Preliminary Processing of Movement Data

Data processing …

is the least loved and most time consuming aspect of any data analysis!

It is also unavoidable and extremely important.

Goals

Facilitate Analysis!

Principles

Smart data processing is:

• compartamentalized - e.g. each step a function
• interactive - leverage visualization and interactive tools
• generalizable - to apply to multiple individuals
• replicable - important: NEVER overwrite the raw data!
• well-documented - so you don’t have to remember what you did
• forgettable! - so once its done you don’t need to think about it any more

Tools

Several packages are particularly useful for data processing and clean-up:

• plyr - manipulating data frames and lists
• functions: mutate(); ddply()-ldply()-dlply()
• lubridate - manipulating time objects
• rgdal - projecting coordinates
• maps and mapdata - quick and easy maps
• magrittr - for piping

Example: short-toed eagle (circaetus gallicus)

Data: Ugo Mellone - Universidad de Alicante, Spain