Research data is loosely defined as information collected, observed, or created for purposes of analysis to produce original research.
This includes observational variables like rainfall, wind speed, water quality, or survey data; simulated data from earthquake models; experimental data from lab instruments; and derived or compiled data for text mining or testing algorithms. Research data can take almost any digital file format (video, text, photographs, numbers), so managing it effectively can be a challenge.
If you've found this page, it's likely that you manage some form of research data, either your own, your lab's, or your advisor's. Many researchers are not taught data management skills in their graduate courses. This guide and accompanying workshops aim to help fill this gap with the expertise that librarians and data specialists can offer.
Good data management:
"By learning how to preserve and share digital materials so others can effectively reuse them, you will maximise the impact of your research" (Digital Curation Centre)
Data that you generate with or for your research should be available to other researchers to help verify and advance your work. By becoming a good steward of your data, you will have a framework in place to help you keep track of your data, your data will be citable, you can help your graduate students achieve their goals quicker, and you will be helping future researchers in your field of study.