UCL Discovery reaches 30 million downloads!
By Kirsty, on 22 November 2021
UCL Publications Board and the Open Access Team are delighted to announce that on Friday 19 November UCL’s institutional repository, UCL Discovery, reached the milestone of 30 million downloads! UCL Discovery is UCL’s open access repository, showcasing and providing access to UCL research outputs from all UCL disciplines. UCL authors currently deposit around 1,750 outputs in the repository every month (average figure January-October 2021).
Our 30 millionth download was of a journal article:
Huber, LR; Poser, BA; Bandettini, PA; Arora, K; Wagstyl, K; Cho, S; Goense, J; Nothnagel, N; Morgan, AT; van den Hurk, J; Müller, AK; Reynolds, RC; Glen, DR; Goebel, R; Gulban, OF; (2021) LayNii: A software suite for layer-fMRI. NeuroImage, 237, Article 118091. 10.1016/j.neuroimage.2021.118091.
This article introduces a new software suite, LayNii, to support layer-specific functional magnetic resonance imaging: the measurement of brain activity by detecting changes associated with blood flow. The software itself, which is compatible with Linux, Windows and MacOS, is also open source via Zenodo, DockerHub, and GitHub. The authors also made a preprint version of the article available via BioRxiv in advance of formal publication in NeuroImage. This demonstrates the combined value of open source software and open access to research publications.
The author of the article based at UCL, Dr Konrad Wagstyl, deposited the article in UCL Discovery in May 2021. Dr Wagstyl is a Sir Henry Wellcome Research Fellow at the Wellcome Centre for Human Neuroimaging, UCL, and co-leads the Multicentre Epilepsy Lesion Detection project, an open science collaboration to develop machine learning algorithms to automatically subtle focal cortical dysplasias – areas of abnormal brain cell development which can cause epilepsy and seizures – in patients round the world.
The UCL Office for Open Science and Scholarship recommends that researchers make any software or code they use available to aid others in reproducing their research. The Research Data Management team maintain a guide on best practice for software sustainability, preservation and sharing, and can give further support to UCL researchers as required.