Mariano Fernández-López

Methodologies, tools and languages for building ontologies: where is their meeting point?

In this paper we review and compare the main methodologies, tools and languages for building ontologies that have been reported in the literature, as well as the main relationships among them. Ontology technology is nowadays mature enough: many methodologies, tools and languages are already available. The future work in this field should be driven towards the creation of a common integrated workbench for ontology developers to facilitate ontology development, exchange, evaluation, evolution and management, to provide methodological support for these tasks, and translations to and from different ontology languages. This workbench should not be created from scratch, but instead integrating the technology components that are currently available.

Overview and analysis of methodologies for building ontologies

The use of methodologies in software and knowledge engineering is very extensive due to their important advantages. In the case of the development of ontologies, until now, several methodological proposals have been presented for building ontologies. Some of these methodologies are designed for building ontologies from scratch or reusing other ontologies without modifying them, concretely, the following cases can be mentioned: the Cyc methodology, the approach proposed by Uschold and King, Gruninger and Foxs methodology, the KACTUS methodology, METHONTOLOGY and the SENSUS methodology. There is even a proposal for re-engineering ontologies, and several proposals for collaborative construction of ontologies.In this article, we describe the methodologies and check their degree of maturity, contrasting them with respect to the IEEE standard for software development. Before this, we justify to what extent this standard can be used. A conclusion to this study is that there is no completely mature methodological proposal for building ontologies, since there are some important activities and techniques that are missing in all these methodologies. However, all the methodologies do not have the same degree of maturity. In fact, METHONTOLOGY is a very mature methodology. The other conclusion of this article is that, although work to unify proposals can be interesting, maybe several approaches should coexist.

Building legal ontologies with METHONTOLOGY and WebODE

This paper presents how to build an ontology in the legal domain following the ontology development methodology METHONTOLOGY and using the ontology engineering workbench WebODE. Both of them have been widely used to develop ontologies in many other domains. The ontology used to illustrate this paper has been extracted from an existing class taxonomy proposed by Breuker, and adapted to the Spanish legal domain.

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.

WebODE: a scalable workbench for ontological engineering

This paper presents WebODE as a workbench for ontological engineering that not only allows the collaborative edition of ontologies at the knowledge level, but also provides a scalable architecture for the development of other ontology development tools and ontology-based applications. First, we will describe the knowledge model of WebODE, which has been mainly extracted and improved from the reference model of METHONTOLOGYs intermediate representations. Later, we will present its architecture, together with the main functionalities of the WebODE ontology editor, such as its import/export service, translation services, ontology browser, inference engine and axiom generator, and some services that have been integrated in the workbench: WebPicker, OntoMerge and the OntoCatalogue.

WebODE in a nutshell

WEBODE is a scalable workbench for ontological engineering that eases the design, development, and management of ontologies and includes middleware services to aid in the integration of ontologies into real-world applications. WEBODE presents a framework to integrate new ontology-based tools and services, where developers only worry about the new logic they want to provide on top of the knowledge stored in their ontologies.

WebODE: An Integrated Workbench for Ontology Representation, Reasoning, and Exchange

We present WebODE as a scalable, integrated workbench for ontological engineering that eases the modelling of ontologies, the reasoning with ontologies and the exchange of ontologies with other ontology tools and ontology-based applications. We will first describe the WebODEs knowledge model. We will then describe its extensible architecture, focusing on the set of independent ontology development functionalities that are integrated in this framework, such as the Ontology Editor, the Axiom Builder, the OKBC-based inference engine, and the documentation and interoperability services.

Methodological guidelines for reusing general ontologies

Currently, there is a great deal of well-founded explicit knowledge formalizing general notions, such as time concepts and the part_of relation. Yet, it is often the case that instead of reusing ontologies that implement such notions (the so-called general ontologies), engineers create procedural programs that implicitly implement this knowledge. They do not save time and code by reusing explicit knowledge, and devote effort to solve problems that other people have already adequately solved. Consequently, we have developed a methodology that helps engineers to: (a) identify the type of general ontology to be reused; (b) find out which axioms and definitions should be reused; (c) make a decision, using formal concept analysis, on what general ontology is going to be reused; and (d) adapt and integrate the selected general ontology in the domain ontology to be developed. To illustrate our approach we have employed use-cases. For each use case, we provide a set of heuristics with examples. Each of these heuristics has been tested in either OWL or Prolog. Our methodology has been applied to develop a pharmaceutical product ontology. Additionally, we have carried out a controlled experiment with graduated students doing a MCs in Artificial Intelligence. This experiment has yielded some interesting findings concerning what kind of features the future extensions of the methodology should have.

The NeOn Methodology framework: A scenario-based methodology for ontology development

This paper describes a scenario-based methodology called the NeOn Methodology framework. The aim of this framework is to speed up the construction of ontologies and ontology networks by reusing available knowledge resources (ontologies, non-ontological resources and ontology design patterns). The methodology is founded on four pillars: (1) a glossary of processes and activities; (2) a set of nine scenarios for building ontologies and ontology networks; (3) two ontology life-cycle models; and (4) a set of prescriptive methodological guidelines for performing specific processes and activities. The paper also shows how to apply this methodology framework to develop an ontology network within the multimedia domain. Finally, it presents an empirical evaluation of the NeOn Methodology framework.

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.