Preserving is more than a backup. It is a set of actions, which ensure long-term retention of the integrity of data, by maintaining its (a) accessibility, (b) authenticity and (c) longevity. Digital objects are fragile, being susceptible to “data rot” which might influence their accessibility and authenticity. Preservation aims to ensure that datasets are in the best shape to be stored, discovered, accessed and re-used. It implies recurring activities.
There are different digital preservation methods, such as migration, emulation, digital archaeology, and technology preservation.
Preservation is usually carried out by archives, data centers or data managers after data have been submitted by the data producer. However, data producers can facilitate the process by performing good data management practices in the preceding steps of the data life cycle.
http://www.dcc.ac.uk/resources/how-guides/cite-datasets (DCC How-To-Guide)
http://databib.org (useful data repository registry)
http://www.re3data.org (useful data repository registry)
http://en.wikipedia.org/wiki/Data_degradation (Information about data degradation)
Recommended citation:
German Federation for Biological Data (2021). GFBio Training Materials: Data Life Cycle Fact-Sheet: Data Life Cycle: Preserve. Retrieved 16 Dec 2021 from https://www.gfbio.org/training/materials/data-lifecycle/preserve.