Keywords
integrated environmental modelling; environmental model development; model development practices; software development practices
Start Date
26-6-2018 9:00 AM
End Date
26-6-2018 10:20 AM
Abstract
Integrated models are often made up of smaller component models, each representing a particular domain that are coupled together. Such models are software for a scientific purpose, and so similarities between model and software development exist. These models tend to be developed by researchers who take on a dual-role of scientist and software developer.
Despite the similarities in development approaches, many best practices found within the field of software engineering may not be applied. These lead to issues revolving around the reusability, interoperability, and reliability (in terms of model application and results) of models developed for integrated assessment. To address these concerns recent efforts have seen the development and proliferation of component-based implementation approaches, repositories that act as a store of reusable models, and model development frameworks.
These approaches by themselves are not a panacea to model development issues. Component models may be difficult to integrate and error-prone due to the aforementioned lack of best practices. The structure of component and integrated models found in repositories may render them difficult to reuse/reapply in a different context. Model development frameworks may ease the overall technical burden of model development and integration, however they often come with a steep learning curve of their own, which may hamper their effective use. This may in turn exacerbate issues regarding model reusability and interoperability. In this paper we suggest some guidelines and general directions identified and supported through literature review and expert knowledge to fill in the gap between software and modelling paradigms.
Software Development Best Practices in Integrated Environmental Model Development
Integrated models are often made up of smaller component models, each representing a particular domain that are coupled together. Such models are software for a scientific purpose, and so similarities between model and software development exist. These models tend to be developed by researchers who take on a dual-role of scientist and software developer.
Despite the similarities in development approaches, many best practices found within the field of software engineering may not be applied. These lead to issues revolving around the reusability, interoperability, and reliability (in terms of model application and results) of models developed for integrated assessment. To address these concerns recent efforts have seen the development and proliferation of component-based implementation approaches, repositories that act as a store of reusable models, and model development frameworks.
These approaches by themselves are not a panacea to model development issues. Component models may be difficult to integrate and error-prone due to the aforementioned lack of best practices. The structure of component and integrated models found in repositories may render them difficult to reuse/reapply in a different context. Model development frameworks may ease the overall technical burden of model development and integration, however they often come with a steep learning curve of their own, which may hamper their effective use. This may in turn exacerbate issues regarding model reusability and interoperability. In this paper we suggest some guidelines and general directions identified and supported through literature review and expert knowledge to fill in the gap between software and modelling paradigms.
Stream and Session
A4