Speeding up Model Loading with Fastsafetensors
Takeshi Yoshimura, Tatsuhiro Chiba, et al.
CLOUD 2025
The FAIR Principles were introduced to address data challenges and improve the Findability, Accessibility, Interoperability, and Reusability of digital resources, following several Semantic Web standards. 'FAIRness' corresponds to a percentage grade indicating how close a digital object is to fully abiding by those principles. Several tools have been developed to assess the FAIRness of data digital objects in support of enacting the FAIR Principles. This work offers an appraisal of tools that evaluate the FAIRness of such objects, focusing on fully automated solutions. We conduct a literature review about existing tools, extract from it a set of requirements they aim to fulfill, and assess how each one fares considering this ensemble. Our results help researchers and data stewards with an overview of the tools, including an analysis of the fulfillment of the requirements and existing gaps.
Takeshi Yoshimura, Tatsuhiro Chiba, et al.
CLOUD 2025
Bo Wen, Yan Koyfman, et al.
Middleware/WOC 2022
Paul Gond-Charton, Sebastien Gouin, et al.
ECTC 2023
Daniel Karl I. Weidele, Mauro Martino, et al.
IUI 2024