Approaches to modeling take many forms. The mathematical, computational and encapsulated components of models can be diverse in terms of complexity and scale, as well as in published implementation (mathematics, source code, and executable files). Many of these systems are attempting to solve real-world problems in isolation. However the long-term scientific interest is in allowing greater access to models and their data, to enable simulations to be combined in order to address ever more complex issues, and to enable common patterns to emerge through parametrization.
The goal of this research topic is to bring together researchers from across scientific disciplines whose computational models require interoperability or for whom there is a need for abstraction. This may arise through interactions between different domains, systems being modeled, connecting model repositories, or coupling models themselves Model-driven approaches, markup languages, meta-data specifications, and ontologies have emerged as pathways to greater interoperability. Domain specific modeling languages allow for a declarative development process to be achieved. Meta-data specifications enable coupling while ontologies allow cross platform integration of data.
The outcomes of this forum will be to better understand the nature of multidisciplinary computational modeling and data handling. Moreover we hope to identify common abstractions and crosscutting themes in future interoperability research applied to the broader domain of scientific computing and health informatics.
Approaches to modeling take many forms. The mathematical, computational and encapsulated components of models can be diverse in terms of complexity and scale, as well as in published implementation (mathematics, source code, and executable files). Many of these systems are attempting to solve real-world problems in isolation. However the long-term scientific interest is in allowing greater access to models and their data, to enable simulations to be combined in order to address ever more complex issues, and to enable common patterns to emerge through parametrization.
The goal of this research topic is to bring together researchers from across scientific disciplines whose computational models require interoperability or for whom there is a need for abstraction. This may arise through interactions between different domains, systems being modeled, connecting model repositories, or coupling models themselves Model-driven approaches, markup languages, meta-data specifications, and ontologies have emerged as pathways to greater interoperability. Domain specific modeling languages allow for a declarative development process to be achieved. Meta-data specifications enable coupling while ontologies allow cross platform integration of data.
The outcomes of this forum will be to better understand the nature of multidisciplinary computational modeling and data handling. Moreover we hope to identify common abstractions and crosscutting themes in future interoperability research applied to the broader domain of scientific computing and health informatics.
