With a chart you can analyze information from your models and present them in an understandable and visually appealing way. Charts can have a supportive function, e.g. in portfolio management, but they can also be used in dashboards. Charts are available in Amber, ArchiMate® and BPMN™ models.
Chart data input
Population and dimensions
The information shown in a chart is defined by two parameters:
- the population, and
- the dimensions of a chart
The population defines the elements of the model on which information is displayed. An example of such an element is a project in a model.
Dimensions define the different types of information that is shown for each element from the population. Examples of types of information are the costs, benefits and risks of a project. This information can be stored in the model by using the profile attributes of the project. In our example the dimensions are defined by the project attributes.
Depending on the type of chart one or more dimensions can be displayed and related. A bubble chart for example can display minimal two and up to four dimensions. For example, in a bubble chart projects can be represented via bubbles, with their position on the x-axis showing the costs, their position on the y-axis showing the benefits, and the size of the bubble showing the project risks. Color can be used as the fourth dimension, for example to distinguish strategic and non-strategic projects.
Example of a bubble chart
Manual data input or by script
A chart can be defined in two ways: manually or by using a script.
With a manual definition you can determine the population and dimensions of the chart. The population is defined by selecting objects from the model. Dimensions are defined by selecting profile attributes containing the information to be visualized.
With a definition via script the script determines the population and the dimensions. For each element from the population the script defines a data structure that is passed to the chart. By defining a script and linking it to the chart, the chart can be filled with data.
Prerequisites for working with charts
Charts particularly have value when there is suitable information in your models defined by a profile. A profile is formed by a set of properties one can assign values to. In addition to the profile that is assigned to the elements of a model by default, with properties like name, it is also possible to assign other profiles to the elements. These additional profiles enable you to fill in specific values for element properties that may be relevant to certain analyses.
Profile information that is suitable for charts mostly concerns numbers, amounts and dates. This applies to most charts. One chart (the table) can, in principle, handle all kinds of data, including strings.
Before you start working with charts it is therefore important that a profile containing information suitable for charts, is available in your model.
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