Analysing ORCID coverage across repositories through CORE

* This post was authored by Matteo Cancellieri, Petr Knoth and Nancy Pontika.

Last month, CORE attended the JISC ORCID hackday events in Birmingham and London. (ORCID is a non-profit organisation that aims to solve the author disambiguation problem by offering unique author identifiers). Following the discussions that sparked off at the two events, we decided to test the CORE data towards ORCID’s API and we discovered some information that we think is of interest to the scholarly community.

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CORE released a new Dataset

picture1We are pleased to announce that we have released a new version of our dataset, which contains data aggregated by CORE in a downloadable file.

It is intended for (possibly computationally intensive) data analysis. Here you can read the dataset description and the download page. If you need fresh data, and your requirements are not computationally intensive, you can also use our API.

CORE Recommender

* This post was authored by Nancy Pontika, Lucas Anastasiou and Petr Knoth.

The CORE team is thrilled to announce the release of a new version of our recommender; a plugin that can be installed in repositories and journal systems to suggest similar articles. This is a great opportunity to improve the functionality of repositories by unleashing the power of recommendation over a huge collection of open-access documents, currently 37 million metadata records and more than 4 million full-text, available in CORE.

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