Research data life cycle
As a researcher, you work on a daily basis with a wide range of research data. In the course of a project, these data go through various phases of the so-called research data life cycle until they end up in your publication, are published themselves and archived for the long term or deleted according to plan.
Links to supporting material related to individual phases
Data – A life cycle
Your scientific work begins with the project idea and subsequent implementation planning. The steps that follow include data management planning as well as generation, analysis, synthesis and publishing of research data. Depending on the nature of your research discipline, you process data in a variety of file types, formats and sizes and are available in the form of text, code, graphics, tabulated data or audiovisual material.
In order to keep the data available in the long term, they are made available in accordance with the appropriate formats and standards, added to a repository or archive and thus safeguarded in easily searchable form for subsequent use.
Structured data description
A scientific re-use of data is only possible if you carefully back up your data at every point in their life cycle, name your data and provide them with sufficient metadata. These metadata must contain the necessary information and the context regarding the origin of the research data and about appropriate handling of these data.
Increasing data visibility
The phase of active research data management includes the generation and collection of raw data and their analysis. In this phase, you should carefully document the collection of primary data and the analysis processes. This enables subsequent use by you or other researchers and prevents loss of information.
Detailed data management planning at the beginning of a research project is beneficial.
- Store research data in a structured manner and provide them with meaningful names.
- Add metadata to the records.
- Ensure that you can track how you compiled the existing data and findings at each stage of the data life cycle.