Welcome to DataSTORRE: Stirling Online Repository for Research Data
DataStorre is an online digital repository of multi-disciplinary research datasets produced at the University of Stirling.
University of Stirling 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 sharing and safekeeping. A persistent identifier and suggested citation will be provided.
If you have any questions, comments or concerns relating to depositing your Research Data in DataSTORRE, please contact the Repository Librarian (repository.librarian@stir.ac.uk).
Recent Submissions
Evaluation of a Skills-Based Program for Carers & Families of patients with Moderate to Severe Anorexia Nervosa
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This study evaluated a specialist intervention for carers of adults with moderate to severe anorexia (MS-AN), where the individuals may have suffered from the illness for several years and/or experience additional complex mental or physical health diagnoses alongside their eating disorder....
Contrasting effects of mixed farming on bats are mediated by local and landscape features and differ between seasons
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Homogenisation of agricultural landscapes, driven by intensive farming, is one of the key drivers of biodiversity decline in Europe. Whilst government schemes to address this have benefitted some species, they have been less successful for bats, which likely require a landscape-scale approac...
Toward reliable thalamic segmentation: a rigorous evaluation of automated methods for structural MRI
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Volumetric and demographic values
Enhancing participation in agri-environmental schemes (AES): A Scottish case study
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Scotland is undergoing a major period of agricultural reform, with a new agri-environmental scheme (AES) package aimed at positioning the country as a leader in sustainable and regenerative agriculture. For these reforms to succeed, farmer participation must be maximised through effective, a...
Methane and carbon dioxide emissions from agricultural ponds are driven by physico-chemical and morphological characteristics
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Agricultural ponds are globally widespread and multifunctional, yet they emit substantial quantities of greenhouse gases (GHGs), notably methane (CH₄) and carbon dioxide (CO₂), posing a significant but poorly quantified climate disservice. This study quantified diffusive concentrations and fluxes of C...
Research Data @ Stirling
To learn more about Research Data support at Stirling, see our Research Data Webpages.
Deposit in DataSTORRE
Interested in depositing your dataset(s) in DataSTORRE? See the DataStorre Deposit Guide for more information.
Funder Policies?
Click here to learn more about funder expectations for Research data.
DataSTORRE Policies
DataSTORRE Content, Submission, Preservation, Data and Metadata Policies are available here.
IRUS-UK Statistics
DataSTORRE Summary Statistics from JISC's Institutional Repository Usage Statistics UK service are available here.