Data management lesson

I was the lead instructor at a [bootcamp](http://damienirving.github.io/2014-02-10-hobart/) for weather, climate and ocean scientists in February 2014, for which I prepared a novice level Python lesson on data management. The main messages in this lesson would be relevant to all areas of research, so I am hoping to get feedback/assistance on how best to generalize the lesson. So far I am thinking that I will:

* Replace the content that depends on the `cdms2` library, as it is not easily installed using a package manager like `pip` or `easy_install`
* Perhaps use HDF5 instead of the netCDF file format???
* Perhaps find some wind speed data that can be downloaded more easily than the CMIP5 data??? (although it would also need to have an instructive data reference syntax)    

A static version of this initial commit can be viewed [here](http://nbviewer.ipython.org/gist/DamienIrving/7572585). 

I have a feeling that the content of this lesson is also highly relevant to (but perhaps not yet covered in) the data carpentry materials that people have been working on lately...