Summer Course: Next Generation Data Management in Movement Ecology
Fondazione Edmund Mach, San Michele all’Adige, Trento, Italy. July 1-10 2015
The advancement of a movement ecology theoretical framework has been paralleled by technological progress that allows ecologists to obtain a huge amount and diversity of empirical animal movement data sets. In addition to the increasing spatial and temporal resolution and size of data sets available from tagging technology, locations of animals come with complex associated information related to the environmental context, such as habitat types and vegetation indexes based on remote sensing, population density, weather. This fast-growing process must be matched by proper procedures to manage and integrate animal movement data sets, thus filling leaving the gap between the acquisition of data and the overarching scientific questions. This summer school was designed to support this process: what to do with these data? How to handle, manage, store and retrieve them and how to eventually feed them to analysis tools?
The course is organized in two modules. In the first module (3 days), participants are exposed to basis of spatial databases and SQL. The second module (5 days) is focused on the specific data management requirements of wildlife tracking data. The second module is further divided in three sections: practical lessons to use spatial database for wildlife tracking data management; practical and theoretical lessons to introduce R in connection with the database as tool for data analysis; theoretical lessons to explore general topics of interest in tracking data management (such as use of remote sensing data, concept of landscape variability, dissemination of information on the web and data sharing) and examples of existing e-infrastructure.
The lessons of the first section of the second module are available on this website (see below). For all the other lessons, you can make reference to the official IRSAE web site. IRSAE financially supported and co-organized the summer school.
PART 1 - Introduction to SQL and spatial SQL (Antonio Galea)
- Lesson 01. Explore the basic features of SQL
- Lesson 02. Creating and managing a PostgreSQL database
- Lesson 03. Introduction to spatial database
PART 2 - Spatial database for wildlife tracking data management (Ferdinando Urbano)
- Lesson 01. Storing tracking data in an advanced database platform: PostgreSQL
- Lesson 02. Managing and modelling information on animals and sensors
- Lesson 03. From data to information: associating locations to animals
- Lesson 04. Spatial is not special: how to manage the locations data in a spatial database
- Lesson 05. Environmental layers: integration of spatial ancillary information
- Lesson 06. How to extract environmental information related to location data
- Lesson 07: Consolidation and use of the spatial database: recap exercises
- Lesson 08. Integrating activity data into the database
- Lesson 09. Working with activity data: what the animal was doing there?
- Lesson 10. Data quality: how to detect and manage outliers
PART 3 - Tracking data analysis with spatial database and R (Mathieu Basille)
- Lesson 01. The movement model: implementation
- Lesson 02. There and back again – part I: Analyzing movement data in the R environment
- Lesson 03. There and back again – part II: Connecting PostGIS and R
- Lesson 04. The movement model: recap and integration with the database
- Lesson 05. There and back again – part III: Extending PostGIS with Pl/R