Guidelines to Study Differences in Expressiveness between Ontology Specification Languages: A Case Of Study

We focus on our experiences on translating ontologies between two ontology languages, FLogic and Ontolingua, in the framework of Methontology and ODE. Rather than building "ad hoc" translators between languages or using KIF, our option consists of translating through ODE intermediate representations. So, we have built direct translators from ODE intermediate representations to Ontolingua and FLogic, and we have also built reverse translators from these two languages to ODE intermediate representations. Expressiveness of the target languages is the main feature to analyse when automatically generating ontologies from ODE intermediate representations. Therefore, we analyse the expressiveness of Ontolingua and FLogic for creating classes, instances, relations, functions and axioms, which are the essential components in ontologies. The motivation for this analysis can be found in the (KA)² initiative and can be easily extended to any other domains and languages

Engineering Enterprise Software Systems with Interactive UML Models and Aspect-Oriented Middleware

Large scale enterprise software systems are inherently complex and hard to maintain. To deal with this complexity, current mainstream software engineering practices aim at raising the level of abstraction to visual models described in OMG’s UML modeling language. Current UML tools, however, produce static design diagrams for documentation which quickly become out-of-sync with the software, and thus obsolete. To address this issue, current model-driven software development approaches aim at software automation using generators that translate models into code. However, these solutions don’t have a good answer for dealing with legacy source code and the evolution of existing enterprise software systems. This research investigates an alternative solution by making the process of modeling more interactive with a simulator and integrating simulation with the live software system. Such an approach supports model-driven development at a higher-level of abstraction with models without sacrificing the need to drop into a lower-level with code. Additionally, simulation also supports better evolution since the impact of a change to a particular area of existing software can be better understood using simulated “what-if” scenarios. This project proposes such a solution by developing a web-based UML simulator for modeling use cases and sequence diagrams and integrating the simulator with existing applications using aspect-oriented middleware technology

A methodology for producing reliable software, volume 1

An investigation into the areas having an impact on producing reliable software including automated verification tools, software modeling, testing techniques, structured programming, and management techniques is presented. This final report contains the results of this investigation, analysis of each technique, and the definition of a methodology for producing reliable software

Language Convergence Infrastructure

The process of grammar convergence involves grammar extraction and transformation for structural equivalence and contains a range of technical challenges. These need to be addressed in order for the method to deliver useful results. The paper describes a DSL and the infrastructure behind it that automates the convergence process, hides negligible back-en

Building Ontologies at the Knowledge Level using the Ontology Design Environment

This paper discusses how ontologies can be specified at the knowledge level using the set of intermediate representations (Gómez-Pérez, Fernández & de Vicente 1996) proposed by METHONTOLOGY (Fernández, Gómez-Pérez & Juristo 1997; and Gómez-Pérez 1998). These intermediate representations bridge the gap between how people think about a domain and the languages in which ontologies are formalized. Thus, METHONTOLOGY enables experts and ontology makers unfamiliar with implementation environments to build ontologies from scratch. In this paper, we also present the ODE (Ontology Design Environment) as a software tool to specify ontologies at the knowledge level. ODE allows developers to specify their ontology by filling in tables and drawing graphs. Its multilingual generator module automatically translates the specification of the ontology into target languages