This seems to have gone under the radar: Accelerating Access to Research Results: New Implementation Date for the 2024 NIH Public Access Policy.

We’ve been accelerating our metadata development efforts and recently released version 5.4 of our metadata schema, and are planning to release version 5.5 (including support for multiple contributor roles and the CRediT taxonomy) this summer.

Following my recent talk for the Boston Library Consortium, many of you expressed a strong interest in learning how to test the new generation of AI-powered academic search tools.

2024 was a banner year for dataset resources in DataCite. The National Institute of Fusion Science registered over 10,000,000 datasets. These metadata are remarkably complete - a bright spot demonstrating great metadata at scale.

In this dual case study, we learn why the Howard Hughes Medical Institute (HHMI) relies on OA.Report and why OA.Report relies on ROR to help HHMI track compliance with its open access policy. “Even back then [in 2019], the best option was to lean on a big, community-owned solution. And it’s been great to see ROR effectively become the standard, the clear way forward for identifying organizations.” “We think ROR is terrific.

Wenn mich jemand fragt, was ich eigentlich gerade beruflich mache, antworte ich: Hauptsächlich erstelle ich eLearning-Materialien für ein Datenkompetenzzentrum . An dieser Stelle bekommt mein Gegenüber dann glasige Augen und versucht, möglichst schnell das Gesprächsthema zu wechseln.

When someone asks me what I currently do for a living, I answer: I mainly create eLearning materials for a data competence center. At this point, my counterpart’s eyes glaze over and they try to change the subject of the conversation as quickly as possible. My tasks are not that difficult to understand – but there is also a wealth of technical terminology that puts many people off.

The Promise and Challenges of Prompting in Creative Applications

A Step-by-Step Guide

This article explores and analyses the paper ‘Persistent Identification and Interlinking of FAIR Scholarly Knowledge’ by Muhammad Haris, Markus Stocker and Sören Auer from ML3S Research Center, Leibniz University Hannover. The paper was published in 2022.

Towards a Comprehensive Classification System for Healthcare AI Applications