On 28th November OxTalks will move to the new Halo platform and will become 'Oxford Events' (full details are available on the Staff Gateway).
There will be an OxTalks freeze beginning on Friday 14th November. This means you will need to publish any of your known events to OxTalks by then as there will be no facility to publish or edit events in that fortnight. During the freeze, all events will be migrated to the new Oxford Events site. It will still be possible to view events on OxTalks during this time.
If you have any questions, please contact halo@digital.ox.ac.uk
The FAIR Principles (doi.org/10.1038/sdata.2016.18) have propelled the global debate in all disciplines about better Research Data Management (RDM), transparent and reproducible data worldwide, and in all disciplines. FAIR has de facto become a global norm for good RDM, a prerequisite for data science, since their endorsement by global and intergovernmental leaders. Funding bodies are consolidating FAIR into their funding agreements; publishers have united behind FAIR as a way to remain at the forefront of open research; and in the private sector FAIR is adopted and enshrined in policy in major biopharmas, libraries, and unions. FAIR is changing the culture of data science, but work is needed to turn the principles into reality. As an author of the FAIR Principles, and lead of an Oxford R&D group that works on improving data reuse and publication (datareadiness.eng.ox.ac.uk), I will use the work of several FAIR-enabling projects and activities we are part of, including Oxford-led FAIR Cookbook (fairplus.github.io/the-fair-cookbook/content/home.html) and FAIRsharing (fairsharing.org), as exemplars to illustrate challenges and progresses.
