Introduction

The PhD Library website is an initiative of the group Plant Production Systems (http://www.pps.wur.nl) of the Wageningen University. Its main purpose is to archive all data that was collected during a PhD study. It’s also used to store your Data Management Plan, which is compulsory for all PhD students at Wageningen University. Read the “Data Management Recipe”.

As a policy of PPS, PhD students must use scripting to process raw data (validating, handling missing data and outliers, data errors, etc.), to analyse the processed data (e.g. using statistics, interacting with other models and/or datasets, GIS) and to generate the results.

At the moment R, Python and Matlab are the most commonly used scripting languages at PPS. The first two languages are open source (free to use) and can be used on almost all operating systems, like Windows, Unix and MacOS.

Please, discuss with your supervisor which scripting language would be most suitable for your work.

For GIS operations, Python and R can also be used, by using resp. the gdal and rgdal module (package). Both are based on the open source QGIS program.

To assist you in scripting, script examples can also be found on this website.

To gain full access to this website (needed for adding content, access to all files), you need to login with your credentials.

Use the search option to look for information within the content of the site, that might be useful for your PhD.

Important

All data must be stored on your local hard disk in a folder called Thesis.

Within this Thesis folder, create a Chapter folder and in this folder create the folders: Data, Model, Paper and Scripts. The Data folder has three sub-folders called: Definitions_Protocols , Raw and Processed.

Final folder Layout:

 Thesis

        Chapter 1

 Data 

        Definitions_Protocols – This folder contains the definition of all protocols

  Raw          - This folder contains all raw data and meta-data (a description of your data).            

 Processed - This folder  contains all processed data. 

              Model               - Folder for complete listing of the model and the model results & analysis.

              Paper                - Folder for Text of a chapter / paper.  

              Scripts              - Contains all scripts used.

       Chapter 2

Data

        Definitions_Protocols – This folder contains the definition of all protocols 

 Raw          - This folder contains all raw data and meta-data (a description of your data).

 Processed - This folder contains all processed data. 

              Model               - Folder for complete listing of the model and the model results & analysis.

              Paper                 - Folder for Text of a chapter / paper.  

              Scripts               - Contains all scripts used.

       Chapter ?

                     Etc. etc.

 

Backup these folders on a daily base on your YoDa-drive.

If you need more space it can be stored on the PPS Backup server. Please, contact M. Lubbers for further details.

If you’re working abroad, you should ask the IT department to create for you a MS-Onedrive account (capacity 500 Gb) for storing your daily backups. As soon as you’re back in Wageningen transfer all content of MS-Onedrive on your M-drive or the PPS Backup server.

For creating daily incremental backups, you may use the GFI software. For installation and usage contact M. Lubbers.

Even though it’s not part of this website, I would like to mention, that for doing surveys we prefer to use tablets and mobile phones using the Open Data Kit (ODK) software (only Android).  This way your survey data will be stored and backed up on our PPS server in Wageningen as soon as your mobile device is connected to the internet. For further details contact M. Lubbers.

 

Data & Documents

Use this section to store per thesis chapter the final versions of your datasets and documents as well as the raw data and meta data. Do it, as soon as you’ve finished a chapter. Also add the full thesis and propositions once you’ve finished your thesis.

Click on the link below for a good example:

http://phd.pps.wur.nl/farming-trees-balancing-act-shade

 

 

First create your own entry, by clicking on the “Add new item...” link on the Data & Documents page. Save your entries once you’ve completed the form.

After you’ve created your own entry, click on it and start uploading documents and/or datasets one by one, by clicking on the “Add data or documents…” link on the bottom of the page (whenever possible store your datasets as a zip-file).

 

Data Management Plan

 

Before entering your own Data Management Plan (DMP), have a look at the “Example Management Plan: Imagine a world with no phosphorus” of Sheida Z. Sattari.

To add your own DMP, click on the link “Add new Data Management Plan…” on the top of the page, complete the form and Save it.

Next reopen your DMP, go the to the bottom section of the page and click on the “Add new data specification..” link, to add the metadata of all datasets you’re going to use for the chapter you’re working on.

The datasets themselves are stored in the Data & Documents section of this website as described before. Update this section whenever you’re going to use new datasets!

Script examples

In this section you find some useful script examples, so you don’t have to start from scratch when implementing you own script. Contact persons for assistance for each script language are also mentioned in this part of the website.

If you’re not familiar with R, it’s perhaps a good idea to do the R-MOOC course on edX (no software installation is needed, it all runs within your browser), URL: https://www.edx.org/course/introduction-r-programming-microsoft-dat204x-0.

Also, some courses on R, Matlab, and Python are offered by the WUR, like e.g.: Introduction to R for Statistical Analysis, An introduction to programming and numerical methods in MATLAB, Programming in Python.