Scientific modelling - prototype SCMO


The identification of the relevant mathematical principles and scientific theory within an information systems framework, to solve real-world problems.

Guidance notes

Scientific modelling activities include - but are not limited to...

  • creating, testing and tuning scientific models through the application of computing.
  • validating and interpreting models implemented in information systems against the reality which models attempt to represent.

Scientific modelling - prototype: Level 7


Directs the creation and review of a cross-functional, enterprise wide approach and culture for scientific modelling. Leads the development of the organisation’s scientific modelling capabilities and champions its use in solving real world problems.

Scientific modelling - prototype: Level 6


Sets standards and initiates the creation, testing, improvement and application of mathematical model frameworks that represent real world systems and scientific theories. Oversees the representation of science and mathematics principles and theories in models to ensure appropriate, consistent and effective usage. Develops or introduces new mathematical techniques where necessary.

Scientific modelling - prototype: Level 5


For a given real world problem, identifies the lack of existing models and creates new mathematical representations of the underlying science that can be implemented in an information systems framework. Applies advanced programming techniques to implement scientific models and apply these for problem solving. Analyses the functioning of existing models to improve accuracy and performance. Communicates limitations such as uncertainty and systematic errors. Ensures appropriate usage of models.

Scientific modelling - prototype: Level 4


Analyses the real world problem, then selects appropriate physical and mathematical models to approximate the phenomena under investigation. Applies relevant mathematical techniques to simulate the problem. Conducts quality and performance assessments on model outputs and makes improvements to the models. Provides advice and guidance to those using these models.