When last week in a large (and relevant) Dutch research event ChatGPT came up, and that this was going to change the world. Even the critiques came up, but were effectively disregarded with “these methods get better very quickly”. This is not untrue, but not really true either. I murmur “not even wrong”. I know how hard it is to get computers to find meaningful patters; I did a PhD in this in the early 21st century.

I think that if you want to make your knowledge FAIR, you should use an open license and RDF. Simple. Now, not everything is knowledge. A lot of data is, but a lot more is not, think raw data. Using RDF to explain a protein sequence is still something that makes me feel uneasy. However, first, you need to make RDF, you need to make assumptions explicit, you need to decide on meaning. Making RDF is not easy.

Okay, the Pilot is over ending with 17 papers, 16 of which have CiTO annotations (and so far 4 J.Cheminform. papers after the pilot), but my interest in the Citation Typing Ontology continues and we just need more adoption. Datasets as source of annotations So, here’s a quick Wikidata update.

Sometimes I think back about how Scholia started, and then I think I remember a Twitter discussion. Twitter was a social platform that was unable to fight hate speech. I left it last year in favor of Mastodon. Anyway, I did some digging today and found this thread from October 8-9 2016.

There are multiple initiatives to support the migration from Twitter to Mastodon (see also this blog post ). But Wikidata should not be forgotten here which has been tracking Mastodon accounts of things in their database: So, here are some Wikidata SPARQL queries to see the uptake: Universities with Mastodon All Mastodon accounts in Wikidata (or subset with also a Twitter account) Nobel Prize winners with Mastodon Academic journals

In August I reported about 2D depiction of (CX)SMILES in Wikidata via linkouts (going back to 2017). Based on a script by Magnus Manske, I wrote a Wikidata gadget that uses the same CDK Depict (VHP4Safety mirror) to depict the 2D structure in Wikidata itself: Note the depiction of the undefined (CIP) stereochemistry on two atoms. Thanks to Adriano and John for working that out.

Yeah, it has been hard to miss it (see e.g. Should I join Mastodon? A scientists’ guide to Twitter’s rival). Twitter is experiencing some turbulence and Mastodon has become a very attractive, open source, community-driven, inclusive alternative. It’s been around since 2016 and there is some research literature about it already. I got my account in 2018, but did not start actively using it until earlier this year.

Forget the journal impact factor and the H-index. You want your research being used. A first approximation of that is getting cited, sure. So, with the Nobel Prize week over (congrats to all winners! the Neanderthaler prize actually helped my work in Maastricht this week), let’s figure out of you are cited by a Nobel Prize winner.

In the end it was a very simple change today (huge thanks to Nikki!), but Wikidata now escapes SMILES and CXSMILES (P10718) with the formatter URL (P1630)! That means that the link to CDK Depict now also works for SMILES (P233 and P2017) with a triple bond in it :) And because Adriano created the so far missing formatter URL for CXSMILES, it also works for lipid classes (see my post yesterday), polymers, etc :) CXSMILES for a group of

Already 3 months ago I visited Dagstuhl for the second time. The weather was much better than in the January right before the start of the pandemic.

I am a bit behind with tweeting about new published papers, but let that not reflect that these papers are not very exciting. The first paper is by Marvin an almost-finished PhD candidate in our group and now working as postdoc on the VHP4Safety project. He has been working on linking adverse outcome pathways (AOPs) with molecular pathways, such as in WikiPathways.