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Ontology Applications

VIEWS: 4 PAGES: 12

									Ontology Applications

By
Aqeel-ur-Rehman
Ph.D. Candidate
FAST-NU, Karachi.
                                                 2/12




Ontology Application

   The topic can be discussed using
    two approaches:

       Discussing the Ontology Application
        Domains

       Discussing the Ontology integration in
        Applications (i.e. Context-aware
        Applications using Ontology)
                                       3/12


Ontology Application Domains/ Key
Areas
   Information retrieval procedure
   Knowledge representation/sharing
   Semantic Digital Libraries
   Software engineering
   Natural-Language processing
   Multi-agent systems
   Information systems in general
   Ontology based reasoning
   Policy language specification
   Database design
   Etc. etc. etc.
                                                                                        4/12




                    Information retrieval procedure

                        Agricultural Ontology Service
                         (AOS)
                             The AOS/CS will serve as a multilingual
                              repository of concepts in the
                              agricultural domain providing
                              ontological relationships and a rich,
                              semantically sound terminology.
                              the purpose of the AOS is to achieve:
                                      better indexing of resources,
                                    better retrieval of resources, and

                                    increased interaction within the
The Agricultural Ontology Service (AOS) (A Tool for Facilitating Access to Knowledge)
                                       agricultural community.
Food and Agriculture Organization of the United Nations (FAO)
Library and Documentation Systems Division, AGRIS/CARIS and Documentation Group
Rome, Italy, June 2001, Draft 5a, September 2001
                                                                                                    5/12


             Agricultural Ontology Service
             Concept Server (AOS/CS)

                Initially developed using relational
                 database
                Now new model is developed using
                 Web Ontology Language (OWL)
                The new developed model in OWL
                 will serve as a skeleton for building
                 agriculture domain ontologies.

*Lauser , B., Sini, M., Liang, A., Keizer, J. and Katz, S., “From AGROVOC to the Agricultural Ontology
Service / Concept Server. An OWL model for creating ontologies in the agricultural domain”,
Networked Knowledge Organization Systems and Services, The 5th European Networked Knowledge
Organization Systems (NKOS) Workshop, Workshop at the 10th ECDL Conference, Alicante, Spain, September
21, 2006.
                                                           6/12


Agricultural Ontology Service
Concept Server (AOS/CS)
   The multilingual issue (lexicalization) is
    handled using three levels of
    representations i.e.
       Concepts (the abstract meaning),
       Term ( language-specific lexical form) and
       Term variant ( the range of forms that can occur
        for each term

   On the Bases on the above representation
    inter-level relations are defined i.e.
       Concept to Term (has_lexicalization)
       Term to String (has_acronym,
        has_spelling_variant, has_abbreviation)
       Concept to Concept (is_a)
       Term to Term (is_synonym_of, is_translation_of)
                                               7/12


    Agricultural Ontology Service
    Concept Server (AOS/CS)



                             The Basic Model




                                URI Disambiguation
The Concept-to-
 Concept interface
                                                                       8/12


             Agricultural Ontology Service
             Concept Server (AOS/CS)




                                     Term-to-Term
    Term-to-String Interface            Interface
                                          Classification Schemes
   e.g. University of Bekkeley
    has the following variants          Model has the support of
       UCB, Cal, UC Berkeley,           two clasification schemes
        University of Calfornia at       namely AGRIS/CARIS and
        Berkeley                         FAO priority areas
       These relationships are             c_classification_scheme
        modeled as properties of
        the data type                       r_belongs_to_scheme
        r_has_term_variant                  r_has_category
                                            r_has_sub_category
                                                                                                  9/12




             Semantic Digital Libraries*
                  To provide uniform access to Digital
                   Libraries to deal with structural and
                   semantic heterogeneities

                   Three application areas of ontologies
                   (referred JeromeDL and BRICKS semantic digital
                   library projects)

                       Bibliographic Ontologies
                       Ontologies for Content Structures
                       Community-aware Ontologies
*Kruk, R.S., Haslhofer, B., Piotrowski, Westerski, A. and Woroniecki, T. “The Role of Ontologies in
Semantic Digital Libraries”, Networked Knowledge Organization Systems and Services, The 5th European
Networked Knowledge Organization Systems (NKOS) Workshop, Workshop at the 10th ECDL Conference,
Alicante, Spain, September 21, 2006.
                                                   10/12




Semantic Digital Libraries
   Bibliographic Ontologies

       Popular bibliographic description format
        are BibTeX, Dublin Core, MARC 21 etc.

       MarcOnt Ontology used in JeromeDL
        project to deal with the different
        metadata standards to describe various
        concepts on different level of
        granularity
                                                   11/12




Semantic Digital Libraries
   Ontologies for Content Structures
       By including structural concepts in
        ontologies, electronic contents can be
        retrieved.

   Community-Aware Ontologies
       In semantic digital libraries, besides
        storing contents and meta data, track of
        users, their interactions, and their
        knowledge can be incorporated into the
        systems using community-aware
        ontologies
                                                              12/12




Important Areas
   Ontologies in Software Engineering
    [Happel & Seedorf “Application of Ontologies in
     Software Engineering”, 2nd International Workshop on
     Semantic Web Enabled Software Engineering (SWESE
     2006), 5th International Semantic Web Conference (ISWC
     2006), November 6th, 2006, Athens, GA, U.S.A.]


   Ontologies in Multi-Agent Systems
    [Workshop on Ontologies in Agent Systems, 2nd
    International Joint Conference on Autonomous Agents and
    Multi-Agent Systems (AAMAS), Melbourne, Australia, 15
    July 2003]

								
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