I've turned one of my teaching modules in #Paleontology into an #OER. It's only one single lab, but many more are waiting to be OER-ised... therefore I really need your input to avoid future mistakes.
github.com/EmiliaJarochowska/Y…

Thanks to the feedback (shoutout to @leouieda and @JMMaok) I knew this:
✅ Must be editable
✅ Must include rubric
✅ Must include an example: I included a possible solution but without an essay, just the code. Now in #Rlanguage but #Python and #JuliaLang will follow.

The most watershed decision was to use #Quarto for everything to make it editable and renderable using Open Source tools and to make it version control-compatible. For people not familiar with #Quarto this may be a barrier?
Not sure what a good alternative would be. #OpenPedagogy

GitHub - EmiliaJarochowska/Yankovich_cave: Reconstruction of Pleistocene climate based on assemblages of mammal microfossils from a cave in Hungary

Reconstruction of Pleistocene climate based on assemblages of mammal microfossils from a cave in Hungary - GitHub - EmiliaJarochowska/Yankovich_cave: Reconstruction of Pleistocene climate based on ...

^GitHub

I'm very happy to announce that we now have an opening for a Research Software Engineer (RSE) at the Royal Military Academy in #Brussels

We are looking to hire someone with a #PhD for this position, #julialang experience is a big plus.

Details at: rma.ac.be/en/research-software…

I am in the process of benchmarking our NCBI Taxonomy package in #JuliaLang (github.com/PoisotLab/NCBITaxon…), and so it's a good time to tell everyone that I dislike benchmarks.

Not because we don't compare well (our worst speedup so far is 5x, our best is of the order of 10⁵x).

But because benchmarks assume that we all want the same thing, and this thing is speed. This is not true.

GitHub - PoisotLab/NCBITaxonomy.jl: Wrapper around the NCBI taxonomy files

Wrapper around the NCBI taxonomy files. Contribute to PoisotLab/NCBITaxonomy.jl development by creating an account on GitHub.

^GitHub

Introducing Tidier.jl for #JuliaLang:

A 100% Julia implementation of the #rstats {tidyverse}. Powered by the DataFrames.jl package and Julia’s meta-programming capabilities.

github.com/kdpsingh/Tidier.jl

Still a work in progress.

Tidier.jl currently supports many of the core tidyverse functions. Because the package implements a non-standard domain-specific language (i.e., tidyverse) within Julia, it requires macros instead of plain functions, which is why all of the functions start with a "@".