Abstract Data in systems are usually described by information models. In precision agriculture, management data related to soils and crops only have meaning when they are also related to the position to which they apply. An information model is necessary to obtain a common level of understanding. This is a prerequisite for the successful application of electronics and information technology in agriculture; especially because agriculture is a multi-vendor environment, and hardware, software and firmware from different vendors have to work together. The paper describes four different methods (lane table, raster table, pattern table, and polygon table) that can be used to tabulate data for geographical objects. Further, an analysis is made of the different types of data that are or can be used in systems that handle location-specific data. The different types of data can be: data related to an operation (execution of work), with a distinction between product-/produce-dependent and -independent data, data related to a crop production unit, and data collected during the execution of work. An Entity Relationship Diagram (ERD) that represents the different objects and the relations between them is presented. This ERD shows the relations between the different geographical objects, the methods for tabulating the data, and the different types of data itself. The entity types are specified in an appendix.
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