Research data management

The University of Twente has an overall data policy on how to handle research data. This policy serves as a starting point for tailored data policies of faculties and/or institutes, and research groups.

Data policies explicitly state the responsibilities and authority within the group. They also state how group members should in principle collect, describe, save and share their data during and after their research.

• Data Policy UT
• Data Librarian | for guidance in setting up your research group's data policy
  

NWO (and STW)

NWO wants research data that emerges from publicly funded research to become findable, accessible, interoperable and reusable (FAIR) for the use by other researchers.

The basic principle is therefore open access to data and that access to data is only limited when necessary. To make data that emerges from NWO-funded research as accessible and reusable as possible, NWO has decided to implement the data management policy in all NWO funding instruments with effect from 1 October 2016.

The data management protocol consists of two steps: 

1. A data management section in the research proposal in which the researcher should answer a number of short questions.
   For support see: The NWO data management section
2. A data management plan that must be submitted after the proposal has been awarded funding. The approval of this plan is a prerequisite for NWO disbursing the grant.
   For support see section ‘writing a data management plan’

EU H2020

From January 2017 each researcher that applies for funding within the Horizon 2020 work program has to write a data management plan. Opting out is possible but has to be argued in the DMP. 

Researchers have to work according to the so-called FAIR data principles, which means that data must be: Findable, Accessible, Interoperable and Reusable.

See the guidelines for further information.

ZonMW

After a research proposal is granted, the researcher has to write a DMP. You can use a specific online DMP-tool. After completion of your research project the data should comply with the FAIR data principles. 

To know how to compose a DMP see instructions.

Having a Data Management Plan (DMP) is essential for your research project. A good DMP lets you work more efficiently, improves the integrity and impact of your research, and complies with legal, contractual and funder requirements.

Although a DMP is written before data collection starts, refining it is an ongoing process during the entire research cycle. A DMP describes what data you will collect and how, it describes how you will save and share them during the research project, and how you will make them sustainably available and publish them afterwards. It also describes your metadata: what will you describe and how? Your metadata describe data as well as processes, such as study protocols and software used for analysis. A DMP also addresses legal issues, such as copyright, the right to use the data and the treatment of sensitive data.

To write your own DMP, please use the University of Twente’s DMP template. When applicable, consult the DMP guidelines of your funder (for example, NWO, Horizon 2020, KNAW, ZonMw).

For a full understanding and guidance in setting up your DMP, sign up for our course on Research Data Management.

• DMP Template UT
• Course on Research Data Management | for a full understanding of research data management and guidance in setting up your data management plan

Video: The what, why and how of data management planning

During your research project, it is important to securely save your (meta)data files and to be able to share them with fellow researchers and stakeholders. Where you save your (meta)data and whom you share them with depends on many factors, such as your research group’s or institute’s data policy,

legal and contractual regulations, the nature of your data (standard, sensitive, or critical classification (in Dutch)), and access, sustainability and reliability issues.

As a University of Twente researcher, you have the following options for saving and sharing your dynamic research data:

^{1 For more information, please contact the information specialist of your faculty.}

• Data Classification UT (in Dutch)
• SURF Filesender
• SURFdrive
• DataverseNL

In the light of open science and scientific integrity, sustainably archiving your static data and providing access is crucial. Data repositories let you digitally archive your (meta)data to keep your research verifiable, replicable and reusable for the long term. We recommend using a Trusted Repository: 4TU.ResearchData for technical and natural sciences data, and DANS for social sciences and humanities data. These Trusted Repositories received the Data Seal of Approval, which guarantees reliable, citable data that can be found, accessed (clear rights and licences) and used in the long term, even if the hardware and software become obsolete.

4TU.ResearchData only accepts open data (everyone has unlimited access to your data). DANS prefers open data, but also offers restricted access (access is limited and can only be granted on request) and the possibility to place an embargo on your data (your data will become available after a set period of time, with a maximum of two years).

The University of Twente is in favour of sustainably available and accessible research data, and supports its researchers financially by offering an Open Science Fund.

• 4TU.ResearchData | for depositing technical and natural sciences data
• DANS | for depositing social sciences and humanities data
• Data Seal of Approval | seal for sustainable and trusted data repositories
• List of repositories with a Data Seal of Approval

Video: Durable and accessible data storage: Good for science, good for you (DANS/KNAW/NWO):

To publish your data, simply deposit them in a Trusted Repository (see above). When you upload your data to 4TU.ResearchData or DANS, a persistent identifier is assigned to your data, which guarantees sustainable access to your data.

Once you have published your data, you can enhance your publication(s). This process is two-fold: You need to let your dataset refer to your article(s), and vice versa.

Letting your dataset refer to your article

Both 4TU.ResearchData and DANS offer the possibility to include a reference to your published article(s). This reference will be part of the metadata describing your data. If permitted, DANS will archive your publication(s) along with the accompanying dataset.

Letting your article refer to your data

For upcoming articles, please make sure that your data reference is included in the reference list of your article. We also recommend mentioning this reference in your cover letter, so reviewers can verify your research. For published articles, please contact the publisher and request a link to your data to be displayed online, along with the description of your article.

 More and more researchers enhance their scientific publications by linking them to the underlying data. Research has shown that enhanced publications are cited more often than regular publications¹, so digitally archiving your data as citable output and enhancing your publication(s) increases your scientific impact.

^{1 Piwowar HA, Vision TJ. (2013) Data reuse and the open data citation advantage. PeerJ 1:e175 https://dx.doi.org/10.7717/peerj.175}

Persistent identifiers and data citation explained (Research Data Netherlands):