Model Representation and Simulation in Scientific Inquiry
Summary
Model representation and simulation stand at the heart of contemporary science, providing a bridge between abstract theoretical constructs and empirical phenomena. Models—in mathematical, computational or material form—serve as idealised surrogates that capture essential features of complex systems, from climatic patterns to cellular processes. Simulation extends this representational capacity by instantiating models as executable procedures, permitting exploration of system behaviour under varied conditions and the generation of novel hypotheses. Together, representation and simulation enable scientists to navigate vast parameter spaces, connect multiple levels of organisation and integrate diverse data streams. Critical to this endeavour are choices of abstraction level, parameterisation strategy and validation against real‐world observations. As scientific inquiry becomes increasingly data‐rich and computationally intensive, careful attention to the epistemic roles of models and the reliability of simulation outputs has grown ever more important. This synthesis highlights how advances in model architecture, algorithmic design and exploratory strategies are shaping the global landscape of research, driving both theoretical insight and practical application across disciplines.
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Model Representation and Simulation in Scientific Inquiry publication trend
The graph below shows the total number of articles in model representation and simulation in scientific inquiry across all publications each year (not limited to Nature Index journals).
Technical terms
Model representation: The mapping between a scientific model and the aspects of reality it is intended to capture.
Simulation model: A computational instantiation of a model that can be executed to study system behaviour under varied inputs.
Abstraction: The process of simplifying a system by focusing on key features while omitting extraneous details.
Parameterisation: The assignment of numerical values or functional forms to the variables that define a model’s behaviour.
Exploratory simulation: A simulation approach that probes system dynamics without reliance on a fully elaborated theoretical framework, often by varying parameters and prototyping scenarios.
References
- The Non-theory-driven Character of Computer Simulations and Their Role as Exploratory Strategies. Minds and Machines (2023).
- What is a Simulation Model?. Minds and Machines (2020).
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