Outline of the Data Model

The data structures which can be represented using the DX data model include:

1. data defined on a regular orthogonal grid,

2. data defined on a deformed regular or curvilinear grid,

3. data defined on various sorts of irregular grids,

4. unstructured data with no connection between the data points.

In the first case the dependent variable (which is the quantity to be visualised), perhaps for example, temperature, is sampled in a regular grid inside some region defined with the independent variables as axes. Usually the independent variables will be positions in two, three or higher dimensions. Typically inside your own programs such data would be represented as an array of appropriate dimensionality. The second and third cases are generalisations of the first and can be ignored for our present purposes. The fourth case corresponds to particle (or catalogue) data. Here each point is simply a point in an assemblage or cloud of points; there is no connection in terms of either the independent variables (positions) or the dependent variable between the points. An example might be a simulation of a globular cluster where each data point corresponds to a separate star following its own orbit inside the cluster.

Any of the four cases can occur with any dimensionality: one, two, three and higher dimensional data can be represented. Similarly all the usual data types are available: integer, real, double precision, complex etc. The dependent quantity may be a scalar (such as temperature, pressure or energy) or a vector (such as velocity or momentum).

The fundamental entity in the DX data model is an object. Data are represented by the same set of objects both when they are resident in memory when DX is running and when they are stored in native format disk files⁷. There are several sorts of objects. For the present purposes the most important type of object is the field; usually each separate dataset will be represented as a single field⁸.

A field consists of an arbitrary number of components and each component itself has a number of attributes. This hierarchy is illustrated in Figure .

Figure: The hierarchy of items in a DX field. Indenting to the right indicates successively lower levels in the hierarchy.