Abstract
GPS positions are used to describe animal movements and to derive a large set of information, for example, about animals’ behaviour, social interactions and environmental preferences. GPS data are related to (and must be integrated with) many other sources of information that together can be used to describe the complexity of movement ecology. This can be achieved through proper database data modelling, which depends on a clear definition of the biological context of a study. Particularly, data modelling becomes a key step when database systems manage many connected data sets that grow in size and complexity: it permits easy updates of the database structure to accommodate the changing goals, constraints and spatial scales of studies. In this chapter’s exercise, you will extend your database (see Chap. 2) with two new tables to integrate ancillary information useful to interpreting GPS data: one for GPS sensors and the other for animals.
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Notes
- 1.
Age class of an animal is not constant for all the GPS positions. The correct age class at any given moment can be derived from the age class at capture and by defining rules that specify when the individual changes from one class to another (for roe deer, you might assume that on 1st April of every year each individual that was a fawn becomes a yearling, and each yearling becomes an adult).
- 2.
The file with the test data set trackingDB_datasets.zip is part of the Extra Material of the book available at http://extras.springer.com.
- 3.
In some cases, a good recommendation is to use a ‘serial’ number as primary key to let the database generate a unique code (integer) every time that a new record is inserted. In this exercise, we use an integer data type because the values of the gps_sensors_id field are defined in order to be correctly referenced in the exercises of the next chapters.
- 4.
- 5.
These categories are based on roe deer; other species might need a different approach.
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© 2014 Springer International Publishing Switzerland
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Urbano, F. (2014). Extending the Database Data Model: Animals and Sensors. In: Urbano, F., Cagnacci, F. (eds) Spatial Database for GPS Wildlife Tracking Data. Springer, Cham. https://doi.org/10.1007/978-3-319-03743-1_3
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DOI: https://doi.org/10.1007/978-3-319-03743-1_3
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