Keywords
modularity, observatory, culture of sharing, ontology, open source, environmental management
Start Date
1-7-2008 12:00 AM
Abstract
Community modelling is a promising paradigm to develop complex evolving and adaptable modelling systems that can share methods, data and models more easily within specialized communities. Why then are cooperative modelling communities still quite rare and do not propagate easily? Why has open source been so successful for software development, yet open models are still quite exotic? One difference between software and models is that software shares some common language. Models often use very different principles, theories, and semantics. For example hydrodynamic models, ecological models, and decision support models may have limited commonalities, In these cases, the disciplinary problem being solved may be the impediment to communication and to development of effective community tools these principles to another; it becomes difficult for one model to talk to another one. Similar problems prevail in data operations, when data sets (which are also models of sort) are hard to integrate with other data. An issue of contemporary interest is how will community data and models be implemented within environmental observatories. The environmental observatory may are become the ultimate driver for advancing research with a clear need for interoperability standards and functionality.
Community modelling, and data-model interoperability
Community modelling is a promising paradigm to develop complex evolving and adaptable modelling systems that can share methods, data and models more easily within specialized communities. Why then are cooperative modelling communities still quite rare and do not propagate easily? Why has open source been so successful for software development, yet open models are still quite exotic? One difference between software and models is that software shares some common language. Models often use very different principles, theories, and semantics. For example hydrodynamic models, ecological models, and decision support models may have limited commonalities, In these cases, the disciplinary problem being solved may be the impediment to communication and to development of effective community tools these principles to another; it becomes difficult for one model to talk to another one. Similar problems prevail in data operations, when data sets (which are also models of sort) are hard to integrate with other data. An issue of contemporary interest is how will community data and models be implemented within environmental observatories. The environmental observatory may are become the ultimate driver for advancing research with a clear need for interoperability standards and functionality.
