Overview of methodologies for building ontologies

A few research groups are now proposing a series of steps and methodologies for developing ontologies. However, mainly due to the fact that Ontological Engineering is still a relatively immature discipline, each work group employs its own methodology. Our goal is to present the most representative methodologies used in ontology development and to perform an analysis of such methodologies against the same framework of reference. So, the goal of this paper is not to provide new insights about methodologies, but to put it all in one place and help people to select which methodology to use

Overview of Knowledge Sharing and Reuse Components: Ontologies and Problem-Solving Methods

Ontologies and problem-solving methods are promising candidates for reuse in Knowledge Engineering. Ontologies define domain knowledge at a generic level, while problem-solving methods specify generic reasoning knowledge. Both type of components can be viewed as complementary entities that can be used to configure new knowledge systems from existing, reusable components. In this paper, we give an overview of approaches for ontologies and problem-solving methods

Ontological Reengineering for Reuse

This paper presents the concept of Ontological Reengineering as the process of retrieving and transforming a conceptual model of an existing and implemented ontology into a new, more correct and more complete conceptual model which is reimplemented. Three activities have been identified in this process: reverse engineering, restructuring and forward engineering. The aim of Reverse Engineering is to output a possible conceptual model on the basis of the code in which the ontology is implemented. The goal of Restructuring is to reorganize this initial conceptual model into a new conceptual model, which is built bearing in mind the use of the restructured ontology by the ontology/application that reuses it. Finally, the objective of Forward Engineering is output a new implementation of the ontology. The paper also discusses how the ontological reengineering process has been applied to the Standard-Units ontology [18], which is included in a Chemical-Elements [12] ontology. These two ontologies will be included in a Monatomic-Ions and Environmental-Pollutants ontologies

Iterated learning and grounding: from holistic to compositional languages

This paper presents a new computational model for studying the origins and evolution of compositional languages grounded through the interaction between agents and their environment. The model is based on previous work on adaptive grounding of lexicons and the iterated learning model. Although the model is still in a developmental phase, the first results show that a compositional language can emerge in which the structure reflects regularities present in the population's environment

A conceptual framework for interactive virtual storytelling

This paper presents a framework of an interactive storytelling system. It can integrate five components: management centre, evaluation centre, intelligent virtual agent, intelligent virtual environment, and users, making possible interactive solutions where the communication among these components is conducted in a rational and intelligent way. Environment plays an important role in providing heuristic information for agents through communicating with the management centre. The main idea is based on the principle of heuristic guiding of the behaviour of intelligent agents for guaranteeing the unexpectedness and consistent themes

Using ontologies to support and critique decisions

Supporting decision making in the working environment has long being pursued by practitioners across a variety of fields, ranging from sociology and operational research to cognitive and computer scientists. A number of computer-supported systems and various technologies have been used over the years, but as we move into more global and flexible organisational structures, new technologies and challenges arise. In this paper, I argue for an ontology-based solution and present some of the early prototypes we have been developing, assess their impact on the decision making process and elaborate on the costs involved

Joining up health and bioinformatics: e-science meets e-health

CLEF (Co-operative Clinical e-Science Framework) is an MRC sponsored project in the e-Science programme that aims to establish methodologies and a technical infrastructure forthe next generation of integrated clinical and bioscience research. It is developing methodsfor managing and using pseudonymised repositories of the long-term patient histories whichcan be linked to genetic, genomic information or used to support patient care. CLEF concentrateson removing key barriers to managing such repositories ? ethical issues, informationcapture, integration of disparate sources into coherent ?chronicles? of events, userorientedmechanisms for querying and displaying the information, and compiling the requiredknowledge resources. This paper describes the overall information flow and technicalapproach designed to meet these aims within a Grid framework

A Software Architecture for Knowledge-Based Systems

. The paper introduces a software architecture for the specification and verification of knowledge-based systems combining conceptual and formal techniques. Our focus is component-based specification enabling their reuse. We identify four elements of the specification of a knowledge-based system: a task definition, a problem-solving method, a domain model, and an adapter. We present algebraic specifications and a variant of dynamic logic as formal means to specify and verify these different elements. As a consequence of our architecture we can decompose the overall specification and verification task of the knowledge-based systems into subtasks. We identify different subcomponents for specification and different proof obligations for verification. The use of the architecture in specification and verification improves understandability and reduces the effort for both activities. In addition, its decomposition and modularisation enables reuse of components and proofs. Ther..