"Research data management concerns the organisation of data, from its entry to the research cycle through to the dissemination and archiving of valuable results. It aims to ensure reliable verification of results, and permits new and innovative research built on existing information." - DCC(1)
Research data have a longer lifecycle than the period in which they were created. One way to look at it is by using a research lifecycle. The meaning of the data varies with every phase of the research cycle they are in.The image to the right depicts such a cycle.
A research lifecycle is intended to help illustrate how the various phases in the life of research data tie in with each other and how the choices you make in one phase influence the data quality in the other. A lifecycle helps to shift the short-term perspective to a long-term one: what is the intended purpose for these research data? How do you make sure that the choices you make when you collect data are robust enough to enable reuse and long-term storage?
There are many lifecycles in circulation and all are tailored to a user group’s needs. The image to the left is the lifecycle of environmental sensing research, in which the scientific output derived from it is depicted.
Data archives focussing on long-term storage sometimes use the term digital curation lifecycle.(4) It provides a detailed description of the steps an archive takes after entering a dataset. The lifecycle comprises activities focusing on the primary goal of a data archive: long-term storage and availability.
Essentials 4 Data Support
An in-depth look
- There are quite a few data lifecycles in circulation. Staff of the University of Bath wrote an article(5) in which they compared the various models. What are the recurring elements in each lifecycle?
Sources and additional reading
What is your experience with research lifecycles? Do you prefer a particular lifecycle? If so, why?
Do you want to comment on this section? Lease let us know by posting a comment.