Sartori / Sicilia / Manouselis Metadata and Semantic Research

Third International Conference, MTSR 2009, Milan, Italy, October 1-2, 2009. Proceedings
1. Auflage 2009
ISBN: 978-3-642-04590-5
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 46, 340 Seiten

Reihe: Communications in Computer and Information Science

This volume constitutes the selected paqpers of the third international conference on Metadata and Semantic Research, MTSR 2009, held in Milan, Italy, in September/October 2009. In order to give a novel perspective in which both theoretical and application aspects of metadata research contribute in the growth of the area, this book mirrors the structure of the Congress, grouping the papers into three main categories: 1) theoretical research: results and proposals, 2) applications: case studies and proposals, 3) special track: metadata and semantics for agriculture, food and environment. The book contains 32 full papers (10 for the first category, 10 for the second and 12 for the third), selected from a preliminary initial set of about 70 submissions.

Autoren/Hrsg.

Sartori, Fabio

Sicilia, Miguel-Angel

Manouselis, Nikos

Inhaltsverzeichnis

1;Preface;5
2;Organization;6
3;Table of Contents;9
4;Theoretical Research: Results and Proposals;9
4.1;VMAP: A Dublin Core Application Profile for Musical Resources;12
4.1.1;Introduction;12
4.1.2;Limitation of Metadata Standards for Musical Assets;13
4.1.3;Metadata Modelling for Musical Resources Using FRBR;15
4.1.4;Conclusions and Future Work;21
4.1.5;References;21
4.2;Usage-Oriented Topic Maps Building Approach;24
4.2.1;Introduction;24
4.2.2;An Overview of Our Multilingual Topic Map Construction Approach;25
4.2.3;The Topic Map Building and Validation Steps;27
4.2.3.1;The Topic Map Building Step;27
4.2.3.2;The Topic Map Validation Step;28
4.2.4;The Topic Map Integration Step;29
4.2.5;Related Works;31
4.2.6;Conclusion and Future Work;32
4.2.7;References;32
4.3;ManagemOnt: A Semantic Approach to Software Engineering Management Process;35
4.3.1;Introduction;35
4.3.2;Motivation;36
4.3.3;Semantic Software Engineering Processes;37
4.3.3.1;Software Engineering Management Meta-model;39
4.3.3.2;Software Engineering Management Ontology;40
4.3.4;Future Work;43
4.3.5;Conclusions;43
4.3.6;References;44
4.4;Clarifying the Semantics of Relationships between Learning Objects;46
4.4.1;Introduction;46
4.4.2;Critical Review of Relationships in LOM;47
4.4.3;Related Work;50
4.4.4;Impact of Relationships in the Metadata 1.7 Structure;52
4.4.5;Modeling Relationships;54
4.4.6;Conclusions;56
4.4.7;References;57
4.5;A Framework for Automatizing and Optimizing the Selection of Indexing Algorithms;59
4.5.1;Introduction;59
4.5.2;Related Work;60
4.5.3;A Generic Framework for Selecting Indexing Algorithms;62
4.5.3.1;Determining Indexing Algorithms According to a Query ;62
4.5.3.2;Concrete Application Domains;64
4.5.4;Application to Structured Metadata;65
4.5.4.1;Application to RDF-Based Descriptions;65
4.5.4.2;Optimizations and Discussions;67
4.5.5;Conclusion;68
4.5.6;References;69
4.6;Empirical Analysis of Errors on Human-Generated Learning Objects Metadata;71
4.6.1;Introduction;71
4.6.2;Quality of Learning Objects Metadata;72
4.6.3;Data Description;73
4.6.4;Methodology;73
4.6.4.1;Groups of Errors;73
4.6.5;Results;75
4.6.5.1;General Overview;77
4.6.5.2;Errors and Level of Knowledge about Categories;78
4.6.5.2.1;Category 3.Meta-metadata:;78
4.6.5.2.2;Category 9.Classification:;79
4.6.6;Conclusions and Future Work;80
4.6.7;References;81
4.7;Analysis of Educational Metadata Supporting Complex Learning Processes;82
4.7.1;Introduction;82
4.7.2;Design, Execution and Control of Complex Learning Processes;83
4.7.2.1;Related Work on Learning Process Design and Execution;83
4.7.2.2;An Extended Characterization of Complex Learning Processes;85
4.7.3;Workflow Control Patterns-Based Analysis of EMLs;85
4.7.3.1;Workflow Control Patterns;86
4.7.3.2;Learning Process Analysis Based on Workflow Control Patterns;87
4.7.4;Case Study: Wrapping a Learning Design with LPCEL Metadata Primitives;90
4.7.5;Conclusions;91
4.7.6;References;92
4.8;A Fine-Grained Metric System for the Completeness of Metadata;94
4.8.1;Introduction – Related Work;94
4.8.2;A Metric System for Completeness;96
4.8.2.1;Introducing Completeness at the Field Level;97
4.8.2.2;Measuring Completeness at the Field Level;98
4.8.2.3;Extending Completeness Metrics at the Representation Level;100
4.8.3;A Discussion of the Proposed Metrics;102
4.8.4;Conclusion – Future Work;104
4.8.5;References;104
4.9;Unified Semantic Search of Data and Services;106
4.9.1;Introduction;106
4.9.2;Motivating Scenario and Running Example;107
4.9.3;Building the Global Data and Service View at Set-Up Time;109
4.9.3.1;Building an Integrated Representation of eServices: The GLSO;109
4.9.3.2;Mapping of Data and Service Ontologies;112
4.9.4;Data and eService Retrieval;113
4.9.4.1;eService Retrieval;114
4.9.5;Related Work;116
4.9.6;Conclusion and Future Work;117
4.9.7;References;117
4.10;Preliminary Explorations on the Statistical Profiles of Highly-Rated Learning Objects;119
4.10.1;Introduction;119
4.10.2;Quantitative, Measurable Aspects of Learning Objects;121
4.10.3;Preliminary Empirical Study;121
4.10.3.1;Method;122
4.10.3.2;Results;123
4.10.4;Discussion;123
4.10.5;Conclusions and Outlook;126
4.10.6;References;127
5;Applications: Case Studies and Proposals;10
5.1;A Semantic Web Based System for Context Metadata Management;129
5.1.1;Introduction;130
5.1.2;Related Work;130
5.1.3;Semantic Web Based System for Context Metadata Management;132
5.1.3.1;System Architecture;132
5.1.3.1.1;Context module.;132
5.1.3.1.2;History module.;133
5.1.3.1.3;Rules module.;133
5.1.3.1.4;Inference module.;133
5.1.3.1.5;Input module.;133
5.1.3.1.6;Output module.;133
5.1.3.1.7;Translation module.;133
5.1.3.1.8;User interface module.;134
5.1.3.2;Module Interactions;134
5.1.3.3;Context Model;135
5.1.4;Case Study;137
5.1.5;Conclusions and Future Work;138
5.1.6;References;139
5.2;An XML Pipeline Based System Architecture for Managing Bibliographic Metadata;141
5.2.1;Introduction;141
5.2.2;Background;143
5.2.3;XML Metadata Format;144
5.2.4;System Architecture;145
5.2.5;Implementing the System in Practice;150
5.2.6;Conclusions;150
5.2.7;References;151
5.3;DataStaR: Bridging XML and OWL in Science Metadata Management;152
5.3.1;Introduction;152
5.3.2;Motivation and General Approach;153
5.3.3;XML Schemas and OWL: Background and Related Work;154
5.3.4;First Application: Ecological Metadata;155
5.3.5;System Implementation;156
5.3.5.1;Generation of Editing and Display Interfaces;156
5.3.5.2;Hidden XML Semantics;158
5.3.6;Ongoing Work;158
5.3.6.1;Multiple Formalisms and DL Compatibility;158
5.3.6.2;Ordering of Axioms;159
5.3.7;Evaluation;159
5.3.7.1;A Particular Advantage of XML Tools – Handling Text Markup;160
5.3.8;Conclusion;160
5.3.9;Funding Acknowledgement and Disclaimer;160
5.3.10;References;161
5.4;Structured Metadata for Representing and Managing Complex ‘Narrative’ Information;162
5.4.1;Introduction;162
5.4.2;General Backaground;163
5.4.2.1;Narratology and Related Disciplines;163
5.4.2.2;Present (and Past) Solutions for Representing Narratives;165
5.4.3;A Short Description of NKRL;166
5.4.3.1;The Knowledge Representation Aspects;166
5.4.3.2;The Querying and Inferencing Aspects;170
5.4.4;Conclusion;174
5.4.5;References;174
5.5;A Semantic Web Framework to Support Knowledge Management in Chronic Disease Healthcare;175
5.5.1;Introduction;175
5.5.2;Healthcare Knowledge Management for Chronic Disease;176
5.5.3;Ontology-Based Healthcare Knowledge Management Framework;177
5.5.3.1;Knowledge Resources;177
5.5.3.2;Ontology Development;177
5.5.3.3;Evidence-Based Healthcare Resource Repository;179
5.5.4;Discussion;180
5.5.5;References;180
5.6;Ontological Enrichment of the {\it Genes-to-Systems Breast Cancer} Database;182
5.6.1;Introduction;182
5.6.2;Background;183
5.6.3;Methods;185
5.6.3.1;Ontologies;185
5.6.4;The Ontology Based G2SBC;185
5.6.4.1;Ontologies Description;185
5.6.4.2;The Ontology Layer Implementation;186
5.6.5;Discussion;187
5.6.5.1;Improvement Related to Ontologies Exploitation;189
5.6.6;Conclusions;191
5.6.6.1;Acknowledgments.;192
5.6.7;References;192
5.7;An Ontology Based Approach to Information Security;194
5.7.1;Introduction;194
5.7.2;Overview of Information Security;196
5.7.3;Ontology Based Applications in the Knowledge Management;197
5.7.4;Ontological Needs in Information Security;198
5.7.5;IS Ontology Conceptual Model;199
5.7.6;Conclusions and Future Work;201
5.7.7;References;202
5.8;Reusability Evaluation of Learning ObjectsStored in Open Repositories Based on Their Metadata;204
5.8.1;Introduction;204
5.8.2;Learning Object Evaluation;205
5.8.3;Learning Object Reusability Metrics Based on Metadata Records;205
5.8.3.1;Cohesion;206
5.8.3.2;Size and Complexity;207
5.8.3.3;Portability;207
5.8.4;Quality Evaluation in the Use of Metadata in Repositories eLera and Merlot;208
5.8.4.1;Source of Metadata;209
5.8.4.2;Correspondence between eLera, Merlot and LOM Metadata Elements;209
5.8.4.3;Unstructured Metadata;210
5.8.4.4;Different Value Spaces;211
5.8.4.5;Metadata Completeness;211
5.8.5;Conclusions;212
5.8.6;References;212
5.9;A Comparison of Methods and Techniques for Ontological Query Expansion;214
5.9.1;Introduction;214
5.9.2;State of the Art;216
5.9.2.1;A Definition of Query Expansion;216
5.9.2.2;Query Expansion Methods;217
5.9.3;Towards a Platform for QE: Implementation;219
5.9.3.1;Type of Ontologies: Thesauri;219
5.9.3.2;Definition of the Ontology Representation Language: SKOS;220
5.9.3.3;Platform Architecture;220
5.9.4;Testing;222
5.9.5;Conclusions;223
5.9.6;References;224
5.10;Exploring Characterizations of Learning Object Repositories Using Data Mining Techniques;226
5.10.1;Introduction;226
5.10.2;Methodology;227
5.10.2.1;Criteria for LOR Selection;227
5.10.2.2;Data Collection;228
5.10.2.3;Preprocessing;228
5.10.2.4;Application of Data Mining Techniques;228
5.10.3;Potential Applications;234
5.10.4;Conclusions;234
5.10.5;References;235
6;Special Track: Metadata and Semantics for Agriculture, Food and Environment;10
6.1;Assuring the Quality of Agricultural Learning Repositories: Issues for the Learning Object Metadata Creation Process of the CGIAR;237
6.1.1;Introduction;237
6.1.2;Issues in Approaching the Nature of Quality in Education;238
6.1.3;Addressing Quality Metadata;239
6.1.4;Quality Assurance for LOM of the CGIAR;242
6.1.5;Conclusion;245
6.1.6;References;246
6.2;Ontology Design Parameters for Aligning Agri-Informatics with the Semantic Web;250
6.2.1;Introduction;250
6.2.2;Design Parameters;251
6.2.2.1;Purposes of the Ontologies;251
6.2.2.2;Reusing Ontologies and Ontology-Like Artefacts;251
6.2.2.3;Bottom-Up Development of Ontologies through Ontology Learning;253
6.2.2.4;Representation Languages and Reasoning Services;253
6.2.3;Conclusions;254
6.2.4;References;255
6.3;Developing an Ontology for Improving Question Answering in the Agricultural Domain;256
6.3.1;Introduction;256
6.3.2;Related Work;258
6.3.3;Improving Question Answering for the Agricultural Domain;259
6.3.3.1;The RCCA Journal as Agricultural Domain;260
6.3.3.2;Ontology Construction;260
6.3.3.3;The AGROVOC Thesaurus and WordNet;261
6.3.3.4;Alignment between Ontology and Domain Terminology;262
6.3.3.4.1;Calculating Weights.;264
6.3.4;Experiments and Results;264
6.3.5;Conclusions and Future Work;266
6.3.6;References;266
6.4;A Service Architecture for Facilitated Metadata Annotation and Ressource Linkage Using agroXML and ReSTful Web Services;268
6.4.1;Introduction;268
6.4.2;Materials and Methods;268
6.4.2.1;Prototype;270
6.4.3;Discussion ;271
6.4.4;Outlook;273
6.4.5;References;273
6.5;A Water Conservation Digital Library Using Ontologies;274
6.5.1;Introduction;274
6.5.2;Ontology Development Methodology;275
6.5.2.1;Specification and Conceptualization;275
6.5.2.2;Formalization and Implementation;276
6.5.3;Ontology Application;276
6.5.3.1;Top Level Ontology;277
6.5.3.2;Domain Specific Ontology;277
6.5.3.3;System Architecture;278
6.5.4;Preliminary Conclusions;279
6.5.5;References;280
6.6;Evaluation of a Metadata Application Profile for Learning Resources on Organic Agriculture;281
6.6.1;Introduction;281
6.6.2;Background;282
6.6.2.1;Generic Process for AP Development;282
6.6.2.2;Evaluating the Application Profile;283
6.6.2.3;Revisiting the Process;284
6.6.3;Development of a LOM-Based AP for Organic Agriculture and Agroecology and Evaluation Study;285
6.6.3.1;Pilot Experiment Settings;285
6.6.3.2;Results;286
6.6.3.3;AP Revisions;288
6.6.4;Conclusions;289
6.6.5;References;290
6.7;Ontology for Seamless Integration of Agricultural Data and Models;293
6.7.1;Introduction;293
6.7.2;Ontologies in Integrated Assessment Studies;294
6.7.2.1;The Seamless Integrated Project;294
6.7.2.2;A Platform for Agro-Environmental Impact Assessments: SeamFrame;295
6.7.3;Ontology Development for Scientific Workflows;295
6.7.3.1;Model Chains and Scales – Interoperability Issues;295
6.7.3.2;Community Ontology Development in Seamless-IP;296
6.7.4;The Seamless Ontologies;296
6.7.4.1;The Seamless Model Chain;296
6.7.4.2;Crops and Products Ontology;297
6.7.4.3;Farm Ontology;298
6.7.4.4;Production Enterprise;298
6.7.4.5;Agricultural Activities;299
6.7.4.6;Economic Valuation of Agricultural Activities and Optimal Farmer Behaviour;300
6.7.4.7;Agricultural Policy Assessment;300
6.7.4.8;Assessment Project Ontology;301
6.7.5;Contribution of Ontology Development in Software Engineering Tasks;302
6.7.5.1;Cross-Programming Language Transliterations;302
6.7.5.2;Persistent Storage of Simulation Results;303
6.7.5.3;Documentation of Source Code and Database Schemas;303
6.7.6;Discussion;303
6.7.7;References;304
6.8;Assessment of Food and Nutrition Related Descriptors in Agricultural and Biomedical Thesauri;305
6.8.1;Introduction;305
6.8.2;Materials and Methods;306
6.8.2.1;Thesauri and Databases under Study;307
6.8.3;Results;308
6.8.3.1;Descriptors Related to Food in General;308
6.8.3.2;Descriptors Related to Vegetables;309
6.8.3.3;Descriptors Related to Milk;312
6.8.3.4;Descriptors Related to Seafoods;312
6.8.4;Discussion and Conclusions;314
6.8.5;References;315
6.9;Networked Ontologies from the Fisheries Domain;317
6.9.1;Introduction;317
6.9.2;The Process of Reengineering Reference Data for Time Series;319
6.9.3;The First Network of Fisheries Ontologies;319
6.9.4;Conclusions and Future Work;321
6.9.5;References;322
6.10;Improving Information Exchange in the Chicken Processing Sector Using Standardised Data Lists;323
6.10.1;Introduction;323
6.10.2;Method;324
6.10.3;Results;326
6.10.4;Discussion;328
6.10.5;References;331
6.11;Navigation as a New Form of Search for Agricultural Learning Resources in Semantic Repositories;333
6.11.1;Introduction;333
6.11.2;Technical Foundations;334
6.11.2.1;Overall Architecture of Organic.Edunet;334
6.11.2.2;Semantic Technologies;335
6.11.3;Semantic Search;335
6.11.4;Conclusions;337
6.11.5;References;337
7;Author Index;339