Sharing data means you make your research data available to others, which can be done during and/or after your research. Journals or funders may require you to provide (open) access to your research data or at least share your data with other researchers upon request. In this way, they are stimulating the public availability of data and scripts. You can share your data by depositing it in a trusted online repository openly available or available upon request.
If you share your data openly and especially if you publish Open Access, there is a large likelihood that you will reach a broader audience (e.g. not only your fellow scientist but also practitioners, policymakers, journalists and the general public) and more people will cite your work. They are better able to validate your findings and more people can read your work. As such, you will have a larger audience and an audience with more confidence in your study. The subset of your audience that will eventually cite your work is also likely to be bigger.
Data archiving concerns data storage after a research project ends. Data archiving aims in the first place at preventing physical data loss or destruction and securing the authenticity of data. Besides, it contributes to the quality and impact of your scientific work by enabling verification and possible reuse. For instance by allowing further analysis or follow-up research, or as a contribution to a data resource for the scientific community.
For sharing your research data during research, several options are recommended:
See also UT Research Support on sharing and sending data (as well as storage). Furthermore, use this tool to find the best solution for storing, sharing, transferring or collaborating on research data, during the research.
At the UT:
- Group/share UT Network storage (P-drive)
- custom filesystem (network-share) on the UT central hard disks
- Lightweight database (no costs for < 5 GB data storage)
External (in the cloud):
- SURFdrive (secure file storage and/or share these with colleagues/students)
- Dataverse (also Archiving possible)
- OneDrive (Microsoft) (offers a GDPR compliant solution for having multiple access to your data and sharing with others)
- SURFfilesender (safe sharing/sending (also encrypted possible) of data between student-supervisor or UT employee-external partner)
- Tech4people server at BMS Lab
More info on storing & sharing your research data
For archiving your research data we recommend using the UT DATA ARchive Areda:
The long-term archiving of research data can be done safe and secure by using the UT facility Areda. This facility is integrated with the already available datasets registration in the UT Research Information System (Pure).
Areda is the University of Twente archive for the long-term storage of static data collected, generated or used in UT research projects. But archiving is more than just storing data. Metadata must be added, so datasets can be findable, whereas proper documentation is needed for interpretation and verification, as well as interoperability and reuse of the data. Therefore Areda is linked to the UT research information system (Pure), for adding metadata, while documentation can be included in a README file.
All files are durably stored on ISO 27001 and NEN 7510 certified servers at the University of Twente. The back-up facility is hosted by Surf, which data centers are located in Utrecht and Amsterdam, The Netherlands. Default, preservation and availability is for a period of 10 years. In the near future, other preservation periods are possible.
Areda offers research groups their own ‘bucket’ where (zipped) files can be uploaded and shared among the group members in accordance with the group’s data policy and guidelines. Therefore, the research group always remains access to the research data that its researchers produce. For more information about Areda and how to use Areda, please check the UT webpage on Areda.
Read the UT guidance on preserving & archiving research data, and the Guidelines for the archiving of academic research for faculties of behavioural and social sciences in the Netherlands.
For publishing your research data we recommend using a trusted repository:
To make your data and research more visible to the scientific community, in addition to archiving your data in Areda, you can also use trusted repositories to publish your data. By publishing/depositing your data set to a trusted repository, your data set gets a persistent digital identifier (e.g. DOI) which allows your data to be widely findable, accessible, and easily cited by others.
DANS, for social sciences and humanities 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). DANS has the Data Seal of Approval. A demo recording on how to upload a dataset to DANS is available on the UT DCC website.
Open Science Framework (OSF) is becoming more familiar in the social sciences. OSF is a free, open-source Web tool designed to help researchers collaboratively manage, store, and share their research process and files related to their research. Unlike the other repositories (such as DANS or Dataverse), which were built to simply house and share files once a research project is finished, OSF also allows researchers to store and interact with files during the research process and to preregister their work and upload preprints if they so desire. They have Guides and FAQ available. NOTE: by default OSF stores your data in the United States, choose Germany - Frankfurt as storage location instead, as US is not GDPR compliant.
We advise you to think about what data to share, with whom, how, when and for how long at the start of your research project and to capture these preferences in a Data Management Plan (DMP).
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, for PhD candidates, registration for the course (online course + interactive session) is needed; for other UT staff, the online part of this course is available without registration.