An FAQ on Research Data Management and Data Ownership
Data custodianship and ownership
Yes. For example, when you store your data files with a cloud service that has its servers located in the US, like Dropbox, you fall within US jurisdition. The US is subject to the Freedom Act. US authorities can demand the details of your account. If you wish to use a cloud storage service, it is better to use SURFdrive. This is a service developed for Dutch educational institutions and has its servers located in the Netherlands. Contact the IT Servicedesk if you would like a SURFdrive account. Note that cloud storage is not suitable for all data types. This depends on the confidentiality level of the data.
No. According to the verifiability principle of The Code of Conduct for Academic Practice whenever research results are published, it is clear what the data and conclusions are based on, where they originate from and how they can be verified.
Yes. Individual researchers may be challenged to be transparent about the choices that they've made for Data Management and data sharing. These choices need to follow Wageningen University & Research's ethical guidelines. The Code of Conduct for Academic Practice states that raw research data should be kept for at least 10 years and in such a way that they can be consulted at all times with a minimal expense of time and effort. This means carefully thinking about Data Management Planning.
Planning my research - preparing for data collection
It is important that Data Management Plans, and the day-to-day data management practice, follow WUR’s research data policy. This policy outlines the regulations on data storage, archiving and registration.
Yes, we do. You can find the template and examples on our Support page on Data Management Planning. In the template you will find information on how to fill in your Data Management Plan.
Most funders have requirements on data management planning and data publication. We have compiled details for NWO/STW, Horizon 2020, ZonMw, NSF and RCUK on this support page.
You can use several sources to look for datasets:
- DataSearch lists datasets from various disciplines. It also contains supplementary data from scientific articles.
- DataCite also lists datasets from a range of disciplines.
- ScholeXplorer collects links between datasets and literature. This way it enables you to find datasets underlying articles, or articles based on datasets.
- Re3Data lets you browse data repositories rather than datasets. Once you find a suitable repository, you can look for a dataset on the repository website.
- Staff Publications lists datasets in different repositories by Wageningen University & Research authors.
- Zanran is a service that scans the public internet for webpages that contain numerical data or statistics.
Visit our page Finding research data for more tips.
Doing my research - managing current data
You can protect your data from incidental loss by using a storage medium that is secure, by making regular backups and by ensuring that the backup of your research data is as independent as possible from the main storage. See 'Storage solutions' for more information.
Wageningen University & Research offers different managed storage solutions to securely store your data. You can choose personal or shared storage solutions with backup options. For all additional options see our support page 'Storage solutions'.
By documenting your data files you give subtitles to your datasets. What is your data about? Concise and clear data documentation helps you as well as current and future users to understand the context in which your data were collected and increases the chance your data can be found, understood and reused. See our support page 'Data documentation' for more details on how to prepare data documentation.
Wageningen University & Research has a High Performance Computer facility. The HPC can be used for variety of research applications within the domain of the life sciences. Are you interested in using the HPC? Have a look at the service page 'High Performance Computing Cluster (HPC)' for more information.
How can I securely exchange/collaborate on my research data with others inside and outside the institution?
The exact solution depends on several factors:
- Who needs access to your research data and from where?
- What is the confidentiality classification of your research data?
- Do you just want to transfer data or do you wish to collaborate?
Depending on your answers we offer project or department shares through the W drive, through the creation of a Team site or through the use of the FTP-service. See 'Exchanging data' to choose the option that best fits your needs.
To collaborate on source code, Wageningen University & Research has developed Git@WUR.
Finishing my research - keeping and publishing final data
Raw research data should be kept for at least ten years. The Code of Conduct for Academic Practice states you have to make the data available on request to other academic practitioners, unless legal requirements dictate otherwise. Journals and learned societies may also demand a certain data retention period which is never shorter than ten years.
Following WUR’s research data policy, any datasets underlying research data should be archived in a repository.
In general, most journals encourage data publishing but data availability policies differ on a journal to journal basis. We have compiled a list of the data availability statements for the top 20 journals in which Wageningen University & Research researchers publish. See 'Journal Requirements'.
WUR’s research data policy stipulates that you should archive datasets in a repository if these datasets underlie any publications. The policy gives various archiving options for these, such as the national data centres DANS-EASY and 4TU Centre for Research Data. Visit our pages on data repositories and on the data archiving policy for more information.
Following WUR policy, datasets that underlie publications must be archived in a data repository. Such datasets should include all data files and documentation (additional explanation of these files) needed to reuse the data and verify any results presented in the publication. More information on what data to archive can be found on our page about data archiving.
Datasets that do not underlie any publications can also be published – this is in fact recommended if these datasets can be of value to other researchers. The flow chart below may help you to decide on whether to publish such data.