FAIR stats F-uji checker results and aggregation of the NFDI4bioimage consortia

This dataset is an exemplary application of the fair stats aggregator code from github. it collects all fair statistics from the partner institutes of NFDI4bioimage (top 10,000 most cited publications) and aggregates the results. The aim is to find systematic or major errors in the metadata and to be able to optimise them.

Cited from github: 

This repository hosts a prototype tool designed to analyze and aggregate FAIR (Findable, Accessible, Interoperable, and Reusable) statistics for a list of Digital Object Identifiers (DOIs). The tool currently utilizes the F-UJI FAIR checker to evaluate the FAIRness of the metadata associated with each DOI. 

The tool processes a list of DOIs, which can be sourced from a website or fetched using a metasearch API like Crossref or DataCite (an example implementation is provided that generates the list of doi's for an institute via openalex query). It calculates FAIR statistics for each DOI, aggregates these statistics by publication year, and identifies common metadata errors that impact FAIRness. The results are presented in an aggregated FAIR-statistic per publication year diagram and a summary of the most frequent metadata issues.

This tool also serves as a justification for metadata providers (e.g., Springer, Nature) to ensure their metadata is hosted in a machine-readable format, as this is crucial for optimal FAIRness evaluation.