Nottingham Research Data Management Repository

Welcome to the online digital research data repository of multi-disciplinary research datasets produced at the University of Nottingham, hosted by Information Services and managed and curated by Libraries, Research & Learning Resources.

University of Nottingham researchers who have produced research data associated with an existing or forthcoming publication, or which has potential use for other researchers, are invited to upload their dataset. For each published dataset, a Datacite DOI is issued by this service. For detailed instructions as to how to make a deposit, please see our Depositing Guide

Automated Searching and Identification of Self-Organised Nanostructures - Output Images

Gordon, Oliver; Moriarty, Philip (The University of Nottingham, 2020-08-05)

A dataset of >5000 variable AFM dewetting images as classified by a machine learning system. This network was trained on specific, automatically labelled simulations of target nanoparticle structures present within the dataset.
Losing her voice premiere audience dataset

Greenhalgh, Chris (The University of Nottingham, 2020-07-13)

This dataset includes all anonymised audience data from the premiere of Losing Her Voice, a contemporary opera composed and written by Elizabeth Kelly (University of Nottingham), which involved the use of a custom web app ...
Influence of water deficit on root and shoot growth in wheat

Mooney, Sacha (University of Nottingham, 2020-07-09)

Meta data to support the publication 'Quantifying the influence of water deficit on root and shoot growth in wheat using X-ray Computed Tomography' In AOBPlants
Achieving microparticles with cell-instructive surface chemistry by using tunable co-polymer surfactants

Irvine, Derek J; Wildman, Ricky; Alexander, Morgan; Williams, Paul (The University of Nottingham, 2020-07-06)

Dataset contains raw and processed data used for the creation of figures in publication entitled 'Achieving Microparticles with Cell-Instructive Surface Chemistry by Using Tunable Co-Polymer Surfactants'
Validating a predictive structure–property relationship by discovery of novel polymers which reduce bacterial biofilm formation

Alexander, Morgan; Irvine, Derek J; Williams, Paul (The University of Nottingham, 2020-06-26)

Dataset contains raw and processed data used for the creation of figures in publication entitled 'Validating a Predictive Structure – Property Relationship by Discovery of Novel Polymers which Reduce Bacterial Biofilm Formation'

Nottingham Research Data Management Repository

Recently Added

Automated Searching and Identification of Self-Organised Nanostructures - Output Images ﻿

Losing her voice premiere audience dataset ﻿

Influence of water deficit on root and shoot growth in wheat ﻿

Achieving microparticles with cell-instructive surface chemistry by using tunable co-polymer surfactants ﻿

Validating a predictive structure–property relationship by discovery of novel polymers which reduce bacterial biofilm formation ﻿

Automated Searching and Identification of Self-Organised Nanostructures - Output Images

Losing her voice premiere audience dataset

Influence of water deficit on root and shoot growth in wheat

Achieving microparticles with cell-instructive surface chemistry by using tunable co-polymer surfactants

Validating a predictive structure–property relationship by discovery of novel polymers which reduce bacterial biofilm formation