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The Semantic Web is characterized by the existence of a very large number of distributed semantic resources, which together define a network of ontologies. These ontologies in turn are interlinked through a variety of different meta-relationships such as versioning, inclusion, and many more. This scenario is radically different from the relatively narrow contexts in which ontologies have been traditionally developed and applied, and thus calls for new methods and tools to effectively support the development of novel network-oriented semantic applications.

This book by Suárez-Figueroa et al. provides the necessary methodological and technological support for the development and use of ontology networks, which ontology developers need in this distributed environment. After an introduction, in its second part the authors describe the NeOn Methodology framework. The book’s third part details the key activities relevant to the ontology engineering life cycle. For each activity, a general introduction, methodological guidelines, and practical examples are provided. The fourth part then presents a detailed overview of the NeOn Toolkit and its plug-ins. Lastly, case studies from the pharmaceutical and the fishery domain round out the work.

The book primarily addresses two main audiences: students (and their lecturers) who need a textbook for advanced undergraduate or graduate courses on ontology engineering, and practitioners who need to develop ontologies in particular or Semantic Web-based applications in general. Its educational value is maximized by its structured approach to explaining guidelines and combining them with case studies and numerous examples. The description of the open source NeOn Toolkit provides an additional asset, as it allows readers to easily evaluate and apply the ideas presented.



Chapter 1. Introduction: Ontology Engineering in a Networked World

While ontology engineering is rapidly entering the mainstream, expert ontology engineers are a scarce resource. Hence, there is a need for practical methodologies and technologies, which can assist a variety of user types with ontology development tasks. To address this need, this book presents a scenario-based methodology, the NeOn Methodology, which provides guidance for all main activities in ontology engineering. The context in which we consider these activities is that of a networked world, where reuse of existing resources is commonplace, ontologies are developed collaboratively, and managing relationships between ontologies becomes an essential aspect of the ontological engineering process. The description of both the methodology and the ontology engineering activities is grounded in a comprehensive software environment, the NeOn Toolkit and its plugins, which provides integrated support for all the activities described in the book. Here we provide an introduction for the whole book, while the rest of the content is organized into 4 parts: (1) the NeOn Methodology Framework, (2) the set of ontology engineering activities, (3) the NeOn Toolkit and plugins, and (4) three use cases. Primary goals of this book are (a) to disseminate the results from the NeOn project in a structured and comprehensive form, (b) to make it easier for students and practitioners to adopt ontology engineering methods and tools, and (c) to provide a textbook for undergraduate and postgraduate courses on ontology engineering.
Mari Carmen Suárez-Figueroa, Asunción Gómez-Pérez, Enrico Motta, Aldo Gangemi

NeOn Methodology Framework


Chapter 2. The NeOn Methodology for Ontology Engineering

In contrast to other approaches that provide methodological guidance for ontology engineering, the NeOn Methodology does not prescribe a rigid workflow, but instead it suggests a variety of pathways for developing ontologies. The nine scenarios proposed in the methodology cover commonly occurring situations, for example, when available ontologies need to be re-engineered, aligned, modularized, localized to support different languages and cultures, and integrated with ontology design patterns and non-ontological resources, such as folksonomies or thesauri. In addition, the NeOn Methodology framework provides (a) a glossary of processes and activities involved in the development of ontologies, (b) two ontology life cycle models, and (c) a set of methodological guidelines for different processes and activities, which are described (a) functionally, in terms of goals, inputs, outputs, and relevant constraints; (b) procedurally, by means of workflow specifications; and (c) empirically, through a set of illustrative examples.
Mari Carmen Suárez-Figueroa, Asunción Gómez-Pérez, Mariano Fernández-López

Chapter 3. Pattern-Based Ontology Design

In this chapter, we present ontology design patterns (ODPs), which are reusable modeling solutions that encode modeling best practices. ODPs are the main tool for performing pattern-based design of ontologies, which is an approach to ontology development that emphasizes reuse and promotes the development of a common “language” for sharing knowledge about ontology design best practices. We put specific focus on content ODPs (CPs) and show how they can be used within a particular methodology. CPs are domain-dependent patterns, the requirements of which are expressed by means of competency questions, contextual statements, and reasoning requirements. The eXtreme Design (XD) methodology is an iterative and incremental process, which is characterized by a test-driven and collaborative development approach. In this chapter, we exemplify the XD methodology for the specific case of CP reuse. The XD methodology is also supported by a set of software components named XD Tools, compatible with the NeOn Toolkit, which assist users in the process of pattern-based design.
Valentina Presutti, Eva Blomqvist, Enrico Daga, Aldo Gangemi

Chapter 4. The NeOn Ontology Models

Interoperability on multiple levels, concerning both the ontologies themselves and their engineering activities, is a key requirement for ontology networks to be efficient, with minimal redundancy and high reuse. This requirement has a strict binding for software tools that can support some interoperability levels, yet they can be hindered by a lack of shared models and vocabularies describing the resources to be handled, as well as the ways of handling them. Here, three examples of metalevel vocabularies are proposed, each covering at least one peculiar interoperability aspect: OMV for modeling the artifacts themselves, LIR for managing a multilingual layer on top of them, and C-ODO Light for modeling collaboration-supportive life cycle management tasks and processes. All of these models lend themselves to handling by dedicated software tools and are all being employed within NeOn products.
Alessandro Adamou, Raúl Palma, Peter Haase, Elena Montiel-Ponsoda, Guadalupe Aguado de Cea, Asunción Gómez-Pérez, Wim Peters, Aldo Gangemi

Ontology Engineering Activities


Chapter 5. Ontology Requirements Specification

The goal of the ontology requirements specification activity is to state why the ontology is being built, what its intended uses are, who the end users are, and which requirements the ontology should fulfill. This chapter presents detailed methodological guidelines for specifying ontology requirements efficiently. These guidelines will help ontology engineers to capture ontology requirements and produce the ontology requirements specification document (ORSD). The ORSD will play a key role during the ontology development process because it facilitates, among other activities, (1) the search and reuse of existing knowledge resources with the aim of reengineering them into ontologies, (2) the search and reuse of ontological resources (ontologies, ontology modules, ontology statements as well as ontology design patterns), and (3) the verification of the ontology along the ontology development.
Mari Carmen Suárez-Figueroa, Asunción Gómez-Pérez

Chapter 6. Reusing and Re-engineering Non-ontological Resources for Building Ontologies

With the goal of speeding up the ontology development process, ontology developers are reusing as much as possible available ontological and non-ontological resources such as classification schemes, thesauri, lexicons, and folksonomies, that have already reached some consensus. The reuse of such non-ontological resources necessarily involves their re-engineering into ontologies. Based on this new trend, this chapter presents a general method for re-engineering non-ontological resources into ontologies, taking into account that non-ontological resources are highly heterogeneous in their data model and contents. The method is based on the so-called re-engineering patterns, which define a procedure that transforms the non-ontological resource components into ontology representational primitives. This chapter also presents the description of a software library that implements the transformations suggested by the patterns. Finally, the chapter depicts an evaluation of the method.
Boris Villazón-Terrazas, Asunción Gómez-Pérez

Chapter 7. Ontology Development by Reuse

This chapter presents methodological guidelines that allow engineers to reuse generic ontologies. This kind of ontologies represents notions generic across many fields, (is part of, temporal interval, etc.). The guidelines helps the developer (a) to identify the type of generic ontology to be reused, (b) to find out the axioms and definitions that should be reused and (c) to adapt and integrate the generic ontology selected in the domain ontology to be developed. For each task of the methodology, a set of heuristics with examples are presented. We hope that after reading this chapter, you would have acquired some basic ideas on how to take advantage of the great deal of well-founded explicit knowledge that formalizes generic notions such as time concepts and the part of relation.
Mariano Fernández-López, Mari Carmen Suárez-Figueroa, Asunción Gómez-Pérez

Chapter 8. Ontology Localization

In the context of the Semantic Web, resources on the net can be enriched by well-defined, machine-understandable metadata describing their associated conceptual meaning. These metadata consisting of natural language descriptions of concepts are the focus of the activity we describe in this chapter, namely, ontology localization. In the framework of the NeOn Methodology, ontology localization is defined as the activity of adapting an ontology to a particular language and culture. This adaptation mainly involves the translation of the natural language descriptions of the ontology from a source natural language to a target natural language, with the final objective of obtaining a multilingual ontology, that is, an ontology documented in several natural languages. The purpose of this chapter is to provide detailed and prescriptive methodological guidelines to support the performance of this activity.
Mauricio Espinoza Mejía, Elena Montiel-Ponsoda, Guadalupe Aguado de Cea, Asunción Gómez-Pérez

Chapter 9. Ontology (Network) Evaluation

Ontology evaluation refers to the activity of checking the technical quality of an ontology against a frame of reference. As such, it is of core importance for ontology engineering supporting scenarios such as ontology validation, knowledge selection, or the evaluation of knowledge extraction algorithms. In this chapter, we provide methodological guidelines for evaluating stand-alone ontologies as well as ontology networks. Our goal is not only to present the NeOn perspective on this issue but to also provide a practical outlook to the vast area of work in the area of ontology evaluation. Without performing an extensive state-of-the-art analysis of this research field, we aim to illustrate how various evaluation methods developed by the NeOn project, and not only, can be used at different stages of the evaluation process. We conclude the chapter with some concrete examples of performing ontology evaluation.
Marta Sabou, Miriam Fernandez

Chapter 10. Modularizing Ontologies

As large monolithic ontologies are difficult to handle and maintain, the activity of modularizing an ontology consists in identifying components (modules) of this ontology that can be considered separately while they are interlinked with other modules. The end benefit of modularizing an ontology can be, depending on the particular application or scenario, (a) to improve performance by enabling the distribution or targeted processing, (b) to facilitate the development and maintenance of the ontology by dividing it in loosely coupled, self-contained components or (c) to facilitate the reuse of parts of the ontology. In this chapter, we present a brief introduction to the field of ontology modularization. We detail the approach taken as a guideline to modularize existing ontologies and the tools available in order to carry out this activity.
Mathieu d’Aquin

Chapter 11. Ontology Evolution

Ontologies are dynamic entities that evolve over time. There are several challenges associated with the management of ontology dynamics, from the adequate control of ontology changes to the identification and administration of ontology versions. Moreover, ontologies are increasingly becoming part of a network of complex relationships and dependencies, where they reuse and extend other ontologies, have associated metadata in order to ease sharing and reuse, are used to integrate heterogeneous knowledge bases, etc. Under these circumstances, a change in an ontology does not only affect the ontology itself but may also have consequences in all its related artifacts. In this chapter, we propose methodological guidelines for carrying out the ontology evolution activity. We target different scenarios, supporting users in the process of ontology evolution from a generic perspective and on how to use tools that semiautomatically assist them in discovering, evaluating, and integrating domain changes to evolve ontologies. To illustrate their applicability, we describe how such guidelines have been used in real example applications.
Raúl Palma, Fouad Zablith, Peter Haase, Oscar Corcho

Chapter 12. Methodological Guidelines for Matching Ontologies

Finding alignments between ontologies is a very important operation for ontology engineering. It allows for establishing links between ontologies, either to integrate them in an application or to relate developed ontologies to context. It is even more critical for networked ontologies. Incorrect alignments may lead to unwanted consequences throughout the whole network, and incomplete alignments may fail to provide the expected consequences. Yet, there is no well-established methodology available for matching ontologies. We propose methodological guidelines that build on previously disconnected results and experiences.
Jérôme Euzenat, Chan Le Duc

The NeOn Toolkit


Chapter 13. Overview of the NeOn Toolkit

The NeOn Toolkit is one of the major results of the NeOn project. It is a state-of-the-art, open-source, multiplatform ontology engineering environment, which provides comprehensive support for the ontology engineering life cycle of networked ontologies. It is based on an open and modular plugin architecture that allows adding additional plugins realizing more advanced features supporting more complex ontology engineering activities. A substantial number of plugins have been developed within and outside the NeOn consortium and are available at the NeOn Toolkit homepage. The NeOn Toolkit supports the Web Ontology Language OWL 2, the ontology language specified by the W3C, and features basic editing and visualization functionality. Its user interface, especially the presentation of class restrictions, makes the NeOn Toolkit accessible to users that do not have long experience with ontologies but instead know the object-oriented modeling paradigm. In the chapter, we will present the feature set of the NeOn Toolkit and how to use it. A second part explains some architecture and implementation background and how new plugins can be integrated into the common platform.
Michael Erdmann, Walter Waterfeld

Chapter 14. Scheduling Ontology Engineering Projects Using gOntt

In order to manage properly ontology development projects in complex settings and to apply correctly the NeOn Methodology, it is crucial to have knowledge of the entire ontology development life cycle before starting the development projects. The ontology project plan and scheduling helps the ontology development team to have this knowledge and to monitor the project execution. To facilitate the planning and scheduling of ontology development projects, the NeOn Toolkit plugin called gOntt has been developed. gOntt is a tool that supports the scheduling of ontology network development projects and helps to execute them. In addition, prescriptive methodological guidelines for scheduling ontology development projects using gOntt are provided.
Mari Carmen Suárez-Figueroa, Asunción Gómez-Pérez, Oscar Muñoz-García

Chapter 15. Customizing Your Interaction with Kali-ma

This chapter presents the Kali-ma NeOn Toolkit plugin, which exploits the versatility of the C-ODO Light model to assist ontology engineers and project managers in locating, selecting, and accessing other plugins through a unified, shared interaction mode. Kali-ma offers reasoning methods for classifying and categorizing ontology design tools with a variety of criteria, including collaborative aspects of ontology engineering and activities that follow the NeOn Methodology. Furthermore, it provides means for storing selections of tools and associating them directly to development projects so that they can be shared and ported across systems involved in common engineering tasks. In order to boost Kali-ma support for third-party plugins, we are also offering an online service for the semiautomatic generation of C-ODO Light–based plugin descriptions.
Alessandro Adamou, Valentina Presutti

Chapter 16. Visualizing and Navigating Ontologies with KC-Viz

There is empirical evidence that current user interfaces for ontology engineering are still inadequate in their ability to reduce task complexity for users, especially non-expert ones. Here we present a novel tool for visualizing and navigating ontologies, KC-Viz, which exploits an innovative ontology summarization method to support a “middle-out ontology browsing” approach, where it becomes possible to navigate ontologies starting from the most information-rich nodes (i.e., key concepts). This approach is similar to map-based visualization and navigation in geographical information systems, where, e.g., major cities are displayed more prominently than others, depending on the current level of granularity. Building on its powerful and empirically validated ontology summarization algorithm, KC-Viz provides a rich set of navigation and visualization mechanisms, including flexible zooming into and hiding of specific parts of an ontology, visualization of the most salient nodes, history browsing, saving and loading of customized ontology views, as well as essential interface support, such as graphical zooming, font manipulation, tree layout customization, and other functionalities.
Enrico Motta, Silvio Peroni, José Manuel Gómez-Pérez, Mathieu d’Aquin, Ning Li

Chapter 17. Reasoning with Networked Ontologies

The chapter covers basic functionality pertaining to reasoning with ontologies. We first introduce general methods for detecting and resolving inconsistencies, and then present three plugins that provide reasoning and query functionality. The three plugins are: the reasoning plugin, which allows for standard reasoning tasks, such as materialising inferences and checking consistency in ontologies; the RaDON plugin, which provides functionality for diagnosing and resolving inconsistencies in networked ontologies; and the query plugin, which allows for users querying ontologies in the NeOn Toolkit via the RDF query language SPARQL.
Guilin Qi, Andreas Harth

Case Studies


Chapter 18. Knowledge Management at FAO: A Case Study on Network of Ontologies in Fisheries

In this chapter, we illustrate the work conducted at the Food and Agriculture Organization of the United Nations (FAO) with the creation of a network of ontologies about fisheries, developed with NeOn technologies and methodologies. The network included the main thematic areas needed to talk about fish stocks (often referred to as aquatic resources) and included data sources of various types: reference data for time series, thesauri for document indexing, actual time series, and the reuse of an existing well-known ontology maintained by FAO (the geopolitical ontology). Such a network of ontologies was also used within a prototypical web-based application. After describing the methodologies used to create the network, and its contents and features, we draw some conclusions and highlight the lessons learned during the process.
Caterina Caracciolo, Juan Heguiabehere, Aldo Gangemi, Claudio Baldassarre, Johannes Keizer, Marc Taconet

Chapter 19. Electronic Invoice Management in the Pharmaceutical Sector: The PharmaInnova Case

Since the use of electronic invoicing in business transactions was approved by the EU back in 2002, its application in Europe has grown considerably. However, despite the existence of standards like EDIFACT (http://​www.​unece.​org/​trade/​untdid/​welcome.​htm) or UBL, (http://​www.​oasis-open.​org/​committees/​ubl) widespread take-up of electronic invoicing has been hindered by the enormous heterogeneity of proprietary solutions. In this chapter, we describe an approach toward addressing the interoperability problem in electronic invoice exchange. We especially focus on networked ontologies as the main enablers of such an approach, where networked ontologies serve as a semantic gateway for the transformation of invoice data between different formats and models.
José Manuel Gómez-Pérez, Víctor Méndez, Joan Candini, Juan Carlos Muñoz

Chapter 20. Integrating Product Information in the Pharmaceutical Sector

In recent years, increased attention has been paid to what is called semantic interoperability in eHealth, being the interoperable identification and description of drugs at its very core. In spite of the efforts toward having a common way to describe drugs, there is no universal nomenclature but several attempts like SNOMED CT (http://​www.​ihtsdo.​org/​snomed-ct/​) or the biomedical ontologies in OBO Foundry (http://​www.​obofoundry.​org/​) and BioPortal (http://​bioportal.​bioontology.​org/​). This chapter describes an approach that applies NeOn technology to bridge the gap between different ontologies describing pharmaceutical products.
Tomás Pariente Lobo, Germán Herrero Cárcel


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