Research Data Management

Good RDM promotes:

• Access, reuse & impact
  Enable others to build on your data, increase citations, and enhance the visibility of your research.
• Efficiency
  Save time and resources by organizing your data and preventing duplication of effort.
• Quality & security
  Ensure that your research results are accurate, reproducible, and less prone to loss.
• Compliance
  Meet legal, ethical, and contractual obligations, as well as UT’s RDM Policy and funder requirements.

Having a data management plan (DMP) is essential for your research project. A good DMP lets you work more efficiently and improves the integrity and impact of your research.

A data management plan describes:

• what data you will collect and how, as well as which software will be used for collecting, processing and analysis;
• how you will save and share the data during the research project;
• how you will make the data sustainably available and, if possible, publish them afterwards (watch this video about sharing data);
• how the data will be documented;
• how data will be shared and transferred securely;
• what legal issues are relevant, such as copyright, the right to reuse the data and the treatment of sensitive data.

The information you provide in the DMP has to comply with the UT research data management policy and, if available, the data policy of your faculty and research group, as well as legal, contractual and funder requirements. 

To write your DMP, please use the UT DMP-tool. The template in this tool is also accepted by NWO, ZonMw and EU.

As a guidance when writing a DMP you can follow the research data management course.

The UT Research Data Management (RDM) Policy is the overarching framework for handling research data at UT. Faculties (and, where relevant, institutes/departments/groups) implement this framework in their own policies. If there’s any inconsistency, the UT RDM Policy prevails. Below you find the research data policy of the UT and part of the faculties.

• UT RDM policy
• BMS Data policy
• EEMCS RDM Checklist 
• ET RDM policy
• ITC Data policy
• S&T RDM Guideline

Most funders expect you to include a short data section in the application, submit a Data Management Plan (DMP) after award, follow FAIR (“as open as possible, as closed as necessary”), and deposit suitable outputs in a trusted repository. The UT DMP-tool (also linked to the UT RDM course) template is accepted by NWO/ZonMw and may be used for EU projects as well.

NWO

• NWO has an RDM policy across all funding instruments (in place since 1 Oct 2016).
• In the application, complete the short data management section.
• After award: submit your DMP within 4 months. You can use the UT DMP-tool (institutional templates are accepted).
• The NWO data policy aims at stimulating researchers to work according to the so-called FAIR data principles, which means that data must be findable, accessible, interoperable and reusable.
• More information can be found on the NWO data management page.

ZonMw

• When writing your grant proposal it is highly recommend to already think about data management during and after your research.
• After a research proposal is granted, the grant recipient must draw up a data management plan. You can use UT DMP-tool template which is recognized by ZonMw.
• ZonMw and the grant recipient will share ownership of the produced data sets. The data must be available for the benefit of further scientific and/or academic research.
• The ZonMw data policy aims at stimulating researchers to work according to the so-called FAIR data principles, which means that data must be findable, accessible, interoperable and reusable.
• More information can be found on the ZonMw data management page.

EU

RDM and FAIR data are an essential part in both EU funding programmes. There are guidelines available. More information is offered by the UT Grants Office.

Horizon Europe/ERC

• General information and requirements regarding research data management can be found in the programme guide, Open science section.
• When filling the Horizon Europe Programme Standard Application Form, you can use this guidance document for Part B -section 1.2. Methodology.
• Horizon Europe (incl. ERC): submit the first Data Management Plan by month 6, then update it as the project evolves, and follow your specific call text and Grant Agreement. There is specific information on Open Research Data and Data Management Plans (DMP) and Horizon Europe programme guide.
• You can use the UT DMP-tool template which is accepted.
• More information can be found in the Horizon Europe programme guide, especially in the section about Open Science.

Storing and sharing of data refers to the dynamic phase of the project. Once a dataset becomes static (no more changing) you should prepare the data for long-term preservation.

All collected research data, including related materials such as protocols, models or questionnaires, must be stored in the UT (LISA) facilities that are ISO 27001- and NEN 7510-certified (see UT RDM Policy.)

Use the local drive of your laptop or computer only for work copies of your data files as data on these media may be lost in case of malfunctioning or because the device is lost or stolen. The local drive must, if possible, be encrypted to prevent data breach (see the special UT Data Breach webpage).

Not sure where to store, share or collaborate? Use the UT decision tree “Selecting the best UT facility to handle (research) data”.

If data are confidential (e.g., personal/sensitive), apply appropriate security measures. You can find more information about security measures in research on the UT cyber safety webpage.

Data breach

A personal data breach in research refers to the loss or theft of, or unauthorized access to personal or confidential data. More specifically it is linked to personal data breach in the framework of GDPR. In case of a personal data breach you must report this within 72 hours (see the special UT Data Breach webpage).

You should pay attention to preventing data breach, regardless the confidentiality of the data, as it may have a negative impact on the research itself, privacy and reputation of involved persons or organizations and the safety of individuals and society.

Encryption

When you use devices for work copies of data, it is wise to encrypt the device, folder or file with sensitive data to prevent data leaks occurring in the event of loss or theft. When encrypting a single file, there is a high probability of errors or that an application leaves (parts of) the file unencrypted on your hard disk. The best way is to encrypt the entire hard disk or USB stick.

You can find more (practical) information on the Encryption-webpage.

When working with personal data (data on identified or identifiable natural living persons) you need to comply with the General Data Protection Regulation (GDPR), in Dutch: the Algemene Verordening Gegevensbescherming (AVG).

Find more about handling of personal data in research at the UT cyber safety webpage.

Pseudonymization and anonymization

When you are processing personal data in your research you need to pseudonymize them. As soon as the purpose of the collection of the data has been fulfilled, mostly by the end of the project, in most cases you must anonymize the data.

In short, pseudonymization is a method to substitute identifiable data with a reversible, consistent value. This value is usually kept in a key file, in which the pseudonymized data is linked to the personal data.

Be aware that the key file must be stored on a secure and persistent location, such as an encrypted storage device placed in a safe or on the Project and Organization drive of your research group with controlled access.

The purpose of pseudonymization is to protect the privacy of research participants from the onset, during the collection of data. For more information see this report from the National Coordination Point Research Data Management (LCRDM).

Anonymization is the destruction of the identifiable data or the removal of private or confidential information from raw data. You can find a list of anonymization tools here.

Research Data Management (RDM) Bootcamp

• Mandatory for PhD candidates (UT RDM Policy):  Please enroll through Course finder CTD: UT courses for employees | University of Twente.
• Other UT staff: Enroll in the RDM online course via Canvas.

Course Handling Personal Data in Research

Handling Personal Data in Research (HPDR): Learn compliance with privacy regulations and enroll Enroll in Handling personal data in research. Contact the UT Data Protection Officer for questions and further details Contact | Cyber Safety.

RDM micro-lectures

Micro-lectures are short, animated videos that introduce essential RDM concepts in an accessible way. They are especially useful for Bachelor’s and Master’s students, early-career researchers, or anyone wanting a quick refresher. RDM micro-lectures for students | Research Data Management | BMS - BMS Datalab

• RDM - 1 - How do I get your data (yuja.com)
• RDM - 2- How do I use your data (yuja.com)
• RDM - 3 - How do I trust your data (yuja.com)
• RDM - 4 - How do I build on your data (yuja.com)
• RDM - 5 - What am I allowed to do with your data (yuja.com)

More courses and trainings

Looking for more? You’ll find extra courses, quick guides, and interactive resources below.

• Essentials 4 Data Support (RDNL)
• TU Delft MOOC “Open Science: sharing your research with the world”
• LCRDM / Taxila curated materials
• DANS Data Game
• Data Horror escape room (VU/Leiden/TU/e)

Data stewards in the faculties can help you with research data management issues, like writing your data management plan, advise you about storing, sharing and securing your research data and help you with publishing, archiving and registering research data.