The value of RDM
Watch a short video about good RDM practice and read why research data management is essential.
Research data management is in the first place about keeping your data safe and make them available to others.
Watch the video below about experiences with and advantages of sharing research data. It is an interview with Arnd Hartmanns, assistant professor in the Formal Methods and Tools group at EEMCS faculty.
Good research data management is important because it promotes:
Access, re-use, impact and recognition
- Facilitating future research by allowing others to build on or add to your research data;
- Increased citations of research data and of publications based on that data.
Efficiency
- Increasing your research efficiency by saving time and resources;
- Preventing duplication of effort by enabling others to use your data.
Quality and security
- Ensuring the integrity and reproducibility of your research;
- Ensuring that research data and records are accurate, complete, authentic and reliable;
- Enhancing data security and minimizing the risk of data loss.
Compliance
- Meeting legal obligations, restrictions and codes of conduct;
- Meeting the University of Twente research data management policy requirements;
- Meeting funding body grant requirements.
Effective planning and budgeting
Find out how to write a data management plan and estimate RDM costs.
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.
Costs for data management made during a research project can be inserted into a proposal’s budget. These may be costs related to temporary storage, to the anonymization or the transcription of data, or to the curation of data before sustainable archiving.
In case of archiving your research data in 4TU.ResearchData the costs for depositing up to 1 TB/yr will be reimbursed by the UT. At Dans depositing is free of charge for individual researchers with datasets under 50 GB. The rate for depositing larger files is determined by a number of factors. More information.
Use this guide for estimating research data management costs. For costs of UT RDM services see this overview.
Data policies and requirements
Find out what data policies and guidelines there are at the UT and in the faculties and what research funders demand.
The University of Twente has a policy on research data management (RDM). This is an overall data policy on how to handle research data. It serves as a framework for data policies in the faculties, institutes, departments and research groups. Data policies give regulations and guidelines regarding data management plans as well as the storage, security, documentation, sharing and archiving of research data.
When setting up your research you should check all RDM policies that are relevant to you. Below you find the data policy of the UT and part of the faculties.
Research funders NWO, ZonMw and the EU have a data management policy which affects grant submission. They all ask you to write a data management plan within a certain amount of months after the start of your project. NWO and the EU also want you to answer specific questions as part of the submission process (data management section) about the way you are going to manage the research data.
NWO
NWO implemented a data management policy in all funding instruments with effect from 1 October 2016.
Data management section
Calls for proposals will include a data management section in which the researcher should answer a number of short questions.Data management plan
No later than 4 months after the project has been awarded, the researcher must submit a data management plan. You can use the template in the UT DMP-tool (also linked to the UT RDM course) which is approved by NWO.FAIR data
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
Planning research data management
When writing your grant proposal it is highly recommend to already think about data management during and after your research.Data management plan
After a research proposal is granted, the grant recipient must draw up a data management plan. You can use the template in the UT DMP-tool (also linked to the UT RDM course) which is approved by ZonMw.Data ownership and availability
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.FAIR data
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
The EU has programmes for research and innovation projects. Horizon 2020 will end in December 2020, but there are still several calls open. A new programme, Horizon Europe has been developed for 2021-2027. More information is offered by the UT Grants Office.
RDM and FAIR data are an essential part in both EU funding programmes. There are guidelines available.
Horizon 2020 (2014-2020)
Information and requirements regarding RDM and FAIR data can be found in the EU Horizon 2020 guidelines. In section 3 of this guideline you can read what RDM issues you should address in your application.Look here for general information on data management in this programme.
When a project has been granted a data management plan (DMP) must be handed in before the start of the project. The template in the UT DMP-tool (also linked to the UT RDM course) is accepted. More information can be found on the H2020 general information page.
ERC (European Research Council) grantees of projects that take part in the Horizon 2020 Open Research Data pilot are required to submit a DMP within six months after the start of the project. There is specific information on Open Research Data and Data Management Plans.
Horizon Europe (2021-2027)
General information and requirements regarding research data management can be found in the programme guide, Open science section. If you expect to generate or reuse data and/or other research outputs (except for publications), you are required to outline in a maximum of one page how these will be managed. Research data management should be in line with the FAIR principles.When using the Horizon Europe Programme Standard Application Form, you can use this guidance for Part B -section 1.2. Methodology, final bullets “Open Science” and “Research data management and management of other research outputs".
ERC (European Research Council) grantees who generate research data have to submit a DMP at the latest six months after the start of the project. There is specific information on Open Research Data and Data Management Plans (DMP).
When a project has been granted a DMP must be handed in before the start of the project. The template in the UT DMP-tool (also linked to the UT RDM course) is accepted.
More information can be found in the Horizon Europe programme guide, especially in the section about Open Science.
Handling data during your research
Find out how to store and share data safe and securely and how to handle personal data.
Storing and sharing of data refers to the dynamic phase of the project. As soon as your research data sets are stable and static you should archive the data for long-term preservation.
All collected research data, including related materials such as protocols, models or questionnaires, must be stored in facilities offered by the UT (LISA), which are ISO 27001- and NEN 7510-certified. See UT research data management 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).
The decision tree "How to handle with research data" is a tool to find the best solution for storing, sharing, transferring or collaborating on research data, during the research.
Especially when research data are to be considered as confidential, for instance in case of personal or sensitive information, data security is needed.
You can find more information about security measures in research on the UT cyber safety webpage.
Data breach
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.
Training and support
Find here selected courses for researchers or support staff and visuals of the UT RDM support organisation.
There are several courses available on general research data management, both at the UT and nationally.
RDM online course
Are you looking for a good start into research data management (RDM)? Enroll yourself in the RDM course that is available for UT staff via Canvas! The course can be used as the lead while writing your own data management plan. It serves every aspect of good RDM and will guide you through all the steps you have to take in the process of RDM.
Are you a PhD student who is obligated to follow this course as part of the TGS bootcamp? Please register for this course here.
Other UT staff can enroll directly via this link.
Course Handling Personal Data in Research
Are you going to collect and process personal data in your research? The course Handling Personal Data in Research (HPDR) will help you understand the range of perspectives needed to build and demonstrate compliance with privacy regulation in research.
UT staff can enroll directly via this link.
For more information about this course you can contact the UT Data Protection Officer.
MOOC on RDM from TUdelft
As a start of their career as data steward at the UT, Simone Fricke (ET and S&T), Judith (Techmed Centre) and Qian (BMS and ITC) followed the MOOC on Open Science: sharing your research with the world. They found it a very helpful and interesting way to get acquainted with the topics of sharing data and RDM. This course is open and available for everyone.
DANS Data game
Do you want to learn more about research data management (RDM) in an easy-and-fun way? And are you looking for online activities to connect with your colleagues or friends during this isolated situation? If your answer is YES, come to play this online data game developed by DANS (Data Archive and Networked Services)! The game is played as Go Fish or kwartet (in Dutch) so the rules are easy to understand. Visit this page to learn more and for the link to the online game and challenge your peers!
Data Horror Escape room
Are you a group of researchers looking for a fun and digital way to learn more about research data management? The VU Amsterdam, Leiden University, and the Eindhoven University of Technology created an online data horror escape room. The room consists of six tasks related to the following data management topics: FAIR data, personal data, data archiving, data transfer, persistent identifiers, and metadata.
Essentials 4 Data Support
Essentials 4 Data Support is an introductory course for those people who (want to) support researchers in storing, managing, archiving and sharing their research data.
More courses
Other courses and trainings you can find on the website of LCRDM.
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.
If you want a broader picture of RDM support, check the visuals below giving you an overview of the research data management support organization at the UT. Feel free to use the materials offered here, they are all licensed under a CC-BY-NC-SA license, unless stated otherwise.