- About the value of RDMWatch a short video about good RDM practice and read why research data management is important. Good practice 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. Celebrating 4TU.ResearchData’s Role in Fostering Open Science Video recording of the event "Celebrating 4TU.ResearchData’s Role in Fostering Open Science" Why RDM is important 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
- Data policies and requirementsFind out what data policies and guidelines there are at the UT and in the faculties and what research funders demand. Data policies 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. RDM policy UT BMS Data policy S&T RDM Guideline ET RDM policy ITC Data policy EEMCS RDM Checklist NWO / Funder requirements 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
- Effective planning and budgetingFind out how to write a data management plan and estimate RDM costs. Writing your data management plan 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
- Handling data during your researchFind out how to store and share data safe and securely and how to handle personal data. Storing and sharing research 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
- Preserving and publishing data (FAIR)
- Aims and services
- Data policies and responsibilities
- Making data FAIR
- Preserving data at the UT (Areda)
- Publishing data in a repository
- Questions and answers
- Research software managementUT’s Research Software Policy is designed to ensure the recognition of all research output and encourage open access across the board with FAIR principles—making both data and software Findable, Accessible, Interoperable, and Reusable. Why research software management? Software is different from other published research output or research data in that it is dynamically executable and often has dependencies on other software or hardware. Therefore, it is crucial that software is developed with sustainability in mind, must be well documented and preferably published under an open-source license to ensure the ability to reproduce results and assess findings' reliability. When software projects depend on many libraries and programs which themselves depend on other code, the chance increases that somewhere in the chain something breaks. Code may be moved, updated (and no longer be compatible) or be removed all together. Because of new versions, security issues, platforms may cease to operate, operating systems may
- Training and supportFind here selected courses for researchers or support staff and visuals of the UT RDM support organization. Courses and training 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