Research Data Management

Research data management (RDM) will help you:

• Save valuable time and resources
• Preserve your data
• Maintain data integrity
• Meet grant requirements
• Promote new discoveries
• Support open access and open data

RDM is the compilation of small practices that make your data:

• Easier to find & understand
• Less likely to be lost
• More likely to be usable during a project or 10 years later

Most importantly you don't want to lose your data!

What is data?

Data is anything you perform analysis on.

Data can:

• Be both digital and physical (i.e. computer files and paper survey responses)
• Be from many fields - sciences, humanities, etc
• Include research notes or lab notebooks, survey responses, software, code, measurements, images, audio, video, and physical samples.

- Data Management for Researchers by Kristin Briney    

Quantitative vs. Qualitative

• Quantitative - numeric data (social sciences, physics, etc.)
• Qualitative - descriptive in nature and deals with the quality of things (anthropology, history, etc.)

Primary vs. secondary data

• Primary data - data that is collected by the researcher for a particular project. This is original data that is created from an experiment or observation. Gathered and maintained by the researcher. 
• Secondary data - data originally created by someone else. For instance, census data or data via open access repositories. 

Other types of data

• Experimental data - derived from controlled, randomized experiments
• Observational data - gathered in instances where it is not possible to conduct a controlled experiment
• Computational data - the output of a computer that has taken a large set of data and run it through a simulation