Research data can represent large scientific, socio-economic, and historical values, so it's important that they can be reused to as large extent as possible. In order to be able to reuse data in new research or for other valuable purposes for society, the data need to be findable. The best way of making data findable is to describe the data material in data catalogues, where other people can search for them (for example, the SND research data catalogue). Data descriptions in these catalogues have to be sufficiently detailed so that it is possible to make efficient searches. A description should also include information about how to access the data material and what you are allowed to do with it once you have gained access to it (e.g. specified by licenses).

It is also important that the data remain reusable for a long time. You cannot know whether the data will be valuable to someone in one, ten, or fifty years’ time, so you want to describe and store research data in a way that gives them a good chance to survive for long. So-called certified digital repositories have a long-term perspective on data accessibility, and we recommend that you choose a certified repository. SND is an example of such a repository, and certified according to the CoreTrustSeal.

Whether a file format is readable can change rapidly over time. To minimise the risk that a file becomes unreadable and unable to analyse by future researchers, you should choose file formats with a high probability to remain readable in the future. Those are formats that are common, can be opened and read in several different software applications, and well-documented. In other words, you should be able to find a technical specification for how the format stores information in the file. (You can read more about file formats in the File format section.)

If we want other people to be able to use research data that they haven’t created or collected themselves, the data have to to be well-documented. In this context, “well-documented” means that the data are documented well enough that someone else can understand and analyse them as correctly as possible. (If you want to read more about documenting research data and what to think about if you want to make data reusable, go to the section on data documentation.)

(See the section on the FAIR data principles for research data, as well.)