slack comments to analyse

[jcolomb]

we will try to push here all interesting comments sent to slack

[jcolomb]

Hi all, I read the notes both on the CryptDrive and the GitHub. I saw one concrete outcome was the updating of the Module's rationale and learning outcomes. Now I guess you will start to develop the resources needed to cover each one of the three learning goals in your design. Just a comment: as progression of learning, I would invert the second learning goal with the third, for this last is more specific and practical in terms of skills relating to the (now) third. I would also remove the "researchers will be able of" and leave just 1) define the characteristics of open data...; 2) locate and re-use datasets ....3) share research data openly. I guess the first goal should be supported by contents such as policy context documents, videos explaining FAIR, reports on the current situation and practices; the second, annotated examples of practice; the third, RDM templates and guidelines to build own datasets. Please let me know if you need to build resources or check existing ones. ----------Another more broader comment: Open Data varies from discipline to discipline, so as the behaviour of researchers...Maybe a good approach could be to generate commented examples from broad categories like natural sciences, medicine, engineering and computer science, social sciences...making this categorisations is always difficult but maybe we can find a way to sample the different behaviours and approaches.
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[jcolomb]

Hi, as promissed after our meeting on Zoom and some ideas/resources I share the group. Julien told me that there will be two initial phases in the course:
1- Understanding the importance of re-using data in research. Activities could be: Searching for an interesting research in your own field and looking for the connected data. Discussing on the online forum? Wrap up by us as video or webinar?
2- Getting to know the advancement of the Open Data movement. Here we need to develop some learning resources, at least in the form of a list of links to relevant documents and learning resources. Just as example, I built this material for the PhD Students in my disciplinary field (educational technologies: https://docs.google.com/document/d/1hQ1oG-CFbsVCsJP55yg5s_JdQ641jSEcHHxITFZLG60/edit#heading=h.xl3v4yxbdtlr

So here is my proposal, of adding a third phase with practical activities leading to technical skills' achievement necessary to become active in the Open Data movement.

3- Critically using tools and environments to create your Open Data. Activities here could be:
3.1. An "Open Data Expedition" as a sort of User Experience on Open Data platforms. As an example, I created this resource for my learners, to guide them in the OD expedition. Normally, I comment with them their results: https://docs.google.com/forms/d/e/1FAIpQLSf3fbD8wj08UfAfu7bBgVvEcUKfd_tMIfRSCXN39OmZDuYZpw/viewform
3.2. Use the template to create a draft of your first Open Data. As an example, I created this resource: https://docs.google.com/document/d/1ytbh_ZkbRWr4B41XUYwBTaTScINNxNkpUKtPczvWwqY/edit

To all, maybe we could edit this on the GitHub and make something more appealing. Let's discuss...Sorry for the long post!
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[jcolomb]

notes as usual here: https://cryptpad.fr/code/#/2/code/edit/FSBaEuaf8ol1VhAc8B0x7Z63/
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