
• KM aspects stems from
• KIMO of KIM Project
• OpenCyc
• Wordnet
• DOLCE
• EuroWordnet
• Voluntary compliance with
• Dublin Core
• Automatic Content Extraction annotation types
• Alexandria Digital Library Feature Type Thesaurus
• Future compliance with FOAF and other popular
  standars ontologies.

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PROTON (contiuned)

• Architecture
• Site at Semanticweb.org
• Organized in three levels Basic, Top, Upper
• In four modules
• System (basic protons...) application ontology
  meant for use by ontology-based software
• Top (top protont...) abstractions
• Upper (upper protonu...) specific cases
• KM (upper protonkm...) specific cases

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PROTON (contiuned)

• KM module for application-specific extension of
  PROTON
• Information Spacecollection of themed info
  resources
• Software Agent specialized Agent
• User User and UserProfile
• Profile
• User Profile
• Mention name droppings, references to (private)
  instances
• Weighted Term relates objects to numbers
• Device references to user devices.

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Organizations

• The Knowledge Management Forum (KMForum)
• Virtual community of practice focused on
  furthering fundamental theories, methods and
  practices. Features archives and news.
• What Is Knowledge Management
• KM Forum
• Boston Knowledge Management Forum A Community of
  Practice Learning and Working in the Knowledge
  Management Community
• KnowledgeBoard
• Forum to establish a community and to support and
  identify commonality in terminology, application
  and implementation. Features news, workshops, a
  library, ...

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Conferences

• Knowledge Representation Ontology Workshop (KROW
  2008).
• Eleventh International Conference on Principles
  of Knowledge Representation and Reasoning (KR
  2008),
• Sydney, Australia, September 16 - 19, 2008

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Commercial Conferences

• Knowledge Base Publishing course series of the
  Montague Institute includes articles
• Introduction to Knowledge Base Publishing
• Taxonomies, search Sharepoint
• Metadata and search
• Integrating taxonomies
• Information modeling and metadata management
• See also Roundtables, for example the following
• Benchmarking Sharepoint for KM (December 12,
  2007)
• Six weeks to the Semantic Web (November 7, 2007)
• Integrating folksonomies with Google (October 17,
  2007)
• Migrating metadata to the Semantic Web (September
  5, 2007)

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References

• John Davies, Rudi Studer, Paul Warren (Editors)
  Semantic Web Technologies Trends and Research in
  Ontology-based Systems, John Wiley Sons (July
  11, 2006). ISBN 0470025964. Ch. 7. pp. 115-138.
• W3C Semantic Web Tools Wiki page
• Check ...