In broad terms, conceptual modelling is the process of developing a graphical representation (or model) from the real world. In the context of collaborative problem-solving it provides an easily understood representation of the system for the different stakeholders involved. The process of conceptual modelling requires decisions to be taken regarding the scope and level of detail of the model. These decisions should generally be a joint agreement between the modeller and the problem owners i.e. the stakeholders who require the model to aid decision-making. It also requires assumptions to be made about the situation concerned. The conceptual modeller has to determine what aspects of the real world to include, and exclude, from the model, and at what level of detail to model each aspect. The conceptual models talked about below can also be thought of as non-software specific descriptions of the situation under inquiry – describing the objectives, inputs, outputs, content, assumptions and appropriate simplifications required. In this wider sense those making conceptual models may be facilitators helping groups of stakeholders better understand their situation.
Conceptual models also provide a useful starting point for participatory or collaborative modeling efforts. They help different stakeholder groups establish a common language that facilitates more innovative planning and evaluation. A number of pages cover related approaches to problem structuring and framing, especially systems thinking, systemic design and systems thinking tools. Conceptual models have a number of uses in collaborative decision making. However, the following links lead to resources looking at how these approaches can support the development of more detailed computer models and decision support systems.
Conceptual models – What are they and how can you use them? This 2017 post by Andrew Powell-Morse provides a good introduction to these models. He explores what conceptual models are, how they are most commonly implemented, and touches on a few advantages and disadvantages of using conceptual models in the realm of software development.
Research on conceptual modelling : less known knowns and more unknown unknowns, please. This 2015 paper by Jan Recker argues that the field has become entrenched in some “bad habits” that usually emerge in evolved paradigms and that we need to proactively pursue a dual research strategy incorporating new and different avenues that lead us to novel and impactful research contexts of conceptual modelling. He provides a framework that can guide this exploration and finishes with some recommendations about how conceptual modelling research programs could proceed.
Conceptual modelling: Knowledge acquisition and model abstraction This paper by Kathy Kotiadis and Stewart Robinson looks at the processes involved in arriving at a conceptual model. This paper contributes to this understanding by discussing the artifacts of conceptual modelling and two specific conceptual modelling processes: knowledge acquisition and model abstraction. Knowledge acquisition is the process of finding out about the problem situation and arriving at a system description. Model abstraction refers to the simplifications made in moving from a system description to a conceptual model. See also systems thinking tools which provide more detail on the use of rich pictures and SSM.
Choosing the right model: conceptual modeling for simulation This paper by Stewart Robinson looks at what to include in the simulation model and what to exclude. The process of determining what to model is known as conceptual modeling. He acknowledges a balance in getting the right level of detail – make it too complex and it may not be possible to complete the model with the time and knowledge available, make it too simple and the results may not be sufficiently accurate. In this paper we explore conceptual modeling first with an illustrative example from a healthcare setting. Conceptual modeling, its artefacts and requirements are then defined. Finally, a framework for helping a modeler to determine the conceptual model is briefly outlined.
Conceptual modelling: framework, principles, and future research The conceptual modelling stage in a simulation project is very important and yet is still generally regarded as more of an art than a science. In this paper Roger Brooks sets out some of his views on conceptual modelling. The meaning and nature of conceptual modelling are discussed and a framework set out. The overall aim should be to choose the best model for the project and conceptual modelling can be viewed as a difficult optimisation problem that can be tackled effectively using a creative search process that develops alternative models and predicts their performance throughout the project. Based on advice from the literature and personal experience 17 principles of conceptual modelling are suggested.
Developing conceptual models is also a key step in developing indicators for sustainable and performance-based management. Another related page in this section provides a number of links outlining how to develop programme-based outcomes models , also called intervention logic models. A number of pages cover related approaches to problem structuring and framing, especially systems thinking, systemic design and systems thinking tools.