- Aims and servicesData preservation means archiving them in a sustainable way. Publishing research data you can see as sharing them on a structural basis with the public. Research data is often regarded as the crown jewels of science. It forms the basis of the results of scientific work. The quality of research results is also determined by the possibility of verification by means of the underlying datasets (see Netherlands Code of Conduct for Research Integrity, 3.2 art. 12a). Besides that, scientific development will benefit from sharing and reuse of research data. Good preservation forms the basis of verification, sharing and reuse of the research data. Aims Data preservation or 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 for further analysis or follow-up, new research or as a contribution to a data resource for the scientific
- Data policies and responsibilitiesResearch groups are responsible for the care of the data collected or generated in the research project, especially when it has a permanent character. This responsibility of proper data archiving extends beyond the end of the project and is, in the first place, the group’s own interest. Secondly, this responsibility is based on the general principle, formulated in the UT RDM policy, that intellectual property rights on research data collected or generated by UT staff (“database right”) are vested in UT. Student's research data The scope of UT RDM policy and the research group’s responsibility of data archiving does not include research data collected or generated by bachelor or master students. However, study programmes or research groups may have developed their own policies and guidelines and can make use of Areda for archiving these research data. Data selection In general, archiving of the right selection of data is the responsibility of the researcher, (former) project leader, the supervisor in case of research
- Making data FAIRThe UT supports the principles of FAIR data, which means research data, at the latest when they are static, should be Findable, Accessible, Interoperable and Reusable. Of course this holds for shared and published static data, but also for data which are only archived at the UT. What are FAIR principles? There has been a tremendous increase in the amount of scholar produced research data and hence, there is an emerging urge to benefit from the published research data at most in the digital era of science as stated by Wilkinson et al.. FAIR principles are guidelines for researchers to make their research data Findable, Accessible, Interoperable, and Reusable with an ultimate goal of making the data available for reusability both by humans and machines as initiated by Force 11. FINDABLE: The first step to make research data FAIR is to be able to find the data and metadata, e.g. the (meta)data should be uniquely and persistently identifiable through persistent identifiers (PID) such as DOI. Moreover, it is of great
- Preserving data at the UT (Areda)Preserving, or archiving, data means that a copy, including description and documentation, is durably stored at the UT, preferably in the data archive Areda. Apart from merely storing data for the long term, also metadata can be added to make the data findable, as well as proper documentation for the sake of interpretation, verification, interoperability and reuse of the data. For adding metadata and documentation (README file), Areda is linked to the UT Research Information System (Pure). Important: Areda is currently only accessible with support of a data steward as part of an evaluation of the user experience. Based on input received from users, we are currently working to improve the system in a few key aspects. If you have any questions about this notice or Areda, please contact your faculty’s data steward. What is Areda Areda is the University of Twente archive for the long-term storage of static data, which is collected, generated or used in UT research projects. Areda offers research groups: Certified
- Publishing data in a repositoryIf possible, make research data open by publishing it in a trusted data repository, such as 4TU.ResearchData or DANS. This is highly recommended, both from an individual and public interest. Sustainable access and reuse One of the services of a trusted repository is the issuing of a persistent identifier, which guarantees sustainable access. Watch this video about Persistent identifiers and data citation explained (Research Data Netherlands). When publishing in a data repository, for proper reuse it is important to add metadata and a README file with documentation (guidance / template). You can use the same you added in Areda. In the near future automatic linking from Areda/Pure to 4TU.ResearchData and DANS will be realized. Before publishing, please check specific project or research group policies. Enhancing your publication Once you have published the research data, you can enhance your publication(s) based on the dataset. You need to let the dataset refer to your article(s), and vice versa. Both 4TU.ResearchData
- Questions and answersCheck these practical questions and answers about archiving research data at the UT. For other questions you can contact the data steward in your faculty. Where can I archive and publish datasets? You can archive datasets in the UT facility Areda. Apart from that you can publish the dataset in a trusted repository, preferably 4TU.ResearchData or DANS. What kind of data materials can I archive? You can archive all types of datasets, both as supportive material to a publication (PhD-theses, journal articles, etc.) and as stand-alone items. Datasets may be accompanied by related materials, such as specific viewing and analysis tools (models, algorithms, scripts, analysis or simulation software, schemas) laboratory or field notebooks, diaries questionnaires, transcripts, codebooks standard operating procedures and protocols informed consent forms Can I archive datasets at any moment during my research? Yes, as long as archiving fulfils the following requirements: it is aimed at securing data authenticity, verification