Just for fun I just "asked" the Wikidata, which software (or actually anything in its database) is implemented using rust. I did this using the SparQL endpoint. There are not many results, and I did not manage to remove doubles. Still, this may be usable to both track the spread of rust, and also may help rustaceans to improve wikipedia / wikidata.
What do you think? Would it be useful to track the spread like this? Any Ideas for other queries? Are "wikipedian rustaceans" present in here?
PS: I'm not a wikipedian but recently got an interest in SparQL and the semantic web. I recommend the "Learning SparQL" Book (Oreilly) in case you have also interest in this.
Good question. It would be helpful to have a wikipedian in place. I guess in the end it's all a matter of whether what is interesting data to the Wikidata project.
I know that much of the data was initially "scraped" out of Wikipedia entries (the info boxes in some articles) in the beginning of Wikidata.The idea of Wikidata is (among other things) that you are able to write wikipedia articles with facts that can get i.e. updated by wikidata, and automate Infobox generation.
Note that SparQL/RDF can easily combine data sources. Assume that crates.io would offer according RDF data in some format, and you can access both, it would make the same to the query-creator as if wikidata included this information. But I guess there is no priority for that.
Anyway, I found it interesting to see how often/seldom rust is mentioned in the EN-Wikipedia / Wikidata. And I thought I'd share this for inspiration purposes
I don't think a blanket import of packages into Wikidata is desired. They deliberately restrict their scope via the "Notability guideline" [1], to avoid becoming a dumping ground for unverified data that nobody cares enough to fact-check etc. (You could argue that the is already too loose, there are lots of poor quality articles on obscure topics, although a vast amount of it gets removed/cleaned up).
Generally "notability" means that the subject is covered by multiple sources, published in places that have editorial teams. Determining that as a human is difficult enough and I don't think it can reasonably be done in an automated fashion.
But if you're brave enough, you can pitch your idea to bot approvers [2] and they will consider it.