This paper is intended to serve as a comprehensive introduction to the emerging field concerned with the design and use of ontologies. We observe that disparate backgrounds, languages, tools and techniques are a major barrier to effective communication among people, organisations and/or software understanding (i.e. an “ontology”) in a given subject area, can improve such communication, which in turn, can give rise to greater reuse and sharing, inter-operability, and more reliable software. After motivating their need, we clarify just what ontologies are and what purpose they serve. We outline a methodology for developing and evaluating ontologies, first discussing informal techniques, concerning such issues as scoping, handling ambiguity, reaching agreement and producing definitions. We then consider the benefits and describe, a more formal approach. We re-visit the scoping phase, and discuss the role of formal languages and techniques in the specification, implementation and evalution of ontologies. Finally, we review the state of the art and practice in this emerging field, considering various case studies, software tools for ontology development, key research issues and future prospects.

Automated modelling is a young research field and is attracting increasingly more attention. It is a cross-disciplinary field involving simulation, modelling, qualitative reasoning, bond graphs and systems dynamics. It is an investigation of the modelling process with the purpose of developing computer tools which will automatically follow modelling principles. In addition, these tools will take into account the details of an application and generate the most appropriate model for the application. Its objective is to develop computer modelling tools which will have perception of model correctness, completeness and appropriateness and can perform modelling automatically. One way to achieve this objective is to introduce well-defined models and automate the process of assembling submodels into models to create well-defined models. This paper reviews the motivation and background behind this new field, its theory and current state of the art, compares existing approaches and discusses the underlying issues. It is hoped that more researchers will become aware of this field and be encouraged to work in it.

This paper presents a review of pattern matching techniques. The application areas for pattern matching are extensive, ranging from CAD systems to chemical analysis and from manufacturing to image processing. Published techniques and methods are classified and assessed within the context of three key issues: pattern classes, similarity types and matching methods. It has been shown that the techniques and approaches are as diverse and varied as the applications.

For the first time, post-conference workshops were organised for the International Conference on Deductive and Object-Oriented Databases (DOOD). There were two workshops focusing on knowledge discovery and temporal reasoning. This report is dedicated to one dealing with temporal reasoning.

The KEML (Knowledge Engineering Methods and Languages) workshop which took place in a suburb of Paris was the sixth in a series, and was preceded by workshops in Bonn (1991 and 1993), Karlsruhe (1992) and Amsterdam (1994 and 1995). Originally, the workshops were dedicated to formal specification languages for KADS models, but later the scope was widened to include methods and languages for Knowledge Engineering in general. However, the emphasis of the KEML workshops remains on formal languages and techniques, and this distinguishes it from the more general Knowledge Acquisition workshops such as KAW (Banff, Canada), EKAW (Europe) and JKAW (Japan).