An Approach to Formalizing Ontology Driven Semantic Integration: Concepts, Dimensions and Framework Wenlong Gao

Total Page:16

File Type:pdf, Size:1020Kb

An Approach to Formalizing Ontology Driven Semantic Integration: Concepts, Dimensions and Framework Wenlong Gao Florida State University Libraries Electronic Theses, Treatises and Dissertations The Graduate School 2012 An Approach to Formalizing Ontology Driven Semantic Integration: Concepts, Dimensions and Framework Wenlong Gao Follow this and additional works at the FSU Digital Library. For more information, please contact [email protected] THE FLORIDA STATE UNIVERSITY COLLEGE OF COMMUNICATION AND INFORMATION AN APPROACH TO FORMALIZING ONTOLOGY DRIVEN SEMANTIC INTEGRATION: CONCEPTS, DIMENSIONS AND FRAMEWORK By WENLONG GAO A Dissertation submitted to the School of Library and Information Studies In partial fulfillment of the requirements for the degree of Doctor of Philosophy Degree Awarded: Spring Semester, 2012 Wenlong Gao defended this dissertation on December 9, 2011 The members of the supervisory committee were: Corinne Jörgensen Professor Directing Dissertation Daniel Schwartz University Representative Ian Douglas Committee Member Besiki Stvilia Committee Member The Graduate School has verified and approved the above-named committee members and certifies that the dissertation has been approved in accordance with university requirements. ii For my parents, I could not have done this without you. iii ACKNOWLEDGEMENTS This dissertation could not have been completed without the tremendous support and help of my dissertation committee, friends and family. First, I would like to thank Dr. Corinne Jörgensen, my dissertation chair and mentor. You supported me through this entire process, and encouraged me whenever I encountered challenges. I will always appreciate the trust and confidence you placed in me. It has been an honor and privilege to be your doctoral student. Second, I am thankful for other committee members, Dr. Ian Douglas, Dr. Besiki Stvilia, Dr. Daniel Schwartz, who inspired me not only throughout the dissertation development but also though my personal academic development. Your thoughtful guidance and insightful reasoning helped me explore this amazing area and opened the doors to many brilliant ideas to improve my work. Furthermore, I am grateful to all friends, staff and faculties of School of Library and Information Studies who ever helped during my study at FSU. I had a wonderful time here and worked with the most diligent and creative people in the past years. Their sincerity, assistance and encouragement would be the invaluable memory of my life. Finally I would like to thank my father and my mother who always support me with their unconditioned and unlimited love. They guided me through all of ups and downs in my life. These past years have not been easy, and I would not have succeeded in this endeavor without such a remarkable family by my side. iv TABLE OF CONTENTS LIST OF TABLES ........................................................................................................... viii LIST OF FIGURES .......................................................................................................... ix ABSTRACT ...................................................................................................................... x CHAPTER 1 INTRODUCTION ........................................................................................ 1 1.1 Background ........................................................................................................... 1 1.2 Research Questions and Objectives ..................................................................... 4 1.3 Outline of Dissertation ........................................................................................... 6 CHAPTER 2 ANALYSIS OF SEMANTIC HETEROGENEITY ......................................... 7 2.1 The Levels of Heterogeneity ................................................................................. 7 2.2 Different Semantic Levels ................................................................................... 12 CHAPTER 3 THE RELATIONSHIP OF DATABASE AND ONTOLOGY DRIVEN SEMANTIC INTEGRATIONS ......................................................................................... 15 3.1 Rule-based and Learning Based Schema Matching ........................................... 15 3.2 Other approaches of semantic integration in database research ....................... 18 3.3 The Evolution of Ontology ................................................................................... 19 3.3.1 Definition of Ontology ............................................................................... 20 3.3.2 The Relationship Between Taxonomy, Controlled Vocabulary and Ontology .................................................................................................................. 22 3.3.3 Methodologies for Ontology Development ................................................ 25 3.3.4 Upper Ontology and WordNet .................................................................. 33 v 3.4 Ontology in syntax and structure levels .............................................................. 36 3.4.1 The comparison of database schemas and ontologies ............................ 36 3.4.2 Mapping between the syntax and semantics ............................................ 38 3.4.3 The relationship of Ontology, Description Logic and the Semantic Web . 42 CHAPTER 4 ONTOLOGY DRIVEN INTEGRATION APPROACHES ........................... 49 4.1 Different Interpretations of Semantic Integration ................................................ 50 4.2 Different Ontology Implementations .................................................................... 52 4.2.1 Single Ontology Approach ........................................................................ 54 4.2.2 Multiple Ontology Approach ...................................................................... 57 4.2.3 Hybrid Ontology Approach ........................................................................ 58 4.3 Different Integration Approaches ........................................................................ 59 4.3.1 Relating Ontologies to Information Sources ............................................. 59 4.3.2 Inter-Ontology Mapping ............................................................................ 60 4.3.3 Linked Data Approach .............................................................................. 71 4.3.4 Various Matching Approaches .................................................................. 74 4.4 Various Evaluation Frameworks ......................................................................... 77 CHAPTER 5 DIMENSION CONSTRUCTION ............................................................... 85 5.1 Ontology Encoding Dimension ............................................................................ 85 5.2 Conceptual Dimension ........................................................................................ 91 5.3 Application Dimension ........................................................................................ 96 5.3.1 Query and Inference Language ................................................................ 96 5.3.2 Ontology Development Methodology ........................................................ 97 vi 5.3.3 Ontology Development Tools ................................................................... 98 5.3.4 Linked Data and Upper Ontologies ......................................................... 101 5.4 Evaluation Dimension ...................................................................................... 103 CHAPTER 6 FRAMEWORK CONSTRUCTION AND UTILIZATION ......................... 108 6.1 The Three Scales of The Framework .............................................................. 108 6.2 The Framework Utilization ............................................................................... 111 6.2.1 Decompose Ontology Encoding Dimension ........................................... 111 6.2.2 Decompose Conceptual Dimension ...................................................... 112 6.2.3 Decompose Application Dimension ........................................................ 114 6.2.4 Decompose Evaluation Dimension ......................................................... 119 6.4 In-depth Review of Operation Mechanism ........................................................ 124 6.5 Conclusion and Future Work ............................................................................ 135 REFERENCES ............................................................................................................. 139 BIOGRAPHICAL SKETCH ........................................................................................... 158 vii LIST OF TABLES Table 1: Concepts Formalization .................................................................................... 95 Table 2: Summary of Ontology Driven Semantic Integration Systems (Part I) ............. 132 Table 3: Summary of Ontology-Driven Semantic Integration Systems (Part II) ........... 133 Table 4: Component Counts ........................................................................................ 134 viii LIST OF FIGURES Figure 1: Semantic Levels .............................................................................................. 13 Figure 2: Using OntoKick to Capture Competency Questions ....................................... 31 Figure 3: Mapping between syntax and Semantics ........................................................ 39 Figure 4: From Simple to Complex Semantics ............................................................... 40 Figure 5: More elaborate semantics ..............................................................................
Recommended publications
  • Automated Ontology Creation Using XML Schema Elements
    Automated Ontology Creation using XML Schema Elements Samuel Suhas Singapogu, Paulo C. G. Costa, J. Mark Pullen C4I center, George Mason University Fairfax, VA, USA [ssingapo,pcosta,mpullen]@c4i.gmu.edu Abstract—Ontologies are commonly used to represent formal semantics in a computer system, usually capturing them in the Although ontologies are valuable assets in system model- form of concepts, relationships and axioms. Axioms convey ing, testing and analysis, the process of manually creating an asserted knowledge and support inferring new knowledge ontology for a complex system is inherently tedious and through logical reasoning. For complex systems, the process of error prone. Existing methods of knowledge discovery and creating ontologies manually can be tedious and error-prone. ontology creation usually are based on text mining of a data Many automated methods of knowledge discovery are based on mining domain text corpus, but current state-of-the-art meth- corpus for that domain. XML-based systems capture the ods using this approach fail to consider properly semantic data structure and syntax of all necessary and meaningful ele- embedded in XML schemata in complex systems. This paper ments in a XML schema, which therefore is a useful starting proposes a mapping method for identifying relevant semantic point for semantic analysis. In such systems, XML schemata data in XML schemata, automatically structuring and repre- have been shown to be a valuable resource of semantic data senting it in the form of a draft ontology. Concepts, concept [2]. Command and Control systems in the military context hierarchy and domain relationships from XML schema are support various functions, including commanding of forces mapped to relevant parts of an OWL ontology.
    [Show full text]
  • Towards a Conceptual Framework for Persistent
    Nova Southeastern University NSUWorks CEC Theses and Dissertations College of Engineering and Computing 2017 Towards a Conceptual Framework for Persistent Use: A Technical Plan to Achieve Semantic Interoperability within Electronic Health Record Systems Shellon Blackman-Lees Nova Southeastern University, [email protected] This document is a product of extensive research conducted at the Nova Southeastern University College of Engineering and Computing. For more information on research and degree programs at the NSU College of Engineering and Computing, please click here. Follow this and additional works at: https://nsuworks.nova.edu/gscis_etd Part of the Computer Sciences Commons Share Feedback About This Item NSUWorks Citation Shellon Blackman-Lees. 2017. Towards a Conceptual Framework for Persistent Use: A Technical Plan to Achieve Semantic Interoperability within Electronic Health Record Systems. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, College of Engineering and Computing. (998) https://nsuworks.nova.edu/gscis_etd/998. This Dissertation is brought to you by the College of Engineering and Computing at NSUWorks. It has been accepted for inclusion in CEC Theses and Dissertations by an authorized administrator of NSUWorks. For more information, please contact [email protected]. Towards a Conceptual Framework for Persistent Use: A Technical Plan to Achieve Semantic Interoperability within Electronic Health Record Systems By Shellon M. Blackman-Lees A dissertation report submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Information Systems College of Engineering and Computing Nova Southeastern University 2017 An Abstract of a Dissertation Submitted to Nova Southeastern University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Towards a Conceptual Framework for Persistent Use: A Technical Plan to Achieve Semantic Interoperability within Electronic Health Record Systems by Shellon M.
    [Show full text]
  • Transforming Recursive Relationships to OWL2 Components
    (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 10, No. 10, 2019 Ontology Learning from Relational Databases: Transforming Recursive Relationships to OWL2 Components 1 Mohammed Reda CHBIHI LOUHDI Hicham BEHJA2 Research Laboratory on computer science innovation (LRII) LRI - Laboratory Faculty of Science Aïn Chock Casablanca ENSEM, Hassan II University Hassan II University, Casablanca, Morocco Casablanca, Morocco Abstract—Relational databases (RDB) are widely used as a ontologies provide classes, properties, individuals, and data backend for information systems, and contain interesting values and are stored as Semantic Web documents [3]. structured data (schema and data). In the case of ontology learning, RDB can be used as knowledge source. Multiple There are many approaches that transform a RDB to an approaches exist for building ontologies from RDB. They mainly ontology. Three main techniques are used: (1) Reverse use schema mapping to transform RDB components to Engineering, to convert the relational model to the conceptual ontologies. Most existing approaches do not deal with recursive model (which is considered as semantically richer than the relationships that can encapsulate good semantics. In this paper, relational model) or to retrieve lost information during the two technics are proposed for transforming recursive transformation of the conceptual model to the relational model, relationships to OWL2 components: (1) Transitivity mechanism (2) Schema Mapping, to convert relational model components and (2) Concept Hierarchy. The main objective of this work is to to ontology components, through the use of transformation build richer ontologies with deep taxonomies from RDB. rules and (3) Data Mining to analyze stored data in order to enrich the ontology.
    [Show full text]
  • Ontology Life Cycle: a Survey on the Ontology and Its Development Steps
    International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Index Copernicus Value (2015): 78.96 | Impact Factor (2015): 6.391 Ontology Life Cycle: A Survey on the Ontology and its Development Steps Eiman Alsiddig Altayeb Ibrahim1, Mohammed Awad Mohammed Ataelfadiel2 1Sudan University of Science and Technology, College of Computer Science and Information Technology, Khartoum – Sudan 2Computer Science dept. AL-Imam MuhommedIbn Saud Islamic University, AL-Ahsa, Kingdom of Saudi Arabia Abstract: In the last decades, the turnout has become great for the use of ontology in various fields, such as web technologies, database integration, multi agent systems, natural language processing, etc... The main goal of this paper is to answer generic questions about ontologies, such as: What is the ontology? Which are the different Types of ontologies? What is the purpose of the use of ontologies in an application? Which methods can I use to build ontology? During the paper we discussed the definition of Ontology, types of ontologies (Formal and Informal ontology) and its Component.Also, highlighted some of the languages used in the construction of the Ontologies beside the ontology Building Tools. In addition, we listed the agreed steps for building the Ontology. In conclusion, we did not overlook to mention some of the Ontology projects specifically in Holy Quran Domain. Keywords: Ontology Definition, Ontology Types, Ontology Building Tools, Ontology languages, Ontology components, Ontology Engineering 1. Introduction 2. Ontology Definition Historically, ontologies arise out of the branch of philosophy There are many interpretations about what ontology is. In fact, known as metaphysics, which deals with the nature of reality – hot discussions are often done in many meetings on ontology.
    [Show full text]
  • Semantic Web and Peer-To-Peer Steffenstaab·Heinerstuckenschmidt(Eds.) Semantic Web and Peer-To-Peer
    Semantic Web and Peer-to-Peer SteffenStaab·HeinerStuckenschmidt(Eds.) Semantic Web and Peer-to-Peer Decentralized Management and Exchange of Knowledge and Information With 89 Figures and 15 Tables 123 Editors Steffen Staab University of Koblenz Institute for Computer Science Universitaetsstr. 1 56016 Koblenz, Germany [email protected] Heiner Stuckenschmidt University of Mannheim Institute for Practical Computer Science A5, 6 68159 Mannheim, Germany [email protected] Library of Congress Control Number: 2005936055 ACM Computing Classification (1998): C.2.4, H.3, I.2.4 ISBN-10 3-540-28346-3 Springer Berlin Heidelberg New York ISBN-13 978-3-540-28346-1 Springer Berlin Heidelberg New York This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable for prosecution under the German Copyright Law. Springer is a part of Springer Science+Business Media springeronline.com © Springer-Verlag Berlin Heidelberg 2006 Printed in Germany The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant pro- tective laws and regulations and therefore free for general use.
    [Show full text]
  • Ontology Without Borders 1St Edition Free Download
    FREE ONTOLOGY WITHOUT BORDERS 1ST EDITION PDF Jody Azzouni | 9780190622558 | | | | | Daniele Lorenzini and Martina Tazzioli: Critique without ontology / Radical Philosophy Uh-oh, it looks like your Internet Explorer is out of date. For a better shopping experience, please upgrade now. Javascript is not enabled in your browser. Enabling JavaScript in your browser will allow you to experience all the features of our site. Learn how to enable JavaScript on your browser. NOOK Book. Home 1 Books 2. Read an excerpt of this book! Add to Wishlist. Sign in to Purchase Instantly. Members save with free shipping everyday! See details. Overview Our experience of objects and consequently our theorizing about them is very rich. We perceive objects as possessing individuation conditions. They appear to have boundaries in space and time, for example, and they appear to move independently of a background of other objects or a landscape. In Ontology Without Boundaries Jody Azzouni undertakes an analysis of our concept of object, and shows what about that notion is truly due to the world and what about it is a projection onto the world of our senses and thinking. Location and individuation conditions are our product: there is no echo of them in the world. Features, the ways that objects seem to be, aren't projections. Azzouni shows how the resulting austere metaphysics tames a host of ancient philosophical problems about constitution "Ship of Theseus," "Sorities"as well as contemporary puzzles about reductionism. In addition, it's shown that the same sorts of individuation conditions for properties, which philosophers Ontology Without Borders 1st edition to distinguish between various kinds of odd abstracta-universals, tropes, and so on, are also projections.
    [Show full text]
  • Completion of Ontologies and Ontology Networks
    Link¨opingStudies in Science and Technology Dissertations. No. 1852 Completion of Ontologies and Ontology Networks by Zlatan Dragisic Department of Computer and Information Science Link¨opingUniversity SE-581 83 Link¨oping,Sweden Link¨oping2017 Copyright 2017 Zlatan Dragisic ISBN 978-91-7685-522-5 ISSN 0345–7524 Printed by LiU Tryck 2017 URL: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139487 Abstract The World Wide Web contains large amounts of data, and in most cases this data has no explicit structure. The lack of structure makes it difficult for automated agents to understand and use such data. A step towards a more structured World Wide Web is the Semantic Web, which aims at introducing semantics to data on the World Wide Web. One of the key technologies in this endeavour are ontologies, which provide a means for modeling a domain of interest and are used for search and integration of data. In recent years many ontologies have been developed. To be able to use multiple ontologies it is necessary to align them, i.e., find inter-ontology re- lationships. However, developing and aligning ontologies is not an easy task and it is often the case that ontologies and their alignments are incorrect and incomplete. This can be a problem for semantically-enabled applications. Incorrect and incomplete ontologies and alignments directly influence the quality of the results of such applications, as wrong results can be returned and correct results can be missed. This thesis focuses on the problem of completing ontologies and ontology networks. The contributions of the thesis are threefold.
    [Show full text]
  • A Probabilistic Extension to the Web Ontology Language
    A Probabilistic Extension to Ontology Language OWL Zhongli Ding and Yun Peng Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore, Maryland 21250 {zding1, ypeng}@cs.umbc.edu Phone: 410-455-3816 Fax: 410-455-3969 A Probabilistic Extension to Ontology Language OWL Abstract With the development of the semantic web activity, ontologies become widely used to represent the conceptualization of a domain. However, none of the existing ontology languages provides a means to capture uncertainty about the concepts, properties and instances in a domain. Probability theory is a natural choice for dealing with uncertainty. Incorporating probability theory into existing ontology languages will provide these languages additional expressive power to quantify the degree of the overlap or inclusion between two concepts, support probabilistic queries such as finding the most probable concept that a given description belongs to, and make more accurate semantic integration possible. One approach to provide such a probabilistic extension to ontology languages is to use Bayesian networks, a widely used graphic model for knowledge representation under uncertainty. In this paper, we present our on-going research on extending OWL, an ontology language recently proposed by W3C’s Semantic Web Activity. First, the language is augmented to allow additional probabilistic markups , so probabilities can be attached with individual concepts and properties in an OWL ontology. Secondly, a set of translation rules is defined to convert this probabilistically annotated OWL ontology into a Bayesian network. Our probabilistic extension to OWL has clear semantics: the Bayesian network obtained will be associated with a joint probability distribution over the application domain.
    [Show full text]
  • Ontology Based Teaching Domain Knowledge Management for E-Learning by Doing Systems Farida Bouarab-Dahmani, Catherine Comparot, Malik Si-Mohammed, Pierre-Jean Charrel
    Ontology Based Teaching Domain Knowledge Management for E-Learning by Doing Systems Farida Bouarab-Dahmani, Catherine Comparot, Malik Si-Mohammed, Pierre-Jean Charrel To cite this version: Farida Bouarab-Dahmani, Catherine Comparot, Malik Si-Mohammed, Pierre-Jean Charrel. Ontology Based Teaching Domain Knowledge Management for E-Learning by Doing Systems. Electronic Journal of Knowledge Management, Academic Conferences and Publishing International, 2015, vol. 13 (n° 2), pp. 156-171. hal-01535943 HAL Id: hal-01535943 https://hal.archives-ouvertes.fr/hal-01535943 Submitted on 9 Jun 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Open Archive TOULOUSE Archive Ouverte ( OATAO ) OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 16919 To link to this article : URL : http://www.ejkm.com To cite this version : Bouarab-Dahmani, Farida and Comparot, Catherine and Si-Mohammed, Malik and Charrel, Pierre-Jean Ontology Based Teaching Domain Knowledge Management for E-Learning by Doing Systems. (2015) Electronic Journal of Knowledge Management, vol.
    [Show full text]
  • Knowledge Organization Systems: Summary Taxonomies Thesauri
    About the Speakers Alexis Dimitriadis Heather Hedden Data and Knowledge Engineer Data and Knowledge Engineer Semantic Web Company Semantic Web Company Alexis holds a Ph.D. degree in Linguistics Heather has over 25 years of experience in from the University of Pennsylvania. He developing and managing taxonomies, metadata, has research and teaching experience in and other knowledge organization systems for ontologies and linked data, database various organizations and applications. She design, natural language processing, and provides training in taxonomy creation and is machine learning and classification. author of the book The Accidental Taxonomist. www.linkedin.com/in/alexisdimitriadis www.linkedin.com/in/hedden Semantic Web Company is a leading provider of graph-based metadata, search, and analytic solutions and the developer of PoolParty Semantic Suite software. Outline 1. Data, Information, and Knowledge Problems 2. Knowledge Organization Systems 3. Ontology Types and Approaches 4. Using and Applying Ontologies to Taxonomies 5. Creating Knowledge Graphs 6. Ontology Modeling Issues and Tips Data, information, and knowledge problems and solutions Data, Information, and Knowledge Problems & Solutions Problems Causing Provided by • Data silos • Inefficiencies • Data-centric architecture • Heterogeneous data • Missed opportunities • Knowledge graphs sources • Poor decisions • Ontologies • Mix of unstructured and structured data Solutions Results in • Same things with • Sharing data • Better decisions different names • Reusable data sets
    [Show full text]
  • Ontology Based Querying and Integration of Heterogeneous Flat Files
    Ontology based Querying and Integration of Heterogeneous Flat Files THESIS Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University By Rohit Dinakar Graduate Program in Computer Science and Engineering The Ohio State University 2010 Master's Examination Committee: Dr. Gagan Agrawal, Advisor Dr. Hakan Ferhatosmanoglu Copyright by Rohit Dinakar 2010 Abstract In scientific domains, most of the measurements collected during observation periods are stored in flat files. In many cases, especially when different scientists come together from different fields to draw comprehensive conclusions, the formats of the files vary from one group to another. Integrating, querying, and retrieving data from such heterogeneous data files present a challenge. Semantic interoperability is essential in order to harmonize these datasets. In this thesis, we describe an ontology-based system that parses, summarizes, represents and integrates heterogeneous data files stored as flat files. The test bed dataset is from the Episodic Events Great Lakes Experiment (EEGLE) project which collected over 500 MB of data in more than 1,500 objects. Existing works on querying hydrological data involve the use of relational databases and do not provide ways to query within the flat files. Hence efficient ways are required to eliminate the overhead associated with relational databases and still provide the flexibility and ease of querying that relational databases offer. We develop an intuitive approach using ontologies to integrate and query the semi-structured data present in the flat files. The crawled data from the flat files is ii represented in XML using resource scripts to provide a structure and schema to it.
    [Show full text]
  • Model Morphisms (Momo) to Enable Language Independent Information Models and Interoperable Business Networks
    Departamento de Engenharia Electrotécnica e de Computadores Model Morphisms (MoMo) to Enable Language Independent Information Models and Interoperable Business Networks By Filipe André Sobral Correia MSc. Dissertation presented at Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa to obtain the Master degree in Electrical and Computer Engineering, held under the guidance of Doctor Ricardo Luís Rosa Jardim-Gonçalves Lisboa September 2010 ii ACKNOWLEDGEMENTS I would like to thank all those who in some way contributed and supported me during the realisation of my course and this dissertation. To my parents, brother and sister in-law who supported me from the beginning and throughout all these long years and never gave up on believing in me. To Lua, my moonlight which guided me in these long seven years with many dark nights. Thank you for always being there and making me believing in myself. To my advisor Doctor Ricardo Gonçalves for believing in my capabilities and giving me the honour of his advices, the time devoted to assist me and the assertive guidance towards the completion of this dissertation. To all my colleagues at GRIS, especially to Carlos Agostinho, João Sarraipa and Fernando Ferreira, who took me as family and supported me from very closely. Finally, a very special thanks to all my friends who shared my worries throughout these long past years especially to Luís Martins, Tiago Gaspar and Fábio Coelho. I will never forget those RedBull-powered nights at the University! iii iv ABSTRACT With the event of globalisation, the opportunities for collaboration became more evident with the effect of enlarging business networks.
    [Show full text]