Good research data management implies that digital and analogue research data is managed in a professional and careful manner throughout all the stages of research projects (i.e., the design, collection, processing, analysis, long-term preservation, and sharing of research data).Research data include any materials or information sources that were collected, processed and/or analyzed to generate, support or describe research findings. Examples of research data produced and used at SBE include text files, spreadsheets, surveys, code books, scripts, audio recordings, computational models, databases from secondary sources, specimens, etc.
SBE views good research data management as one of the prime responsibilities of researchers at the faculty. SBE encourages good research data management practices among its researchers to ensure:
- Research integrity
- Data security
The SBE Research Data Management Policy and this website provides a guide on how researchers can adopt good data management practices as well as information on the services offered by the faculty that can enable researchers to adopt these practices.
A useful basis for responsible data management are the FAIR principles. The FAIR principles were first introduced in 2016 when the ‘FAIR Guiding Principles for scientific data management and stewardship’ were published in Scientific Data. FAIR stands for Findable, Accessible, Interoperable, Reusable. These principles call for research data to be stored safely, carefully curated and made available for reuse as widely and as early as possible. It is important to note that adopting the FAIR principles does not call for openly sharing all datasets, instead data should be “as open as possible, as closed as necessary”.
More information about FAIR data can be found on the libguides of the VU library.
Benefits of RDM for researchers
The benefits of good data management practices for researchers include:
- Increased research efficiency
- Increased visibility and impact
- Wider dissemination and increased impact of results
- Enhanced data security, by minimizing the risk of loss, theft or misuse of data
- Legally and ethically compliant processing of (privacy) sensitive data
- Ability to meet requirements of funding agencies such NWO and European Research Council that increasingly request data management plans.
Data Management Plan
SBE encourages the use of data management plans (DMP) for documenting how data will be handled along the different stages of a project. A DMP is a document that describes a research project as well as how researchers will handle data during and after the research project. It includes information on data collection, storage, processing, protection for privacy, sharing, archiving and publishing. DMPs are mandatory for PhD candidates at the SBE and for projects whose funding agencies require them to submit one. The European Research Council (ERC), the Dutch Research Council (NWO) and ZonMw are examples of research funding bodies that require DMPs.
Data management plans can be created using the DMPonline tool that has built-in templates for most funders and guides on how to respond to questions. The VU library libguides also provide useful information on creating data management plans. Questions can be directed to the faculty data steward (email@example.com).
The ethical handling of data also forms an important component of good research data management. All projects that deal with data on human subjects are required to undergo an ethics review. Human subjects are people that partake in, or are subject to, research in which data on or from these people are being collected. This includes people that might be representing themselves or the interests of others or an organisation in an experiment, interview, survey, online data source and observational study.
Researchers can check whether their project need full ethical review using the online self-check tool available here. More information on research ethics and integrity at the SBE are available on the website above.
Privacy and Security
Safeguarding the privacy of human subjects participating in research is essential for data management. Research that deals with personal data i.e. data relating to an identified or identifiable natural person must be handled in line with the European General Data Protection Regulation (GDPR).
Special attention should be paid to personal data that has been classified under the special categories of data i.e. racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, genetic data, biometric data, health data, data on a person’s sex life or sexual orientation, or data concerning criminal convictions and offences. The Privacy Five Step Plan explains the five main considerations to take when processing personal data.
These slides provide an introduction to the GDPR and its implications for research at SBE. Researchers are strongly advised to contact the faculty privacy champions for advice on the GDPR and privacy (firstname.lastname@example.org).
The VU library libguides also provide useful information and resources.
During research, data should be stored securely and professionally, meaning that measures have been taken to prevent data loss and data leakage. An overview of other data storage options is available on the VU Library libguides.
SBE encourages the use of Research Drive for the storage of research data. Research Drive is designed as a collaborative, GDPR compliant cloud storage service that is particularly suited for the storage of personal and sensitive data. It is also ideal for the storage of large datasets.
In addition to the use of Research Drive, projects that process sensitive data should make use of additional security measures such as anonymisation and pseudonymisation and encryption. The faculty data steward can be contacted for advice on appropriate storage options, anonymisation and data encryption (email@example.com ).
Researchers processing big datasets can make use of SciStor Storage for Scientists cloud storage offered by the VU. Researchers that prefer to use other storage platforms that are considered best practices in the field are encouraged to share these with faculty’s data steward (firstname.lastname@example.org ).
Upon publication and project completion, all data generated at SBE as well as the documentation detailing how the data was collected and processed should be stored (archived) in a recommended repository such as DataVerseNL for a minimum period of ten years. Questions on the appropriate institutional or discipline specific archive can be directed to the faculty’s data steward (email@example.com).
Whenever possible, researchers are encouraged to store datasets, replication code and data documentation on journal websites as supplementary material for published articles.
Archived and published datasets that have been generated at SBE should be made findable (the F in FAIR) by registering the dataset in Pure. A guide on dataset registration is available here.
Researchers who publish datasets along with a paper or in a discipline specific repository can link those locations in their Pure registration, preferably with a persistent identifier. When the dataset itself is not made publicly available, the dataset registration should explain the reasons for that.
Open Science is a growing international academic movement that aims for accessibility of scientific publications and data, and dissemination to society. It encompasses practices such as preregistration of studies, open Access publishing; making it easier to publish and communicate scientific knowledge, making data FAIR and attributing credit to scientific contributions that go beyond impact factor.
SBE supports the open science movement and encourages researchers to preregister their research plan, hypotheses, methods and or analysis prior to the start of a research project. Preregistration of studies increases research credibility and transparency as it differentiates the process of generating and confirming hypotheses. The Center for Open Science provides useful resources on preregistration.
Upon completion of analysis, researchers are encouraged to publish their research output with open access. Information on how this can be done is available on VU Library website here. Questions on open access publishing can be directed here: firstname.lastname@example.org
Researchers at SBE are also encouraged to make use of ORCID iD persistent identifiers to link their afﬁliations, works, memberships and peer review activities. This will increase their impact and visibility.
Useful Documents and links:
VU Research Data Management Policy
SBE Research Data Management Policy
VU Library Research Data Management Libguides
NWO Data Management Paragraph Example (contact: email@example.com)
Additional Research Data Support at VU
In addition to the resources available at SBE, the VU RDM Support Desk at the library can be contacted for RDM-related advice and support. They can be reached via email(firstname.lastname@example.org) or by phone call 020 598 53 67 during regular working hours.
Please refer to the Research Data Support portal for a comprehensive overview of all RDM professionals, tools, policies, guidelines, trainings, workshops and best practices at SBE and the VU at large.