Abstract
In this paper we present our strategy and implementation of a datacentric modelling framework (SOFT, SINTEF Open Framework and Tools) with focus on information interchange in throughprocess and multiscale applications. SOFT needs to accommodate for a inhomogeneous set of in-house open source and proprietary simulators, often written in different programming languages, and storing data in different formats. The complexity and diversity of such a system requires that we have formal schemas and structures of metadata that allow for information interpretation regardless of the original storage formats, which application produced the data, and which application processes the data. We propose a standard for data exchange, separately describing metadata specific to different knowledge domains.
SOFT, via a mechanism of plugins, offers the possibility to utilize different tools for storage of such data and metadata. Further, SOFT facilitates scientific software development by clear separation of numerical routines and platform-dependent input, output, and analysis routines. Automated testing and simulation data analysis are also achieved in SOFT via external plugins and interfaces to scripted languages such as Python and Javascript. The framework has been developed and tested within such flow modelling projects as LedaFlow, NanoSim and SimcoFlow
SOFT, via a mechanism of plugins, offers the possibility to utilize different tools for storage of such data and metadata. Further, SOFT facilitates scientific software development by clear separation of numerical routines and platform-dependent input, output, and analysis routines. Automated testing and simulation data analysis are also achieved in SOFT via external plugins and interfaces to scripted languages such as Python and Javascript. The framework has been developed and tested within such flow modelling projects as LedaFlow, NanoSim and SimcoFlow
