Semantic Models for Information Systems

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Individuals and organizations alike now have access to more data than ever, from a variety of sources ranging from databases to the web and digital media. Unfortunately, data is not the same thing as information. To make meaningful use of the data, users must sift through it, classify and structure it, also maintain it current. Such information management tasks have always been important for managers and knowledge workers. As the amount and variety of available data continues to grow, this form of management will become ever more demanding and ever more critical.The basic hypothesis of this research is that advances in information modeling and knowledge engineering have made it possible to develop integrated technologies along with methodologies which can greatly facilitatethe management of data and turn it into useful information.Our research over the next five years will focus on two topics, one related to software engineering, the other to information modeling and knowledge management. On the first topic, we propose to continue work on asoftware development methodology for agent-oriented software (the Tropos project). Our approach adopts concepts such as "agent", "goal" and (inter-agent) "dependency" to specify requirements and designs for agent-oriented software. This work will result in a systematic method for building software thast can communicate, negotiate, plan and adapt to address stakeholder requirements in a dynamic, open operating environment. On the second topic, we propose to conduct research that extends existing methodologies for designing databases. We also propose to work on novel theories of conceptual models and modelling that combine Logical and Category-theoretic approaches to address syntactic and semantic issues for models.