1. Data organization

3. Purpose of data organization
We live and work in a data-rich environment
All that data must be stored somewhere
Traditionally, all this information held in physical support: papers in folders in filing cabinets
Nowadays: computers, hard disks, distributed file systems, the cloud
Good thing about new systems: they don’t take much physical space
Bad thing about it, you may lose control over your files soon

6. Temp. R First. R Test. R Test2. R Final. R Final_2013_06_24
Temp.R First.R Test.R Test2.R Final.R Final_2013_06_24.R ReallyFinal.R ReallyFinal_JO.R ReallyReallyFinal.R ISwearIfIDoAnotherVersionIllKillSomeone.R

7. Types of data
CSV files

8. Types of data
GIS files: shp, raster…

9. Types of data
Programming files

10. Types of data
Images: maps, plots, charts…

11. Types of data
And, of course, plain text files

12. How to organize There is no “right” way of doing this…
But the more intuitive, the more likely to remember
The sooner, the better
Follow a well designed hierarchy of folders, maybe starting with project folder
Store each file type in a separate folder

13. Example Project – BITW2013 code Datasets Documents … Monday Tuesday R
Tutorial.R
Datasets
shp
Africa_polygon.shp
Worldclim …
Documents
Handouts
Monday
Tuesday