What is a scientific model?
Looks like a human head, but it is obviously missing certain parts. Of course, this would be a model, and it could be considered a scientific model as it represents the anatomy of the head and skull. It can be used to teach about this anatomy.
To describe particular parts of a phenomenon, or the interactions among a set of phenomena, it is sometimes helpful to develop a model of the phenomenon. Scientific models are representations of reality. They can be a physical, mathematical, or logical representations of a system, phenomenon, or process, and they allow scientists to investigate a phenomenon in a controlled way. For instance, a scale model of a house or of a solar system is clearly not an actual house or an actual solar system. The parts of an actual house or an actual solar system represented by a scale model are, only in limited ways, representative of the actual objects (Figure below).
Scientific modeling is the process of making abstract models of natural phenomena. An abstract model is a theoretical construct that represents something. Models are developed to allow reasoning within a simplified framework that is similar to the phenomena being investigated. The simplified model may assume certain things that are known to be incomplete in some details. Such assumptions can be useful in that they simplify the model, while at the same time, allowing the development of acceptably accurate solutions. These models play an important role in developing scientific theories.
A simulation is a model that runs over time. A simulation brings a model to life and shows how a particular object or phenomenon will behave. It is useful for testing, analysis or training where real-world systems or concepts can be represented by a model. For the scientist, a model also provides a way for calculations to be expanded to explore what might happen in different situations. This method often takes the form of models that can be programmed into computers. The scientist controls the basic assumptions about the variables in the model, and the computer runs the simulation, eventually coming to a complex answer.
Examples of models include:
- Computer models
- Weather forecast models
- Molecular models
- Climate models
- Ecosystem models
- Geologic models
One of the main aims of scientific modeling is to allow researchers to quantify their observations about the world. In this way, researchers hope to see new things that may have escaped the notice of other researchers. There are many techniques that model builders use which allow us to discover things about a phenomenon that may not be obvious to everyone. The National Weather Service Enhanced Radar Images web site (http://radar.weather.gov/) is an excellent example of a simulation. The site exhibits current weather forecasts across the United States.
A person who develops a model must be able to recognize whether a model reflects reality. They must also be able to identify and work with differences between actual data and theory.
A model is evaluated mostly by how it reflects past observations of the phenomenon. Any model that is not consistent with reproducible observations must be modified or rejected. However, a fit to observed data alone is not enough for a model to be accepted as valid. Other factors important in evaluating a model include:
- its ability to explain past observations,
- its ability to predict future observations,
- its ability to control events,
- the cost of its use, especially when used with other models,
- ease of use and how it looks.
Theories as Models
Scientific theories are constructed in order to explain, predict, and understand phenomena. This could include explanations for the movement of planets, weather patterns, or the behavior of animals. In many instances we are constructing models of reality. A theory makes generalizations about observations and is made up of a related set of ideas and models. The important difference between theories and models is that the first is explanatory as well as descriptive, while the second is only descriptive and predictive in a much more limited sense.
A model organism is a non-human species that is extensively studied to understand particular biological processes and concepts. These organisms are chosen because it is believed that discoveries made in the model organism will provide insight into the workings of other organisms, including humans. Model organisms range from single-celled bacteria to complex multi-cellular organisms. Even some viruses are utilized as models, though technically a virus is not considered an organism.
The Table below lists some common model organisms. All of these organisms listed have had their complete genomes sequenced.
|Prokaryote||Escherichia coli||E. coli bacteria|
|Eukaryote, unicellular||Saccharomyces cerevisiae||Yeast|
African clawed frog
- abstract model: A theoretical construct that represents something.
- model organism: A non-human species that is extensively studied to understand particular biological phenomena.
- scientific model: A physical, mathematical, or logical representation of a system, phenomenon, or process; allow scientists to investigate a phenomenon in a controlled way.
- scientific modeling: The process of making abstract models of natural phenomena.
- simulation: A model that runs over time.
- Scientific models are representations of reality. They can be a physical, mathematical, or logical representation of a system, phenomenon, or process, and they allow scientists to investigate a phenomenon in a controlled way.
- A simulation is a model that runs over time.
- What is a scientific model? Give two examples.
- Discuss the importance of scientific models.
- What is a model organism? Give three examples.
- Why are simulations useful?
- What are factors important to evaluating a model?