Before we go into the learning bit, let’s just revisit what a version of record is. Wikipedia describes it as “the fully copyedited, typeset and formatted copy of a manuscript as published” (with two references). Basically, in the whole scheme of research output, it is a release . Is is a tagged version of the output, allowing people to discuss that version specifically, so that we do not run into endless “oh, but I meant

Jerven Bolleman et al. recently published a great preprint about how to use RDF to give SPARQL queries context by linking it (semantically) with metadata. The context includes keywords, the SPARQL endpoint the query can be run against, and a human-oriented description of the query.

The x-odus continues and there is a wave of researchers moving from X to another walled-garden called Bluesky. This is good and bad. First, it is good that people are leaving X (imho) and it is good that they move to a platform that supports open standards, the AT Protocol. But I am less sure, about moving to another closed source platform. I prefer Mastodon.

Open Science doesn’t make publishing easier. That that’s all for the better: our research efforts are complex, so why should the publishing be. Sure, I am not talking about references formatting or moving the Methods section to the right location, or some silly statement that all authors agree with the manuscript when you are the only author. No, let’s talk about data. What should you publish? How, and when?

I have not posted a lot about our Virtual Human Platform for Safety Assessment (VHP4Safety) project yet. Actually, more generally I do not post frequently about the funded projects. This is likely that few of them are Open Science by contract and often they have some formal process in place to approve output. That makes open notebook science-style posting about these projects hard. One is restricted to previously cleared material.

It was on my radar for some time already, but did not get around to finishing it. But I completed all five modules of the NASA Transform to Open Science (TOPS) Open Science 101 (doi:10.5281/zenodo.10161527). This Open Science 101 consists of several modules, starting with The Ethos of Open Science , via Open Tools and Resources , Open Data , and Open Code , to Open Results . Now, since I have been

Division 1 of our Institute of Nutrition and Translational Research in Metabolism (NUTRIM) held a meeting last week which had a panel discussion on the use of patents to bring research to the market, aimed at PhD candidates of the institute. Patents are one of the routes to make research output more sustainable. For example, the research output into a new method to study something or make something often needs the development into a product.

If you read my blog, it should not surprise you that I have long experimented with technologies to improve knowledge dissemination, for example in HTML. And I have blogged about publishing from an author and researcher, and editor perspective, for many years (see this longer list on my old blog). Also, in the Journal of Cheminformatics we pushed for innovation, including ORCID and GitHub adoption and Citation Typing Ontology adoption.

Scholarly articles provide context to the factualness of statements in Wikidata, similar to the [citation needed] in Wikipedia. And just like the cited references in each scholarly article itself. The citation network is general seen as an essential part of (doing) science, even without citation intention annotation.

Scholia is a visual layer on top of Wikidata providing a rich user experience for browing scholarly research related knowledge. I am using the combinatie for various things, including exploring new research topics (a method, compound, or protein I do not know so much about yet), indexing notable research output (including citations), progress of Citation Typing Ontology uptake, etc.