Their main task is to further develop a connected model and model-storage solution, containing information and key-parameters of various Sevan concepts. The model will contain all the required data needed to perform a range of analyses. This will greatly simplify the tasks of generating inputs for various simulations, as the fundamental information is stored in the same format independent of the software used.
The storage of different model instances will work as a master-reference for different concepts, meaning an update to one part of the model by a user in one discipline, is automatically received and updated for other users working on other parts of the model. If a user wants to test alternative model setups without inflicting the models of other users, the user can branch out and make the changes they need. If the alternative setup then is desired, that branch can be merged back into the main model.
The work will consist of Python programming; completing the model, creating a NoSQL database and schema solution capable of safely storing the model data, and establishing a way of accessing, branching and merging the data using an API.
Looking forward to following the process and see the results at the end.
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