Talk:Annotated Hub of Science

Prioritization

How do we name and talk about approaches to choosing priorities?

In a world with an infinite amount of potential observational data and metadata, some possibilities:

• Start with a core, iterate across what it cites. Add what cites it.
• Start with a catalog and work through it, gathering what's available, making multiple passes. Expand the catalog.
• Start with a group of authors or sources, work through each of them (federated of the above).

–SJ talk  18:54, 6 September 2019 (UTC)

Hm, isn't this what SemanticSholar tries to do?

Semantic Scholar helps researchers find better academic publications faster. Our engine analyzes publications and extracts important features using machine learning techniques. The resulting influential citations, images and key phrases allow our engine to “cut through the clutter” and give you results that are more relevant and impactful to your work.

https://www.semanticscholar.org/faq#advantages-of-semantic-scholar

I'm not sure how to assess their results in that regard. Arguably, https://gettheresearch.org/ is trying to do something similar.

All the methods assume the availability of the data on which to train models etc. Were you thinking of a way to prioritise data we don't have and need to look for? Say, gender of researchers on Wikidata (per some recent discussion) or subtler data about individuals, or publications from areas underrepresented in the usual databases? Nemo 21:38, 6 September 2019 (UTC)

@Nemo bis: let's revisit. –SJ talk  14:05, 30 April 2021 (UTC)