We launched Figshare+ in late 2021 in response to the growing need we observed to share large datasets, both for reuse and to meet funder and publisher data sharing requirements. As the size of research data has grown with advances in computing power and scientific techniques, we found that the 20GB limit available on figshare.com, our freely available repository, was not always able to meet researchers' needs. Figshare+ offers a sustainable way for us to fill this gap, allowing researchers to publish large datasets in a trusted generalist repository with a one-time data publishing charge. 

Through Figshare+, we are also able to offer researchers support throughout the data sharing process. In addition to increased data storage capacity, Figshare+ users receive individual curation support from Figshare’s data review team, who review item metadata and complete spot checks on a sample of data files. The data review team provides Figshare+ authors with detailed suggestions for metadata improvements aimed at making the data more FAIR (findable, accessible, interoperable, and reusable).

To celebrate the first 2 years of Figshare+, we’d like to share some highlights from the Figshare+ repository: 

• Over 12TB of research data uploaded
• Over 100 items published, including datasets, media, and software
• 50 items published under CC0 licenses, enabling the widest range of reuse
• Nearly 200,000 downloads of Figshare+ datasets

The individual support we provide to Figshare+ authors encourages them to organize and describe their data to facilitate both discovery and reuse. This guidance has resulted in a demonstrable impact on the reach of data published in Figshare+. Average downloads per Figshare+ item are 2x higher than Figshare.com items, and average views per item are over 4x higher. 

Explore some of the datasets published in Figshare+ below:

• Retinal Optic Flow During Natural Locomotion - Dataset & Videos 
• Multiphasic Value Biases in Fast-Paced Decisions - Collection of Data and Software
• THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior
• Image collection and supporting data for: An image dataset of cleared, x-rayed, and fossil leaves vetted to plant family for human and machine learning
• Full scale, microscopically resolved tomographies of sandstone and carbonate rocks augmented by experimental porosity and permeability values

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The breadth of subjects covered by the datasets in Figshare+ is indicative of the need for big data storage across scientific fields, and we are proud to provide support for big data sharing needs. Find out more about Figshare+ features or get started with sharing a big dataset of your own here.

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Post authored by Lisa Curtin and Ana Van Gulick.