Folder Structure
Folder Structure is an important part of Data Management. When created an organization structure, consider the following to improve your navigation and ease of access to data and files
Best Practices for Naming Files
Not keen on using a physical notebook? Need a digital Notebook for documenting your laboratory and experiments? Try these two Electronic Lab Notebooks.
Your Laboratory and Advisor may have alternatives, discounts and preferred tools in this process. Please consult with them for best options.
You have gathered and stored all this amazing data, and you want to share it with your colleagues and peers! Somehow, you have to take your notes, data fields and content and make it easy for others to understand, interpret and modify. You will need to add Metadata!
Metadata is "data about data".... Metadata also helps organize electronic resources, provide digital identification, and helps support archiving and preservation of the resource. (Source from Wikipedia, on 8/11/2015). There are many metadata standards to consider and each discipline has its own preferred fields and identifying schema. For the purpose of this guide, we'll just cover the basics for fields.
On the most basic level, your data preparation should have three components that will help others understand your data: Column headers, a Data Dictionary, and ReadMe.txt.
Column Headers - A spreadsheet should have a column headers with at the top of each column to identify the data fields. Don't share spreadsheet/.csv that doesn't include column identification.
Site |
Date |
Plot |
SP |
BM |
P |
N |
VO |
5/30/2002 |
L |
AVFAT |
4.25 |
3.19 |
0.01 |
VO |
5/30/2002 |
L |
BRHOR |
5.33 |
3.19 |
0.07 |
VO |
5/30/2002 |
L |
CALUT |
3.33 |
3.19 |
0.01 |
Data Dictionary/Key for Column Headers
Researchers can quickly create a Research Key or data dictionary that provides definitions, expanded abbreviations, and other methodology that occurred in experiments.
Readme.txt Files
Create a .txt file that offers a synopsis of the experiment that includes Time Frame, Subject, Location, Methods and Funding Institutions. This gives future researchers more context and documentation.
Data Testing and Validation
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