This looks great: I like the search timeline, the ability to easily search for free full-text meta-analyses (a selection bias we should all be aware of), the MeSH term listing in a reasonably-sized font, and that there's schema.org/ImageObject metadata within the page, but there's no [Medical]ScholarlyArticle metadata?

I've worked with Google Scholar (:o) [1], Semantic Scholar (Allen Institute for AI) [2], Meta (Chan Zuckerberg Institute) [3], Zotero, Mendeley and a number of other tools for indexing and extracting metadata and graph relations from https://schema.org/ScholarlyArticle and MedicalScholarlyArticles . Without RDFa (or Microdata, or JSON-LD) in PDF, there's a lot of parsing that has to go down in order to get a graph from the citations in the article. Each service adds value to this graph of resources. Pushing forward on publishing linked research that's reproducible (#LinkedResearch, #LinkedReproducibility) is a worthwhile investment in meta-research that we have barely yet addressed:

> http://Schema.org/NewsArticle .citation: https://schema.org/citation ... Wouldn't it be great if NewsArticles linked to the ScholarlyArticle and/or Notebook CreativeWorks that they're .about (with reified relations)?

> A practical use case: Alice wants to publish a ScholarlyArticle [1] (in HTML with structured data, as a PDF) predicated upon Datasets [2] (as CSV, CSVW JSONLD, XLSX (DataDownload)) with static HTML (and no special HTTP headers). 1 https://schema.org/ScholarlyArticle 2 https://schema.org/Dataset*

> B wants to build a meta analysis: to collect a # of ScholarlyArticles and Dataset DataDownloads; review study controls and data; merge, join, & concatenate Datasets if appropriate, and inductively or deductively infer a conclusion and suggestions for further studies of variance*

The Linked Open Data Cloud shows the edges, the relations, the structured data links between very many (life sciences) datasets: https://lod-cloud.net/ . https://5stardata.info/en/ lists TimBL's suggested 5-start deployment schema for Open Data; which culuminates in publishing linked open data in non-proprietary formats that uses URIs to describe and link to things.

Could any of these [1][2][3][4][5] services cross-link the described resources, given a common URI identifier such as https://schema.org/identifier and/or https://schema.org/url ? ORCID is a service for generating stable identifiers for researchers and publishers who have names in common but different emails. W3C DID solves for this need in a different way.

When I check an article result page with the OpenLink OSDS extension (or any of a number of other tools for extracting structured data from HTML pages (and documents!) https://github.com/CodeForAntarctica/codeforantarctica.githu... ), there could be quite a bit more data there for search engines, browser extensions, and meta-research tools.

Is this something like ElasticSearch on the backend? It is possible to store JSON-LD documents in the search index. I threw together elasticsearchjsonld to "Generate JSON-LD @contexts from ElasticSearch JSON Mappings" for the OpenFDA FAERS data a few year ago. That's not GraphQL or SPARQL, but it's something and it's Linked Data.

re: "Canada's Decision To Make Public More Clinical Trial Data Puts Pressure On FDA" https://news.ycombinator.com/item?id=21232183

> We really could get more out of this data through international collaboration and through linked data (e.g. URIs for columns). See: "Open, and Linked, FDA data" https://github.com/FDA/openfda/issues/5#issuecomment-5392966... and "ENH: Adverse Event Count / 'Use' Count Heatmap" https://github.com/FDA/openfda/issues/49 . With sales/usage counts, we'd have a denominator with which we could calculate relative hazard.

W3C Web Annotations handle threaded comments and highlights; reviewing the reviewers is left as an exercise for the reader.
Does Zotero still make it easy to save the bibliographic metadata for one or more ScholarlyArticles from PubMed to a collection in the cloud (and add metadata/annotations)?

Sorry to toot my own horn here.
Great job on this. This opens up many new opportunities for research.

[1] https://scholar.google.com

[2] https://www.semanticscholar.org/

[3] https://www.meta.org/

[4] https://zotero.org/

[5] https://mendeley.org/