Data model (GIS)
During the 1970s, the early systems had produced sufficient results to compare them and evaluate the effectiveness of their underlying data models.
[16] The vector logical model represents each geographic location or phenomenon by a geometric shape and a set of values for its attributes.
Although there are dozens of vector file formats (i.e., physical data models) used in various GIS software, most conform to the Simple Feature Access (SFA) specification from the Open Geospatial Consortium (OGC).
[18] It is common to represent a feature by a lower dimension than its real nature, based on the scale and purpose of the representation.
As long as the user is aware that the latter is a representation choice and a road is not really a line, this generalization can be useful for applications such as transport network analysis.
[10]: 89 The raster logical model represents a field using a tessellation of geographic space into a regularly spaced two-dimensional array of locations (each called a cell), with a single attribute value for each cell (or more than one value in a multi-band raster).
Typically, each cell either represents a single central point sample (in which the measurement model for the entire raster is called a lattice) or it represents a summary (usually the mean) of the field variable over the square area (in which the model is called a grid).
[9]: 86 The general data model is essentially the same as that used for images and other raster graphics, with the addition of capabilities for the geographic context.
A small example follows: To represent a raster grid in a computer file, it must be serialized into a single (one-dimensional) list of values.
[18] Raster representations of objects are often temporary, only created and used as part of a modelling procedure, rather than in a permanent data store.
A linear Affine transformation is the most common type of georeferencing, allowing rotation and rectangular cells.
In most GIS applications, lossless compression algorithms (e.g., Lempel-Ziv) are preferred over lossy ones (e.g., JPEG), because the complete original data are needed, not an interpolation.
