1st International Congress on Environmental Modelling and Software - Lugano, Switzerland - June 2002
Keywords
generic integration, environmental information systems, environmental decision support systems, eu fp5, gimmi, imarq
Start Date
1-7-2002 12:00 AM
Abstract
Environmental Information Systems (EIS) and Environmental Decision Support Systems (EDSS) are major building blocks in environmental management and science today. They are used at all levels of public bodies (community, state, national and international level), in science, in management and as information platforms towards the public. EIS and EDSS are usually said to have certain characteristics, which distinguish them from standard information systems, e.g. information complexity in time and space or uncompleteness or fuzzyness of data items. By the very nature of the complex tasks involved, different methodologies can be an option while developing a new system, for instance modelling, decision theoretic approaches, artificial intelligence, geographical analysis, statistics and many more. As software developers, we face the situation that we have to recompose these different methodologies in different application scenarios over and over again. This is rather cumbersome, because the tools implementing certain methodologies are usually not very helpful in the integration process. This paper discusses the question, how different EIS and EDSS tools can be integrated in a generic way. For this purpose, we discuss a number of integration strategies and give 2 examples of current EU-funded projects.
Generic Integration in Environmental Information and Decision Support Systems
Environmental Information Systems (EIS) and Environmental Decision Support Systems (EDSS) are major building blocks in environmental management and science today. They are used at all levels of public bodies (community, state, national and international level), in science, in management and as information platforms towards the public. EIS and EDSS are usually said to have certain characteristics, which distinguish them from standard information systems, e.g. information complexity in time and space or uncompleteness or fuzzyness of data items. By the very nature of the complex tasks involved, different methodologies can be an option while developing a new system, for instance modelling, decision theoretic approaches, artificial intelligence, geographical analysis, statistics and many more. As software developers, we face the situation that we have to recompose these different methodologies in different application scenarios over and over again. This is rather cumbersome, because the tools implementing certain methodologies are usually not very helpful in the integration process. This paper discusses the question, how different EIS and EDSS tools can be integrated in a generic way. For this purpose, we discuss a number of integration strategies and give 2 examples of current EU-funded projects.
