Skills development for Open Science Sharing (open)

Transcript:Skills development for Open Science Sharing (open):
Skills development for Open Science Sharing (open) Data Open Science webinars Open Access week Veerle Van den Eynden 20 October 2020 Skills for data sharing Skills for researchers Skills for research support staff Data sharing / open data only makes sense if data are fit for reuse (examples) FAIR data a better standard than open data Example Only research paper explains what data mean, their provenance. ٧ Open ٧ Evidence X Reuse 6-page data descriptor; machine-readable metadata; usage info, ... ٧ Open ٧ Reuse Skills to share FAIR data Documentation and annotation: explain what data mean Metadata creation (and taxonomies and ontologies) Pseudonymisation / anonymisation Open / standard file formats Legal: data protection, IP, copyright Licensing of data Responsible reuse: Citation and attribution Handling sensitive data Proper data mining Repositories and how to use them Skills for researchers University students get a good grounding in research methods Studies rarely cover the lifecycle of data and the practicalities of making data shareable for the longer term So researchers focus on the immediate activities needed to collect data, interpret and report on them How to teach skills? Effective learning of data skills: active learning by making processes visible directly experiencing methods critical reflection on practice Hands-on Practical examples Templates Tools Examples Active learning: practical tasks, (lab) exercises, quizzes Learning by doing / experiencing: write a data management plan create a metadata record Critical reflection: group discussions of real-case data challenges discussions on individual data needs to explore shared challenges Online self-learning courses For research support staff Learn about those same topics Understand the research practices Try out the various courses To providing training to researchers, reuse existing training courses / materials, e.g.: CESSDA training package (with exercises) Open Science Training Handbook (with exercises) Digital Open Science course for reuse: 60 hours with 15–20 hours of lectures and tutorials UKDS exercises SSHOC Training Toolkit Beyond skills For Open Science to progress, skills are important, but also: Attitudes to data sharing Open Science culture within organisations Support services and infrastructure Thank you !