WUR Data Champions: Plant Developmental Systems

By Jacquelijn Ringersma

Jacquelijn is the Coordinator Research Data Management of th...

Last Summer Wageningen University & Research decided on  new Research Data Management (RDM) regulations. In a series of blogs we will describe some best practices RDM from within WUR: Our WUR data champions. In the blog posts we will indicate how the use case does or doesn’t meet the new regulations. We will also show where and how the Support unit can help in order to be able to match RDM practices to the regulations with minimal effort and maximum result. So, get ready for our first Data Champion!

Plant Developmental Systems

The Plant Developmental Systems group, which is a mixture of WR and WU, studies developmental processes in plants using molecular and genomics tools. Much of the research takes place in the laboratory. Some of the projects running in the group are a collaboration with seed  companies. The group has 5 senior researchers, 2 post-docs, 11 PhD students and 5 technicians. Group leader is Gerco Angenent. So far, the group has 240 publications in WUR Staff Publications of which 24 are datasets.


Data Management practices

Data storage during research: the eLab Notebook is the central application

The common practice was that group members ‘stored’ data and information from experiments in a physical lab journal. Larger data sets were stored separately on a PC or personal external disks. The group is shifting towards a data storage policy where PhD students and staff members  no longer store data on external hard disks. Since 2016, the group uses a Lab Notebook application (ELabJournal). All experimental information, metadata, raw data and derived files are stored within this application. The data within the application are stored on a WUR IT managed (W:\\) drive. All projects are structured in a standard way, which leads to a certain workflow and data storage protocol. Furthermore, the application is fully searchable, which is a requirement for laboratory data management. Within the application, experiments and metadata are coupled to the large data sets avoiding a loss of essential information. Access to the data for both internal collaborators and external colleagues can be arranged per project. ‘As all data are stored on WUR-IT drives, data are safely backed up.

During research, the group maintains the confidentiality level ‘internal’ or ‘confidential’. This means that all data during the research is only shared within the group, or with other collaborating researchers who get access to the data. All research collaborators sign a confidentiality agreement when they sign a WUR contract or are guests.

Within the new data management policy regulations, research data should be stored on WUR W-drive or WUR team sites. Cloud storage solutions or local server solutions are allowed under the condition that an IT member of the Data Management Support team has checked the security of the used system. It is not allowed to use external hard disks or USB-drives. The use of OneDrive, SurfDrive, WUR M-drive[1] or local PC/laptop is not allowed for main storage, but can be used for temporary working copies. For secret data, the use of cloud solutions is not allowed.

Data Management Support gives tips and tools for documenting data along the research lifecycle.

The group has a data storage practice which meets the new regulations.

Data archiving after research: FAIR principles applied

The group has two workflows for storing the data once a research project is finished:

  1. All data remains with the group. Leaving researchers do not have access to the Elabjournal anymore and personal copies are only allowed when agreed in the Exit meeting. In principle, all data generated in a research project is kept for a minimum of 10 years, within the eLab Notebook application.
  2. Data which underlie a publication are archived at The National Center for Biotechnology Information (see this example) or a similar data archive. Usually, the journal publisher of the article obliges the author to archive the data in this archive. Data published at the NCBI are open.

The new data archiving regulations require that all data underlying a publication must be archived in an archive which meets the FAIR criteria.

Data Management Support can assist with archiving data which underlie a publication. The archives which we support are DANS and 4TU.CfRD. These two archives carry the ‘Data Seal of Approval’, meaning that they meet the FAIR principles. If you wish to archive your data in another (domain-specific) archive, this is possible. The archive needs to meet certain sustainability criteria. Data Management Support can advise you on these conditions. Please ask us!

The group has a data archiving practice which meets the new regulations. The NCBI archive which the group uses is (almost) a FAIR archive. Since the trustworthiness of the archive in the domain is large, we do not consider the lack of persistent identifiers on the data sets a knock-out for the archive. Moreover the data set is always linked to a publication with a DOI.

Data registration of published data sets

Data registration in the WUR output registration system Pure (the system behind Staff Publications) has many advantages. First, it is good for the researcher involved; the data sets will appear in his or her publication list and data sets will be linked to publications. This is good news! It shows potential research funders that you are serious about data, and allows your data management practises to be included in your next evaluation. Likewise, it is good for the research group in which you work.

WUR nows requires that data sets which underlie publications are registered in the WUR output system Pure. Pure currently contains around 550 registered data sets.

The Plant Development Systems group currently has no workflow for the registration of data sets in Pure. Data Management Support has run queries in international databases with data sets, and has discovered 24 archived data sets. We have registered these data sets in Pure.

Data Management Support can assist you with the registration of your published data sets. Please contact us.

WUR is serious about data

In 2014, WUR already recognized the importance of RDM. Since then, all PhD students and all university chair groups must have a Data Management Plan, which defines which data will be collected during the research, where the data will be stored, with whom the data will be shared, etc. In 2016, our board realized that RDM should be taken to the next level. The new data management regulations are based on the FAIR principles (and other more formal frameworks), and on use cases in our WUR organisation, such as the one we describe in this blog. While this blog already provides the most important guidelines, more extensive information will be provided early 2018. Join the RDM group on Intranet to stay informed.

Research Data Management (RDM) is important; not just for scientific integrity or the facilitation of the review process, but also for easy research workflows and continuity of research. We hope that the example in this blog has shown this.


[1] WUR M-drive is not allowed because it is a personal drive, which restricts the continuity of research in case the person to which the M-drive belongs suddenly becomes absent.

By Jacquelijn Ringersma

Jacquelijn is the Coordinator Research Data Management of the Wageningen Competence Centre. She works closely together with the Data Management Support team of the Library, IT and DML services.

Research Data Management (RDM) has had her interest since 2005, when she started working for the Max Planck Institute for Psycholinguistics, where RDM was an almost natural part of the academic workflow. From 2011 till 2018 she was the head of the Digital Production Centre of WUR Library. From that time she has contributed to the development of RDM policy and support within WUR.

Jacquelijn is the chair of the Working Group engagement of the National Coordination Point on RDM and a member of the Special Interest Group Agricultural Data of the RDA (Research Data Alliance).

All self respecting research institutes should advocate for FAIR data. Their libraries and IT services should support this to the max.

There is one comment.

  1. […] the serious effort and engagement. Please also read the blogposts on the other WUR data champion: Plant Developmental Systems. And stay tuned: more data champions to […]

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