What is research data?

Within the WUR data policy and research data management, research data refers to any source of information generated and collected to reproduce and verify results, conclusions or other output of your research. This definition results in a wide variety of these sources or information, including video, audio, processing and (statistical) analysis scripts, tabular data, text, interviews, photos / images, etc. The WUR data policy applies to research data only and not to, for example, administrative data (i.e. not research data).

Research data quality - minimal requirements

There are minimal requirements for good quality research data. Data should be supplemented with elaborate data documentation and (administrative) metadata to increase findability, accessiblity, reproducibility and interoperability. For the recommended minimal requirements for data documentation and metadata, see the WUR recommendations.

When there are no legitimate restrictions (e.g. privacy, public safety), research data and metadata should be preserved and accessible in an acknowledged repository, i.e. adhering to certificate (e.g. CoreTrustSeal, ISO certificates) or discipline-specific standards, using a persistent identifier (PID, e.g. a DOI). WUR storage media (e.g. W-drive, Yoda) may be used to preserve sensitive data that cannot be made public, but it is strongly recommended that these data adhere to the FAIR principles and that the metadata is findable and accessible via a PID.

What is research data management?

Research data management concerns the correct handling, storing, preservation, sharing and legal care of research data using the FAIR principles as guidance. It covers a wide array of activities within the research data life cycle including amongst others planning for data management (such as writing data management plans), organising and structuring data, documenting data, and storing / preserving data. The goal of research data management is ensuring that research data is available for a long period, understandable and self-descriptive (so that others could reuse it), follows an organised structure, and can be shared when possible.

Why is research data management important?

It is important that research data are well-organised and cared for during a research project to prevent data becoming unfindable, unusable or even lost. Additionally, because research data often have a longer lifespan than the research project that generates them. Researchers may continue to work on data after funding has ceased, follow-up projects may analyse or add to the data, and data may be reused by other researchers. Without proper care of research data, it may become unusable or even lost to others or yourself in the future.

Support

Questions? Don’t hesitate to contact data@wur.nl.