Preservation
Data preservation aims to keep both content (data) and context (metadata) safe for future reuse. Preservation is made significantly easier when considered in your data management planning process.
The efforts mentioned in the previous lifecycle steps aren’t one-off exercises. Every decision you make before starting a project has clear repercussions on its evolution. The storage location chosen affects file management and formats and this will affect preservation. Therefore, as you carry out your research, you need to routinely think about data management, storage, and preservation, although the first two are a priority earlier on in the process.
Throughout the life of a project, you might realise that your approach to research data management has become outdated or unfit for purpose – if so, you can make changes to the original data management plan. However, you should keep in mind that any decision will affect all subsequent steps in the research data lifecycle so these should be revisited, too.
Here, we discuss how you can protect research data during a project. This includes technical considerations (i.e. security, preservation) and legal ones (i.e. data protection regulation). We also shed light on the topic of managing software created within a research project. Although this is often not regarded as data, it actually is. Researchers sometimes treat software as a means to an end, yet it is an essential part of the research process and should be documented and shared. In addition, note that the availability of the computer code behind a study (if any) is an enabler of research reproducibility.
Many of the issues discussed in this section are relevant for both active data and archival datasets. The former is data that is added as a research project develops, while the latter are the final outputs underpinning your work.
Data preservation aims to keep both content (data) and context (metadata) safe for future reuse. Preservation is made significantly easier when considered in your data management planning process.
Only authorised people should be able to access research data, so it must be protected using appropriate tools. Data security includes measures to protect data in worst case scenarios.
The General Data Protection Regulation (GDPR) deals with all information that allows you to identify a person. There are specific rules to follow and serious fines in the case of non-compliance.
Personally-identifiable information needs to be treated very carefully. It is indispensable in many research fields, although its misuse might lead to high fines and ethical issues.
Software is often created to analyse and manipulate research data. Just like any other research output, software needs to be managed, stored, and preserved to allow future reuse.
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