You should describe your data and record the steps you took with them during your research process. This will enable you to remember and repeat parts of your research process, as necessary. Other researchers will also be able to see and replicate the steps you took. Documenting information about your data will make them easier to organize, locate, and cite.
In this module, you will learn best practices for documentation. Note that metadata is the term used for information describing data. For example, metadata fields might include date, author, publisher, etc.
Record metadata about the original data, whether you collected that data yourself or used data someone else collected. Some examples of typical metadata are: who collected the data, how they were collected, variable names, etc. We will introduce you to techniques for recording and organizing your metadata.
Record metadata about your analysis data files and the steps you took to create them. We will introduce you to techniques for recording and organizing both your research steps and your analysis metadata.
This module is a basic introduction to the concept of documentation. There are various protocols for documentation that are more complex and sometimes discipline-specific. One example in the social sciences is the Tier Protocol, which goes into much more detail on documentation than is presented here.
Learning through Example: Political Science Research Project
For the final project in a political science course, you have a research assignment related to the U.S. electoral process that requires the use of data. You have decided to explore how same-day voter registration laws affect voter participation rates among different racial groups.
We will step through the process of documentation for the political science project. The data you have obtained consists of data from the Minnesota Secretary of State's office about voter turnout before the same day voter registration law went into effect, and exit poll data you collected from the most recent election.