Data management is the process of creating and curating your data in such a way that others can understand and reuse your data. This means that it is important to conceptualize and collect your data in a way that is not only reproducible, but easily understandable to anyone or anything, from other scientists to data-mining programs.
Data management is an ongoing activity - it is not something that you do only at the beginning or the end of a project. As your data evolves, so must your data management processes.
The sources below offer insight into data management best practices, as well as groups and organizations that are committed to understanding and streamlining data management and curation.
In the United States, the Office of Management and Budget's Circular A-110 is the go-to definition for data. It states:
Section 36, (d)(2):
(i) Research data is defined as the recorded factual material commonly accepted in the scientific community as necessary to validate research findings, but not any of the following: preliminary analyses, drafts of scientific papers, plans for future research, peer reviews, or communications with colleagues. This "recorded" material excludes physical objects (e.g., laboratory samples). Research data also do not include:
(B) Personnel and medical information and similar information the disclosure of which would constitute a clearly unwarranted invasion of personal privacy, such as information that could be used to identify a particular person in a research study.
In relation to the above definition, it is important to manage anything that would be considered necessary to validate research findings. Different disciplines will have different standards (and at times, wildly so), so it is important to investigate the best practices for your field.
Talk to your librarian! We can walk you through your specific needs, talk about what's special and important about your data, and set up a plan for how to take care of your data.
Feel free to email me (hlmLO@hampshire.edu) or approach me on campus - I'm always happy to talk about data!