introduction into meta data model 2010-07-02

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Page 1: Introduction into meta data model 2010-07-02

27.01.2010 School of Computer Science & Statistics, Trinity College Dublin 1

University of DublinTrinity College

Introduction

Meta-Data Model for Ontology Mapping Management

Page 2: Introduction into meta data model 2010-07-02

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:

[email protected]

Page 3: Introduction into meta data model 2010-07-02

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

Page 4: Introduction into meta data model 2010-07-02

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

Page 5: Introduction into meta data model 2010-07-02

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

Page 6: Introduction into meta data model 2010-07-02

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

Page 7: Introduction into meta data model 2010-07-02

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

Page 8: Introduction into meta data model 2010-07-02

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