I have been struggling for quite a long time now with keeping my project files organized.
What are your tips for keeping your datasets, images, shapefiles, etc.. organized?
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Note: This rant will be updated as I go
I'm no computer or ArcGIS pro by any means, but here's what I do:
projectsfolder, and are hosted on my internet server, local computer, and dropbox. I always have access to them, and they are very organized, dis and aggregated. You'll spend a lot of time organizing these.
my_projectsfolder. It contains everything related to that project as in, if I copy and paste that folder somewhere else, it will contain everything.
draft_ver5_Dec_31_11__12_30.doc. Again all my final deliverables go in in the FINAL folder
my_projects/codefolder. I do this as most of the python code is reusable. If you put all your python code besides the projects, you'll forget about them. Also, all my python code goes on github.
You did not state that you only work with Desktop GIS software, so I'll share some of my experiences from the programming oriented mindset. Let me first start by saying that I agree with of the things @dassouki says. I think the most important thing is not how you organize, but that you do this.
But to go on to my workflow. What I like about using a programming language (R in my case) is that the script I write documents all the steps I take. This is in contrast to using ArcGIS where I think it is harder to see how a user went from the raw input data to what you can see in an mxd file. Ofcourse you can keep a log of all the steps you take in the GUI, but I think a programming language lends itself much better to saving the exact workflow you took. This can be particularly important when a client/supervisor asks how you did something, or what you exactly did to produce a certain product.
So in practice I have several folders on my drive that are important (note that I am a scientist):
Some main ideas I use:
In general I like using a programming language because in one script you can go from the raw data to the resulting pictures/tables. R is quite a good candidate because it can read and write GIS data easily and has a ton of analyses on board, both GIS and statistics.
I would just like to add to the above answer - 2 things.
I like to have folders in the import raw data directory - folders for each time a receive a dataset - i.e. from_clientname-2011dec23. This way i can trace back when i received each piece of data used in the project.
I also like having a project doc folding on the go - i can then create either a word doc or a simple TXT file in here that i can write down what i did on the project, date, and who requested it. That way i can go back and cover myself off is someone questions why i did something. This may sound tedious for small requests, but it can save you in the end.