For help finding, using, managing, or archiving your research data, contact firstname.lastname@example.org.
Data management is not just the responsibility of the researcher who has created or collected the data. Various parties are involved in the research process and may play a role in ensuring good quality data, safeguarding them and facilitating data sharing. It is crucial that roles and responsibilities are assigned and not just presumed. For collaborative research, assigning roles and responsibilities across partners is important.
People involved in data management and sharing can include:
You should also consider whether any particular training may be needed for any staff involved. Your institution or specialist organisations may coordinate or provide training in various aspects of research data management.
Research centres and large-scale projects can also consider how best to support researchers through a framework of shared best practices, guidance and policies.
Sharing data (with others or within a lab over time) is impossible without proper data documentation. "Metadata" is data about data. It's structured information that describes content and makes it easier to find or use. A metadata record can be embedded in data or stored separately. Any data file in any format can have metadata fields. In social science, this record is called the "codebook" or "data dictionary."
There are many metadata standards and which one is right for your data will depend on the type, scale, and discipline of your research project.
Some examples of metadata standards are:
For more examples, see the Research Data Alliance Metadata Directory.
If your field doesn't have a metadata standard (it may not be listed above) or if you just need a simpler system to keep track of data within your own lab, consider that there are three main types of metadata addressed by most standards:
Also consider this advice from the UK Data Archive [pdf]:
Good data documentation includes information on:
At the data-level, documentation may include: