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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.

Building a chemical ontology using Methontology and the Ontology Design Environment

Methontology provides guidelines for specifying ontologies at the knowledge level, as a specification of a conceptualization. ODE enables ontology construction, covering the entire life cycle and automatically implementing ontologies. To meet the challenge of building ontologies, we have developed Methontology, a framework for specifying ontologies at the knowledge level, and the Ontology Development Environment. We present our experience in using Methontology and ODE to build the chemical ontology.

Ontology languages for the Semantic Web

Ontologies have proven to be an essential element in many applications. They are used in agent systems, knowledge management systems, and e-commerce platforms. They can also generate natural language, integrate intelligent information, provide semantic-based access to the Internet, and extract information from texts in addition to being used in many other applications to explicitly declare the knowledge embedded in them. However, not only are ontologies useful for applications in which knowledge plays a key role, but they can also trigger a major change in current Web contents. This change is leading to the third generation of the Web-known as the Semantic Web-which has been defined as the conceptual structuring of the Web in an explicit machine-readable way. New ontology-based applications and knowledge architectures are developing for this new Web. A common claim for all of these approaches is the need for languages to represent the semantic information that this Web requires-solving heterogeneous data exchange in this heterogeneous environment. Our goal is to help developers find the most suitable language for their representation needs.

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.

Evaluation of ontologies

The evaluation of ontologies is an emerging field. At present, there is an absence of a deep core of preliminary ideas and guidelines for evaluating ontologies. This paper presents a brief summary of previous work done on evaluating ontologies and the criteria (consistency, completeness, conciseness, expandability, and sensitiveness) used to evaluate and to assess ontologies. It also addresses the possible types of errors made when domain knowledge is structured in taxonomies in an ontology and in knowledge bases: circularity errors, exhaustive and nonexhaustive class partition errors, redundancy errors, grammatical errors, semantic errors, and incompleteness errors. It also describes the process followed to evaluate the standard‐units ontology already published at the Ontology Server. © 2001 John Wiley & Sons, Inc.

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.

Some ideas and examples to evaluate ontologies

Ontologies are the platforms that enable the sharing and reuse of knowledge by establishing common vocabularies and semantic interpretations of terms. While ontologies may provide for reusability, sharability or both, the evaluation of their definitions and software environment is critical to the success of the final applications that reuse and share these definitions. If wrong definitions from the ontology coexist with specific knowledge formalized in the KB, the KBS may make poor or wrong conclusions. The lack of methods for evaluating ontologies in laboratories can be an obstacle to their use in companies. The paper presents a set of emerging ideas in evaluation of ontologies useful for: ontology developers in the lab, as a foundation from which to perform technical evaluations; end users of ontologies in companies, as a point of departure in the search for the best ontology for their systems; and future research, as a basis upon which to perform progressive and disciplined investigations in this area. After briefly exploring some general questions such as: why, what, when, how and where to evaluate; who evaluates; and, what to evaluate against, we focus on the definition of a set of criteria useful in the evaluation process. Finally, we use some of these criteria in the evaluation of the Bibliographic-Data ontology (T. Gruber, 1994).<<ETX>>

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.

Towards a framework to verify knowledge sharing technology

Based on the empirical verification of bibliographic-data and other Ontolingua ontologies, this paper provides an initial framework for verifying Knowledge Sharing Technology (KST). Verification of KST refers to the engineering activity that guarantees the correctness of the definitions in an ontology, its associated software environments and documentation with respect to a frame of reference during each phase and between phases of its life cycle. Verification of the ontologies refers to building the correct ontology, and it verifies that (1) the architecture of the ontology is sound, (2) the lexicon and the syntax of the definitions are correct and (3) the content of the ontologies and their definitions are internally and metaphysically consistent, complete, concise, expandable and sensitive.