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3.1 Ontology Engineering

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Knowledge Representation in the Social Semantic Web
This chapter is in the book Knowledge Representation in the Social Semantic Web
242 Ontology Engineering in the Era of the Social Semantic Web models can not only influence each other but are also interlinked to form a knowl-edge organization network. 3.1 Ontology Engineering In the previous chapter, we have seen the main elements of ontologies and how they may be arranged to represent knowledge in a formal way. Due to their com-plex expressiveness, the development of ontologies which make use of all seman-tic elements (from concept hierarchies and individuals to fine-grained concept properties and restrictions) is a demanding and time-consuming task. It requires technical skill and careful considerations of the appropriate representation of the domain of interest. Consequently, ontology engineering – the process of building an ontology – is sometimes considered to be an “art” rather than a process of “en-gineering”, e.g. by Soldatova and King: “The engineering of ontologies is still a relatively new research field. There does not yet exist a well-developed theory and technology for ontology construction, as there is for bridge construction, for example. This means that many of the steps in designing an ontology remain manual and a kind of ‘art’.”(Soldatova & King, 2005)Yet some methodologies have been developed to guide this process, and some phases have been identified which are typical for developing ontologies. The labo-rious work of building high-quality ontologies is supported by a range of tools and some basic design guidelines. 3.1.1 Methodologies, Dimensions and Principles of Ontology Engineering Methodologies Creating an ontology requires careful considerations of how to represent a domain of interest adequately. Ontology engineers (people with skills in knowledge repre-sentation and formal ontology languages206) as well as domain experts (with ex-pert knowledge in the particular domain of interest) are needed to work together in formalizing precise definitions within the ontology (Paulsen, Mainz et al., 2007). The process of building an ontology is rarely linear but requires iterations of re-finements. Particularly in the early years of ontology research, ontologies were built from scratch without many thoughts on the most effective course of action. Step by step, methodologies have been developed inspired by role models from the field of software engineering. We will not go into details of the several methods that have been developed but simply sum up aspects which can be considered to have reached a consensus in the scientific community. Individual methodologies that have gained much attention 206 Sometimes also called information architects.

242 Ontology Engineering in the Era of the Social Semantic Web models can not only influence each other but are also interlinked to form a knowl-edge organization network. 3.1 Ontology Engineering In the previous chapter, we have seen the main elements of ontologies and how they may be arranged to represent knowledge in a formal way. Due to their com-plex expressiveness, the development of ontologies which make use of all seman-tic elements (from concept hierarchies and individuals to fine-grained concept properties and restrictions) is a demanding and time-consuming task. It requires technical skill and careful considerations of the appropriate representation of the domain of interest. Consequently, ontology engineering – the process of building an ontology – is sometimes considered to be an “art” rather than a process of “en-gineering”, e.g. by Soldatova and King: “The engineering of ontologies is still a relatively new research field. There does not yet exist a well-developed theory and technology for ontology construction, as there is for bridge construction, for example. This means that many of the steps in designing an ontology remain manual and a kind of ‘art’.”(Soldatova & King, 2005)Yet some methodologies have been developed to guide this process, and some phases have been identified which are typical for developing ontologies. The labo-rious work of building high-quality ontologies is supported by a range of tools and some basic design guidelines. 3.1.1 Methodologies, Dimensions and Principles of Ontology Engineering Methodologies Creating an ontology requires careful considerations of how to represent a domain of interest adequately. Ontology engineers (people with skills in knowledge repre-sentation and formal ontology languages206) as well as domain experts (with ex-pert knowledge in the particular domain of interest) are needed to work together in formalizing precise definitions within the ontology (Paulsen, Mainz et al., 2007). The process of building an ontology is rarely linear but requires iterations of re-finements. Particularly in the early years of ontology research, ontologies were built from scratch without many thoughts on the most effective course of action. Step by step, methodologies have been developed inspired by role models from the field of software engineering. We will not go into details of the several methods that have been developed but simply sum up aspects which can be considered to have reached a consensus in the scientific community. Individual methodologies that have gained much attention 206 Sometimes also called information architects.

Chapters in this book

  1. Frontmatter I
  2. Contents V
  3. Introduction 1
  4. Chapter 1. Knowledge Representation and Indexing: Background and Future
  5. 1.1 Knowledge Representation 17
  6. 1.2 The Semantic Web 53
  7. 1.3 The Social Web 67
  8. 1.4 The Social Semantic Web 78
  9. Chapter 2. Ontologies: Semantics for the Web
  10. 2.1 Ontologies: Definition and Background 115
  11. 2.2 Structure and Elements of Ontologies 123
  12. 2.3 Ontologies as Knowledge Organization Systems 190
  13. Chapter 3. Ontology Engineering in the Era of the Social Semantic Web
  14. 3.1 Ontology Engineering 242
  15. 3.2 Community-based Ontology Engineering 272
  16. 3.3 Semantic Upgrades & Tag Gardening 317
  17. 3.4 Co-Existence of Knowledge Organization Systems 351
  18. Conclusion & Outlook 403
  19. Backmatter 411
Readers are also interested in:
https://doi.org/10.1515/9783598441585.3.242

Chapters in this book

  1. Frontmatter I
  2. Contents V
  3. Introduction 1
  4. Chapter 1. Knowledge Representation and Indexing: Background and Future
  5. 1.1 Knowledge Representation 17
  6. 1.2 The Semantic Web 53
  7. 1.3 The Social Web 67
  8. 1.4 The Social Semantic Web 78
  9. Chapter 2. Ontologies: Semantics for the Web
  10. 2.1 Ontologies: Definition and Background 115
  11. 2.2 Structure and Elements of Ontologies 123
  12. 2.3 Ontologies as Knowledge Organization Systems 190
  13. Chapter 3. Ontology Engineering in the Era of the Social Semantic Web
  14. 3.1 Ontology Engineering 242
  15. 3.2 Community-based Ontology Engineering 272
  16. 3.3 Semantic Upgrades & Tag Gardening 317
  17. 3.4 Co-Existence of Knowledge Organization Systems 351
  18. Conclusion & Outlook 403
  19. Backmatter 411
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