Data Management can be defined as providing the appropriate labeling, storage, and access for research data. We recognize that best practices for each of these aspects of data management can and often do change over time, and are different for different stages in the data lifecycle.
Data Life Cycle
We find it useful to think about the life cycle of research data, which includes:
- Initial generation of raw data
- Analysis of raw data, generating analyzed data
- Short-term storage of data
- Publication of data, including providing access to data e.g. through a lab database
- Sharing of data with public repositories
- Long-term storage of data to meet requirements of NIH or other grant agencies and/or the institution
- Culling of data at appropriate times after its generation
- Archiving of data as part of an historical record.