Messaggi di Rogue Scholar

language
Pubblicato in iPhylo

Returning to the subject of personal knowledge graphs Kyle Scheer has an interesting repository of Markdown files that describe academic disciplines at https://github.com/kyletscheer/academic-disciplines (see his blog post for more background). If you add these files to Obsidian you get a nice visualisation of a taxonomy of academic disciplines.

Pubblicato in iPhylo

I stumbled across this tweet yesterday (no doubt when I should have been doing other things), and disappeared down a rabbit hole. Emerging, I think the trip was worth it.   Markdown wikis Among the tools listed by @zackfan01 were Obsidian and Roam, neither of which I heard of before.

Pubblicato in rOpenSci - open tools for open science

Whilst working on the blog guide, Stefanie Butland and I consolidated knowledge we had already gained, but it was also the opportunity to up our Rmd/Hugo technical game.Our website uses Hugo but not blogdown 1 to render posts: every post is based on an .md file that is either written directly or knit from an .Rmd file.We wanted to provide clear guidance for both options, and to stick to the well-documented Hugo way of e.g. inserting

Pubblicato in rOpenSci - open tools for open science
Autori Maëlle Salmon, Scott Chamberlain, Stefanie Butland

Last year we reported on the joy of using commonmark and xml2 to parseMarkdown content, like the source of this website built withHugo, in particular to extractlinks,at the time merely to count them. How about we go a bit further and usethe same approach to find links to be fixed? In this tech note we shallreport our experience using R to find broken/suboptimal links and fixthem. What is a bad URL?

Pubblicato in rOpenSci - open tools for open science

A while ago weonboarded anexciting package, codemetarby Carl Boettiger. codemetar is an R specificinformation collector and parser for the CodeMetaproject. In particular, codemetar candigest metadata about an R package in order to fill the termsrecognized by CodeMeta. This meansextracting information from DESCRIPTION but also from e.g. continuousintegration 1 badges in the README!

Pubblicato in rOpenSci - open tools for open science

You might have read my blog post analyzing the social weather ofrOpenScionboarding,based on a text analysis of GitHub issues. I extracted text out ofMarkdown-formatted threads with regular expressions. I basicallyhammered away at the issues using tools I was familiar with until itworked! Now I know there’s a much better and cleaner way, that I’llpresent in this note. Read on if you want to extract insights abouttext, code, links, etc.