- Preserving and publishing data (FAIR)Making data FAIR The UT supports the FAIR principles. In practice, at the latest when a dataset is static (no longer changing), it should be Findable, Accessible, Interoperable and Reusable (FAIR)—for datasets you preserve (archive) at the UT and for datasets you publish in a trusted repository. What are FAIR principles? FAIR principles are widely adopted guidelines to make data discoverable and reusable by humans and machines: Findable, Accessible, Interoperable, Reusable, as first formally published by Wilkinson et al. (2016). Applying FAIR makes your datasets findable, accessible under clear conditions, interoperable and reusable, which increases visibility and citations, improves transparency and reproducibility, and reduces duplication and costs. It also keeps you aligned with community standards and fulfils funder requirements while respecting proportionate openness—as open as possible, as closed as necessary. FAIR in practice FAIR ≠ open: if data can’t be open, publish the metadata and set appropriate access
- Research Data ManagementThe value of RDM Good research data management (RDM) at UT helps ensure integrity, reproducibility, and FAIR sharing. See how UT researchers apply RDM in practice in our Best practices & interviews (DCC). Why RDM is important 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. Effective planning Find out how to write a data management plan. 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
- Research software managementUT’s Research Software Policy is designed to ensure the recognition of all research output and to encourage open access across the board, in line 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