Data organization

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

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

Types of data CSV files

Types of data GIS files: shp, raster…

Types of data Programming files

Types of data Images: maps, plots, charts…

Types of data And, of course, plain text files

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

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