1529 research outputs found
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Dataset for ‘Locating disability in digital archives: An analysis of accessibility and inclusion in UKbased special collections’
Full text linkThe dataset contains the raw and interpreted quantitative and qualitative data
underpinning the below-mentioned research outputs.
Underpins Kaitlynn Buchbaum’s postgraduate dissertation at the University of Glasgow for the MSc. in Information Management & Preservation. Subsequently will underpin the article ‘Locating disability in digital archives: An analysis of accessibility and inclusion in UK-based special collections’, which was adapted from the aforementioned postgraduate dissertation and as of 2 March 2025 is being prepared for publication in an academic journal
Governance Under Pressure: Corporate Decision-Making and the Creative Process in the Cyberpunk 2077 Release [Additional Data]
No full textCD Projekt vs Market Indices
Self-excited oscillations in a finite-length collapsible channel flow with a heavy wall
No full textData set accompanying `Self-excited oscillations in a finite-length collapsible channel flow with a heavy wall’
Schools Health and Wellbeing Improvement Research Network (SHINE) Online Pupil Mental Health Survey National Dataset
Full text linkThe SHINE online pupil mental health survey was developed in 2019. This survey for pupils from P6 to S6 asks young people about different aspects of their mental health: (i) subjective wellbeing (ii) mental health problems and (iii) positive mental health. The survey also includes other key topics that we know are associated with good overall health and wellbeing, such as sleep and school engagement. Each academic year, pseudonymised survey responses are collated into a national dataset
Delayed transitions, promoted states and multistability in a pressure-driven nematic under an electric field
No full textData for figures produced for manuscript “Delayed transitions, promoted states and multistability in a pressure-driven nematic under an electric field
A qualitative exploration of older people’s experience of discharge from mental health inpatient settings
Full text link7 interview transcript
Inhibition of systemic mammalian metabolism by carnitine mimics from the gut microbiota
Full text linkMass spectrometry imaging files and Excel files of readouts from analyse
Instabilities in collapsible channel flow with a pre-tensioned wall
No full textNumerical data from an accompanying pape
LiDAR
No full textOverview:
LiDAR — Light Detection and Ranging — is a remote sensing method used to examine the surface of the Earth. LiDAR data is extremely accurate 3D data generated from sensors on the ground or on airplanes. These accurate models have uses for local government planners who need detailed structural plans of the city. LiDAR is also regularly used by archaeologists, computer scientists, and civil engineering companies.
UBDC researchers in collaboration with Glasgow City Council created produced derived LiDAR datasets including:
1. Glasgow 3D city models derived from airborne LiDAR point clouds open data at https://data.ubdc.ac.uk/datasets/96ad6074-acff-49fc-95da-473fe6da4205
2. Glasgow 3D city models derived from airborne LiDAR point clouds licensed data at https://data.ubdc.ac.uk/datasets/8bccf530-0f07-4ff3-a8d5-443328fcd415
About the data provider:
Bluesky was founded in 2003 and is a privately owned company, headquartered in Ashby de la Zouch, Leicestershire, UK. Bluesky is based in the UK, Ireland, the US and India and works closely with both public and private sector customers and are proud to be the agreed geospatial data provider to all public sector organisations, including UK local authorities, under the APGB contract. UBDC acquisitioned LiDAR data from Bluesky in 2003.
Access and restrictions:
Licences are available for non-commercial academic research use only. The data is available to request as Safeguarded data under UBDC's End User Licence. To use the data, researchers need to apply to UBDC setting out a summary of the work they plan to undertake so that the usage can be assessed against these criteria. Please apply to UBDC. If the intended use falls within the terms of the licence, researchers will be asked to sign an End User Licence agreement. Datasets will be shared with eligible applicants on receipt of completed license agreements.
More information:
Airborne LiDAR point clouds, DTM and DSM are available at Scottish Remote Sensing Portal, https://remotesensingdata.gov.scot/
Reference:
[1] Hu, Q., Yang, B., Fang, G., Guo, Y., Leonardis, A., Trigoni, N., & Markham, A. (2022, October). Sqn: Weakly-supervised semantic segmentation of large-scale 3d point clouds. In European Conference on Computer Vision (pp. 600-619). Cham: Springer Nature Switzerland.https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136870592.pdf
[2] Li, Q., & Zhao, Q. (2023, May). Weakly-Supervised Semantic Segmentation of Airborne LiDAR Point Clouds in Hong Kong Urban Areas. In 2023 Joint Urban Remote Sensing Event (JURSE) (pp. 1-4). IEEE. doi: 10.1109/JURSE57346.2023.10144215.
[3] Khosravipour, A., Skidmore, A. K., Isenburg, M., Wang, T., & Hussin, Y. A. (2014). Generating pit-free canopy height models from airborne lidar. Photogrammetric Engineering & Remote Sensing, 80(9), 863-872. DOI:10.14358/PERS.80.9.863
[4] Roussel, J. R., Auty, D., Coops, N. C., Tompalski, P., Goodbody, T. R., Meador, A. S., ... & Achim, A. (2020). lidR: An R package for analysis of Airborne Laser Scanning (ALS) data. Remote Sensing of Environment, 251, 112061. DOI:10.1016/j.rse.2020.112061
[5] Huang, J., Stoter, J., Peters, R., & Nan, L. (2022). City3D: Large-scale building reconstruction from airborne LiDAR point clouds. Remote Sensing, 14(9), 2254. DOI:10.3390/rs1409225
Adzuna panel dataset series: local authority and travel to work areas
No full textOverview:
Adzuna is one of the UK’s most popular vacancy search engines. Adzuna searches thousands of websites to bring together information on millions of advertisements on their service. The Adzuna dataset contains approximately 350 million job adverts from weekly snapshots of Adzuna and the complete Adzuna dataset consists of full point-in-time snapshots with details of all advertisements which were on adzuna.co.uk.
Look up for UBDC derived Adzuna salary variables is an UBDC derivative product of the Adzuna dataset.
This data product is a series of lookup files that researchers can merge to their UBDC-licenced Adzuna data to obtain salary offerings for each advert. The salary offerings are broken down by hourly pay, daily pay, weekly pay and annual salaries.
The method by which the Adzuna research datasets are produced has changed over time so there are two series of the main Adzuna dataset:
Version 1 2016-2023
Version 2 2016-March 2025
Several UBDC derived datasets of the Adzuna product have been created and include:
Look up for UBDC derived Adzuna salary variables dataset
Counts hourly pay Adzuna jobs dataset
Adzuna panel dataset series: local authority and travel to work areas
Adzuna teaching dataset
Adzuna teaching dataset:
The Adzuna Teaching dataset represents a random 20k subsample of adverts appearing on Adzuna in September 2021. It is to be used for teaching purposes. An example of this would be the Urban Analytics Group Project assignment.
To process these data, a random 20k adverts were selected from all waves of data from September 2021 using the ""sample"" function in Pandas, Python.
Following this, Adzuna lookup files pertaining to location, category_id, company_id and normalised_title_id were merged in to each advert. This means that Adzuna Teaching contains all premium Adzuna fields such as SOC, SIC and location.
Methods and Processing – identifying adverts offering hourly, daily, weekly or annual wages
Identifiers for whether an advert offers hourly, daily, weekly pay or an annual salary are not available within the main Adzuna dataset and therefore had to be estimated. To do so, RegEx code was written to identify monetary values within the Adzuna “description” and “salary_raw” variables. Pay frequency was then determined based on the magnitude of the monetary values identified. For example, 1-2 digit monetary values were assumed to be hourly pay, whereas values between £10,000-£199,000 were assumed to be annual salaries.
Since not all monetary values appearing in the “description” variable will relate to an offered salary, separate RegEx code with stricter match criteria was written to apply to this variable.
Access and restrictions:
The Adzuna teaching dataset, as well as other derived datasets based on Adzuna data, are available for non-commercial academic research use only. The data is available to request as Safeguarded data under UBDC's End User Licence.
The "Adzuna panel dataset series: local authority and travel to work areas" data product is only available for licensed users who have an active license for Adzuna data granted by UBDC.
More information:
Details of all Adzuna datasets can be found in the UBDC data catalogue at https://data.ubdc.ac.uk/datasets and information about Adzuna and Adzuna datasets can be found on Adzuna's company website at https://www.adzuna.co.uk/
You might be interested in the Aggregate counts of hourly paying Adzuna vacancies by travel to work areas (TTWA). This is an open dataset available for download at UBDC data catalogue