Open tobyhodges opened 1 year ago
You asked for issues to be labelled (this one needs the example data
label) but I do not have the power to add issue labels on this repo, sorry.
@tobyhodges
This looks great! But, given the data modality that we are focussing on, namely bioimaging data, we thought that the BioImage Archive might be more suitable, because, e.g., it knows about relevant metadata and might have preview capabilities a.s.o.
Would it work that we put the data into the BioImage Archive and the additionally put links to that data into Pointers?
That would be no problem, provided that the data has an associated Zenodo entry (so we can list it in the Pointers "community" on Zenodo). Domain-specific repositories are often the best place for such example data, and anyway we do not want to make Pointers mutually exclusive with anywhere else the data could/should be deposited.
Finding good example data for use in teaching is challenging for other data-intensive domains as well as (bio)image processing. The Carpentries and the Academic Data Science Alliance are collaborating to try to build a collection of openly-licensed data (CC0, ideally) that is suited to educational use. A lot of public repositories exist for data, but we were not able to find one focused on teaching e.g. for a dataset to be easily used for teaching, it helps for it to be well-documented/annotated and to fit into a "Goldilocks zone" of just-right complexity, size, noisiness, etc.
So we set up Pointers, a place for open peer review and hosting of openly-licensed datasets for teaching, which we hope will serve as a point of reference for people building teaching materials (lessons, curricula, tutorials, etc) to find and re-use good example datasets. So far, the collection contains only one entry (can it be a "collection" if it contains only one entry? 😆) so we would love to see more submissions.
Would you be willing and able to submit any of the example datasets you collect here to Pointers? If so, @vantuyls and I would love to help you in whatever way we can. The project website includes a submission guide that describes the process and the criteria on which datasets will be reviewed.