introduction into meta data model 2010-07-02
TRANSCRIPT
27.01.2010 School of Computer Science & Statistics, Trinity College Dublin 1
University of DublinTrinity College
Introduction
Meta-Data Model for Ontology Mapping Management
27.01.2010 School of Computer Science & Statistics, Trinity College Dublin 2
University of DublinTrinity College
1. Character Phase (1/2)
Target and the source ontology are identified: Ontology Name: a label for the ontology
Ontology on Animals Ontology Source: Where can I find the ontology file?
www.wikipedia.org/animal.owl Ontology PSI: Unique identifier
www.ontologies.org/animal Ontology creation date: 2010-05-04 Ontology author: name:Hendrik, email:
27.01.2010 School of Computer Science & Statistics, Trinity College Dublin 3
University of DublinTrinity College
1. Character Phase (2/2)
Target and the source ontology are characterizes: Ontology language: Format of the ontology
OWL DL, RDF Ontology size: How big is the ontology
5 classes, 10 individuals Ontology style: What does the ontology look like
deep hierarchy , flat hierarchy, network
27.01.2010 School of Computer Science & Statistics, Trinity College Dublin 4
University of DublinTrinity College
2. Matching Phase (1/2)
Describes the method used to identify the candidates: Method: How were the candidates found?
manual selection or automated algorithm Date of selection: When was selection performed
2010-05-06Describes the manual selection: Selectors: Who did the selections?
Hendrik, Andre, Declan (contact details) Selectors background: relevant details about selectors
Selectors had experience in Semantic Web Selection process: details about the selection process
Selectors analyzed all ontology elementsSelectors group equal elements based on name similarity
27.01.2010 School of Computer Science & Statistics, Trinity College Dublin 5
University of DublinTrinity College
2. Matching Phase(2/2)
Describes the automated matching: Algorithm name: human-readable label
String comparison Algorithm implementation:
org.jena.stringComparsion Selection process: details of selection process
Matching based on string similarity
27.01.2010 School of Computer Science & Statistics, Trinity College Dublin 6
University of DublinTrinity College
3. Mapping Phase (2/2)
Describes the mapping context: Mapping objective: What is the purpose/aim of the mappings?
Enable knowledge exchange between ontologies Mapping requirements: What rules have to be followed?
Do not map product ids Mapping context: What is the context?
Mapping is created for Wikipedia.deMapping is used for a demonstrator
Describes the mapping process: Mapping process: details about the mapping process
Confirm mapping with similarity rating of > 0.5 % Date of mapping: When was selection performed
2010-05-06
27.01.2010 School of Computer Science & Statistics, Trinity College Dublin 7
University of DublinTrinity College
4. Execution Phase
Describes the application of the mapping: Mapping format:
INRIA RDF Mapping users: Known users of the mappings
Hendrik Thomas Application using mapping: Known application
which used the mappingsWikipedia.de/mapMe
27.01.2010 School of Computer Science & Statistics, Trinity College Dublin 8
University of DublinTrinity College
5. Management Phase
Describes the sharing of the mapping: Source of the mapping file:
www.mapme.org/m.rdf Hashkey: unique key of mappings
23434534646456456 LastChange:
2010-06-03 Change notification:
www.mapme.org/changes.rss