New research data policy at WUR
Data play a key role in research. All scientific research is based on some sort of data, be it surveys, laboratory experiments or interview analyses; and we all agree that it is important to look after our data well. This means not only the safe storage of data during research, but also the long-term storage (‘archiving’) afterwards. To ensure that research data at Wageningen University & Research are safely stored and archived, WUR has established a new research data policy. This blog post outlines the what’s and why’s of this new policy, which is built around three main components: data storage, archiving and registration.
What is this policy based on?
Establishing a policy on research data requires first defining best practices of storing and archiving. How are data kept safe during the research, yet accessible to (specified) others? What makes a data archive reliable? Several sources were used to come up with the criteria that data storage and archiving should meet:
- the Netherlands Code of Conduct for Scientific Practice
- the FAIR principles (on how data can be made Findable, Accessible, Interoperable and Reusable)
- the Dutch Archival law (as this must be met by Wageningen Research)
- criteria met by existing storage and archival services
Of course, confidential data need stricter safety procedures than data that are open to everybody. The regulations were therefore defined separately for data at four different confidentiality levels (following WUR’s Information Security Policy):
- Open: The data is public, there are no restrictions on distribution
- Internal: The data may be viewed by all WUR staff, students and registered external parties
- Confidential: the data are shared within groups
- Secret: the data are strictly protected; access is granted only to specific individuals
To ensure that the new policy would also suit the current research data practices at WUR, the Taskforce Research Data Management interviewed researchers of eight research units. These interviews showed great variation in data types and practices at WUR, but also suggested that several groups were close to meeting the planned policy already. Read more about how the interviews informed the policy in king lear theme forgiveness.
The new policy
Data storage during research
The policy regulations on storage apply to all data produced and/or analysed during research, including video/audio material and code (but excluding administrative data such as emails). The main focus of the regulations is safety: minimising the chance of data loss, leaking and corruption. However, practicality is also important, especially as the interviews indicated that researchers commonly used their ‘own’ solutions, managed within the group. Taking safety and practicality as starting points, the policy lists these allowed solutions:
The assessment of group-managed and cloud-based solutions will be carried out by Data Management Support as of early 2018.
Data archiving after research
Archiving data sets means giving them a safe place for the long term. This protects data sets against corruption and loss, and makes them findable by other researchers. This findability, in turn, encourages the re-use of data, and allows the verification of results (and data are important in this – the https://weblog.wur.eu/introduction-paragraph-comparison-essay-example/ largely relates to errors in the collection/analysis of data). Another positive thing about archiving data sets is that it turns them into research output types in their own right: Most archives ensure that data sets are indexed in other databases and that they get their own DOI; making them findable and citable.
The WUR policy stipulates that 10-year archiving is required for all data sets underlying a publication. The following solutions may be used:
Data Management Support is currently assessing data archives, and will soon provide a white-list with archives that may be used. This will be a growing list; repositories not yet listed can always be assessed.
Data set registration after research
The registration of data sets refers to the adding of its descriptive details to Pure, the system behind richmond essay word limit.
Why register data sets? Data sets are increasingly recognised as valuable research products – by funders, publishers and other organisations (including WUR). Pure currently lists various output types, and WUR believes that data sets also deserve a place in this list. Individual researchers, research groups, and WUR as a whole can then make their data visible and findable.
Group secretaries usually register publications in Pure, but in the case of data sets, Data Management Support will do the registration. All that is needed to get an archived data set registered, is an email with the DOI or link to the data set to Data Management Support.
WUR is serious about data
Research data policies are often received with mixed feelings: we all see the importance of looking after our data, but worry about the time and money this may cost. WUR defines this new policy from the standpoint that data are valuable, and that safely storing and archiving data will pay off in the long term.
By introducing these regulations, WUR shows that it is serious about data. And while there is still a way to go, several groups already meet these regulations – either fully or partially. These groups will be the topic of a series of blog posts appearing early 2018. More information about the policy will also follow around that time. In the meantime, do not hesitate to contact Data Management Support with any questions.
There are 7 comments.
Nice post, thanks.
Out of curiosity, how easy is it to access data that is stored as ‘open’ or ‘internal’? Can you perhaps write something as well about the data discovery and retrieval aspects?
When data are open, everybody can access them. Think of data made available through the public WUR website. Internal data are those accessible only for those with a WUR (or other registered account). This could be data shared on Intranet or another channel that requires logging in. We will soon provide more information about these four categories in relation to data accessibility/retrieval, most likely on the Data Management Support Hub (https://www.wur.nl/en/Expertise-Services/Data-Management-Support-Hub.htm).
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