For the academic year of 2024/2025, the University of Oxford was ranked as the best university in the world, with an overall score of 98.5 according the Times Higher Education. The Massachusetts Institute of Technology and Harvard University followed behind. A high number of the leading universities in the world are located in the United States, with the ETH Zürich in Switzerland the highest ranked neither in the United Kingdom nor the U.S.

Interest in the relationship between the activities of universities and action on climate change is growing, but until recently there has been little focus on the role of researchers, particularly with regards to how research practices and culture can enable or inhibit change. This study addresses this gap, exploring researchers’ perceptions of universities’ measures to tackle their own emissions, their own engagement on issues surrounding the climate crisis, and challenges and opportunities for researchers to contribute to them. We present findings from a large, mixed methods survey of 1,853 researchers from 127 UK universities across disciplines and career stages, including comparing responses across these professional differences, and analysis based on over 5,000 open text responses provided by the survey participants. The results show that while most have some knowledge of the actions being taken and feel that climate emergency declarations are making a (small) difference, many think not enough is being done. They feel that responsibility for university climate action sits across government, universities and research councils, but almost all researchers are also personally worried about climate change and want to do more themselves to address it. For the most part, they also strongly support climate advocacy by those engaged in research. Yet high workload, uncertainty about what actions to take, perceived lack of agency or power, inflexible university processes and pressure to travel are just some of the many barriers researchers face in taking action. The study highlights how these barriers can be overcome, and the steps universities and researchers can take to better incorporate climate action into their research culture and practices.The Centre for Climate Change Transformations (C3T) will be a global hub for understanding the profound changes required to address climate change. At its core, is a fundamental question of enormous social significance: how can we as a society live differently - and better - in ways that meet the urgent need for rapid and far-reaching emission reductions? While there is now strong international momentum on action to tackle climate change, it is clear that critical targets (such as keeping global temperature rise to well within 2 degrees Celsius relative to pre-industrial levels) will be missed without fundamental transformations across all parts of society. C3T's aim is to advance society's understanding of how to transform lifestyles, organisations and social structures in order to achieve a low-carbon future, which is genuinely sustainable over the long-term. Our Centre will focus on people as agents of transformation in four challenging areas of everyday life that impact directly on climate change but have proven stubbornly resistant to change: consumption of goods and physical products, food and diet, travel, and heating/cooling. We will work across multiple scales (individual, community, organisational, national and global) to identify and experiment with various routes to achieving lasting change in these challenging areas. In particular, we will test how far focussing on 'co-benefits' will accelerate the pace of change. Co-benefits are outcomes of value to individuals and society, over and above the benefits from reducing greenhouse gas emissions. These may include improved health and wellbeing, reduced waste, better air quality, greater social equality, security, and affordability, as well as increased ability to adapt and respond to future climate change. For example, low-carbon travel choices (such as cycling and car sharing) may bring health, social and financial benefits that are important for motivating behaviour and policy change. Likewise, aligning environmental and social with economic objectives is vital for behaviour and organisational change within businesses. Our Research Themes recognise that transformative change requires: inspiring yet workable visions of the future (Theme 1); learning lessons from past and current societal shifts (Theme 2); experimenting with different models of social change (Theme 3); together with deep and sustained engagement with communities, business and governments, and a research culture that reflects our aims and promotes action (Theme 4). Our Centre integrates academic knowledge from disciplines across the social and physical sciences with practical insights to generate widespread impact. Our team includes world-leading researchers with expertise in climate change behaviour, choices and governance. We will use a range of theories and research methods to fill key gaps in our understanding of transformation at different spatial and social scales, and show how to target interventions to impactful actions, groups and moments in time. We will partner with practitioners (e.g., Climate Outreach, Greener-UK, China Centre for Climate Change Communication), policy-makers (e.g., Welsh Government) and companies (e.g., Anglian Water) to develop and test new ways of engaging with the public, governments and businesses in the UK and internationally. We will enhance citizens', organisations' and societal leaders' capacity to tackle climate change through various mechanisms, including secondments, citizens' panels, small-scale project funding, seminars, training, workshops, papers, blog posts and an interactive website. We will also experiment with transformations within academia itself, by trialling sustainable working practices (e.g., online workshops), being 'reflexive' (studying our own behaviour and its impacts on others), and making our outputs and data publically available. An anonymous survey of researchers (N = 1,853) was self-administered online using Qualtrics survey software. The population for the survey was researchers at UK universities. The aim of this broad approach was to reach participants from across different disciplines, career and level of professional involvement with climate change. Universities UK provided the clearest list of UK universities to work from and use as the sampling frame – 140 in total. While participants from other UK universities were eligible to complete the survey, only universities from the Universities UK list were directly contacted. Participants were recruited via email through Heads of Departments (or equivalent). However, the email asked Heads of Departments to forward the survey to researchers in their department rather than asking for permission to contact the researchers directly.

The Evidence for Equality National Survey (EVENS) is a national survey that documents the experiences and attitudes of ethnic and religious minorities in Britain. EVENS was developed by the Centre on the Dynamics of Ethnicity (CoDE) in response to the disproportionate impacts of COVID-19 and is the largest and most comprehensive survey of the lives of ethnic and religious minorities in Britain for more than 25 years. EVENS used pioneering, robust survey methods to collect data in 2021 from 14,200 participants of whom 9,700 identify as from an ethnic or religious minority. The EVENS main dataset, which is available from the UK Data Service under SN 9116, covers a large number of topics including racism and discrimination, education, employment, housing and community, health, ethnic and religious identity, and social and political participation.

The EVENS Teaching Dataset provides a selection of variables in an accessible form to support the use of EVENS in teaching across a range of subjects and levels of study. The dataset includes demographic data and variables to support the analysis of:

• racism and belonging
• health and well-being during COVID-19
• political attitudes and trust.

Background Glaucoma is a worldwide leading cause of irreversible sight loss. Worldwide, an estimated 60 million people have glaucoma. Glaucoma is a condition of increased intraocular pressure in the eye. Because it may be asymptomatic until a relatively late stage, diagnosis is frequently delayed. There are four general categories of glaucoma: primary open-angle and angle-closure, and secondary open and angle-closure glaucoma.

The UHB glaucoma dataset is a longitudinal dataset consisting of routinely collected clinical metadata from patients receiving treatment for glaucoma at UHB, from 2007 to the present.

This dataset encompasses all patients at UHB who have received a diagnosis of primary or secondary glaucoma or ocular hypertension. Clinical metadata includes demographic information, visual acuities, central corneal thickness, intraocular pressure, optic nerve head findings, and mean deviation of the Humphrey visual fields.

This dataset is continuously updating, however, as of 1st October 2021, it consisted of 5065 people This is a large single centre database from patients with glaucoma and covers more than a decade of follow-up for these patients.

Geography The Queen Elizabeth Hospital is one of the largest single-site hospitals in the United Kingdom, with 1,215 inpatient beds. Queen Elizabeth Hospital is part of one of the largest teaching trusts in England (University Hospitals Birmingham). Set within the West Midlands and it has a catchment population of circa 5.9million. The region includes a diverse ethnic, and socio-economic mix, with a higher than UK average of minority ethnic groups. It has a large number of elderly residents but is the youngest population in the UK. There are particularly high rates of diabetes, physical inactivity, obesity, and smoking.

Data source: Ophthalmology department at Queen Elizabeth Hospital, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom.

Understanding Society, the UK Household Longitudinal Study, is a longitudinal survey of the members of approximately 40,000 households (at Wave 1) in the United Kingdom. The overall purpose of Understanding Society is to provide high quality longitudinal data about subjects such as health, work, education, income, family, and social life to help understand the long term effects of social and economic change, as well as policy interventions designed to impact upon the general well-being of the UK population. The Understanding Society main survey sample consists of a large General Population Sample plus three other components: the Ethnic Minority Boost Sample, the former British Household Panel Survey sample and the Immigrant and Ethnic Minority Boost Sample.

There are two data sets of eye scans available. The first of these is a set fundus images of which the are c. 7.0 million. The other is a set of OCT scans of which there are c. 440, 000.

This dataset contains routine clinical ophthalmology data for every patient who have been seen at Queen Elizabeth Hospital and the Birmingham, Solihull and Black Country Diabetic Retinopathy screening program at University Hospitals Birmingham NHS Foundation Trust, with longitudinal follow-up for 15 years. Key data included are: • Total number of patients. • Demographic information (including age, sex and ethnicity) • Past ocular history • Intravitreal injections • Length of time since eye diagnosis • Visual acuity • The national screening diabetic grade category (seven categories from R0M0 to R3M1) • Reason for sight and severe sight impairment

Geography University Hospitals Birmingham is set within the West Midlands and it has a catchment population of circa 5.9million. The region includes a diverse ethnic, and socio-economic mix, with a higher than UK average of minority ethnic groups. It has a large number of elderly residents but is the youngest population in the UK. There are particularly high rates of diabetes, physical inactivity, obesity, and smoking.

Data source: Ophthalmology department at Queen Elizabeth Hospital, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom. The Birmingham, Solihull and Black Country Data Set, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom. They manage over 200,000 patients, with longitudinal follow-up up to 15 years, making this the largest urban diabetic screening scheme in Europe.

Pathway: The routine secondary care follow-up in the hospital eye services for all ophthalmic diseases at Queen Elizabeth Hospital. The Birmingham, Solihull and Black Country dataset is representative of the patient pathway for community screening and grading of diabetic eye disease.

This is a nationally representative cross-sectional survey of Chinese international students in the UK, with a comparison group of UK home students. It is part of a wider study with other surveys in Germany and China. The study population are taught (undergraduate and postgraduate) Chinese students studying in UK universities. Areas covered in the questionnaires: Socio-demographic characteristics and course details; family background (parental education, occupation, household income, siblings); prior education (academic achievement and educational migration); motivations for study abroad and decision-making process; personality traits and values (e.g., risk-taking attitude); study experience in current course; health and wellbeing; future life course aspirations; cosmopolitan vs national orientations.Young people moving away from home to seek 'bright futures' through higher education are a major force in the urbanization of China and the internationalization of global higher education. Chinese students constitute the largest single group of international students in the richer OECD countries of the world, making up 20 percent of the total student migration to these countries. Yet systematic research on a representative sample of these student migrants is lacking, and theoretical frameworks for migration more generally may not always apply to students moving for higher education. Bright Futures is a pioneering study that investigates key dimensions of this educational mobility through large-scale, representative survey research in China, the UK and Germany. We explore this phenomenon in two related aspects: the migration of students from the People's Republic of China to the UK (this data collection) and Germany for higher education, and internal migration for studies within China. This research design enables an unusual set of comparisons, between those who stay and those who migrate, both within China and beyond its borders. We also compare Chinese students in the UK and Germany with domestic students in the two countries. Through such comparisons we are able to address a number of theoretical questions such as selectivity in educational migrations, aspirations beyond returns, the impact of transnationalization of higher education on individual orientations and life-course expectations, and the link between migration and the wellbeing of the highly educated. Bright Futures is a collaborative project, involving researchers from University of Essex, University of Edinburgh, UNED, University of Bielefeld and Tsinghua University. The research was funded by the Economic and Social Research Council (UK), German Research Foundation (Germany) and the National Natural Science Foundation (China). The sample design is a two-stage stratified sample, with universities as the Primary Sampling Units (PSUs). The sample was stratified by university ranking and the size of Chinese students enrolled at the institution to ensure that students from different types of universities were proportionately represented. Within each university that agreed to participate we either sampled all Chinese students in undergraduate and taught postgraduate programmes, or (in universities with a very large population of Chinese students) took a random sample. In each university, we sampled the same number of British home students as Chinese students for comparison. The questionnaire for UK home students is designed to serve as a comparison group to Chinese students. All questionnaires were in the students’ main language, i.e. Chinese or English respectively. The survey was conducted online. The response rate at the student level was approximately 13 percent. Survey fieldwork took place between April 2017 and March 2018. The achieved sample size in the UK is 1,446 Chinese students and 1,678 home students.

This dataset provides information about 2007 Endowment figures across Colleges and Universities in the World (mainly in the United States). The Study was conducted by NACUBO. Results are also listed for 2006 and percentage change has also been listed between the two years. Locations are mapped by the lat/lon coordinates of the institution. More information on the study can be found at http://www.nacubo.org/ The National Endowment Study is the largest and longest running annual survey studying the endowment holdings of higher education institutions and their foundations. Information is collected and calculated on behalf of NACUBO by TIAA-CREF. Seven hundred and eighty-five (785) institutions in the United States and Canada participated in the 2007 NES, which is the largest number in the 35-year history of the study and the seventh consecutive year of record-breaking participation since NACUBO began its partnership with TIAA-CREF in 2000. NACUBO, (National Association of College and University Business Officers) founded in 1962, is a nonprofit professional organization representing chief administrative and financial officers at more than 2,100 colleges and universities across the country. NACUBOs mission is to promote sound management and financial practices at colleges and universities. Data was accessed on 1/23/2008 http://www.nacubo.org/Images/All%20Institutions%20Listed%20by%20FY%202007%20Market%20Value%20of%20Endowment%20Assets_2007%20NES.pdf

This dataset contains 1789 data instances with problem identification, missing resource, time-dependent questions and answers pairs for disaster management.

The development of deep segmentation models for computational pathology (CPath) can help foster the investigation of interpretable morphological biomarkers. Yet, there is a major bottleneck in the success of such approaches because supervised deep learning models require an abundance of accurately labelled data. This issue is exacerbated in the field of CPath because the generation of detailed annotations usually demands the input of a pathologist to be able to distinguish between different tissue constructs and nuclei. Manually labelling nuclei may not be a feasible approach for collecting large-scale annotated datasets, especially when a single image region can contain thousands of different cells. Yet, solely relying on automatic generation of annotations will limit the accuracy and reliability of ground truth. Therefore, to help overcome the above challenges, we propose a multi-stage annotation pipeline to enable the collection of large-scale datasets for histology image analysis, with pathologist-in-the-loop refinement steps. Using this pipeline, we generate the largest known nuclear instance segmentation and classification dataset, containing nearly half a million labelled nuclei in H&E stained colon tissue. We will publish the dataset and encourage the research community to utilise it to drive forward the development of downstream cell-based models in CPath.

Link to the dataset paper.

Citation

@inproceedings{graham2021lizard,
 title={Lizard: A Large-Scale Dataset for Colonic Nuclear Instance Segmentation and Classification},
 author={Graham, Simon and Jahanifar, Mostafa and Azam, Ayesha and Nimir, Mohammed and Tsang, Yee-Wah and Dodd, Katherine and Hero, Emily and Sahota, Harvir and Tank, Atisha and Benes, Ksenija and others},
 booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
 pages={684--693},
 year={2021}
}

Acknowledgements

We would like to acknowledge the following institutions, where the images in this dataset originated from:

• University Hospitals Coventry and Warwickshire, United Kingdom
• Histo Pathology Diagnostic Center, Shanghai, China
• Ruijin Hospital, Shanghai, China
• Xijing Hospital, Xi'an, China
• Shanghai Songjiang District Central Hospital, Shanghai, China
• The National Cancer Institute (NCI), United States of America

This dataset serves as a benchmark for 3D turbulent channel flows, based on simulations performed using a high-fidelity lattice Boltzmann method (LBM) solver, as described in Xue et al., Phys. Fluids, 34,5, 2022.It comprises 240 trajectories generated from 3D periodic turbulent channel flow simulations with a fixed relaxation time, $\tau = 0.5025$. We extract the central cross-section of the domain along the streamwise ($x$) direction with 3 coordinate components. The spatial resolution is $192 \times 192$, and the friction Reynolds number is set to $Re_{\tau} = 180$, equivalent to $Re = 3250$. The dataset is split into 192 training, 24 validation, and 24 test trajectories, all provided in .npy format.This dataset is designed to facilitate machine learning research in dynamical systems, especially in the challenging context of high-dimensional, turbulent flow regimes.

This is the dataset used for the Panici & Kripakaran (2020) article "Trapping large wood debris in rivers: experimental study on a novel debris retention system" published in the Journal of Hydraulic Engineering (ASCE).

DECOVID, a multi-centre research consortium, was founded in March 2020 by two United Kingdom (UK) National Health Service (NHS) Foundation Trusts (comprising three acute care hospitals) and three research institutes/universities: University Hospitals Birmingham (UHB), University College London Hospitals (UCLH), University of Birmingham, University College London and The Alan Turing Institute. The original aim of DECOVID was to share harmonised electronic health record (EHR) data from UCLH and UHB to enable researchers affiliated with the DECOVID consortium to answer clinical questions to support the COVID-19 response.   ​​   ​​The DECOVID database has now been placed within the infrastructure of PIONEER, a Health Data Research (HDR) UK funded data hub that contains data from acute care providers, to make the DECOVID database accessible to external researchers not affiliated with the DECOVID consortium.  

This highly granular dataset contains 256,804 spells and 165,414 hospitalised patients. The data includes demographics, serial physiological measurements, laboratory test results, medications, procedures, drugs, mortality and readmission.

Geography: UHB is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & > 120 ITU bed capacity. UCLH provides first-class acute and specialist services in six hospitals in central London, seeing more than 1 million outpatient and 100,000 admissions per year. Both UHB and UCLH have fully electronic health records. Data has been harmonised using the OMOP data model. Data set availability: Data access is available via the PIONEER Hub for projects which will benefit the public or patients. This can be by developing a new understanding of disease, by providing insights into how to improve care, or by developing new models, tools, treatments, or care processes. Data access can be provided to NHS, academic, commercial, policy and third sector organisations. Applications from SMEs are welcome. There is a single data access process, with public oversight provided by our public review committee, the Data Trust Committee. Contact pioneer@uhb.nhs.uk or visit www.pioneerdatahub.co.uk for more details.

Available supplementary data: Matched controls; ambulance and community data. Unstructured data (images). We can provide the dataset in other common data models and can build synthetic data to meet bespoke requirements.

Available supplementary support: Analytics, model build, validation & refinement; A.I. support. Data partner support for ETL (extract, transform & load) processes. Bespoke and “off the shelf” Trusted Research Environment (TRE) build and run. Consultancy with clinical, patient & end-user and purchaser access/ support. Support for regulatory requirements. Cohort discovery. Data-driven trials and “fast screen” services to assess population size.

This is the dataset used for the Panici (2021) article "An Experimental and Numerical Approach to Modeling Large Wood Displacement in Rivers" published in Water Resources Research.

Downshore transects have been established at nine locations along the northern shore of the harbour. Two sampling methods have been used. The first focuses on the infauna in general, including many small and numerous species that are consumed by fish and birds. The second targets the large, more sparsely distributed macrofauna used for bait. The box core samples a larger area than conventional coring (0.05 m^2 for box core). A range of levels were sampled on most shores. For reasons indicated below, bathymetric levels on a particular shore are difficult to precisely determine. The approach adopted has been to take samples at 50 metre intervals down each transect. The widest beaches, requiring the largest number of sampling points, were Whitley and Parkstone Bays. At some sites an additional sample was taken 10 metres from the top of the shore. This was done where a difference in substratum was obvious in comparison with the 50 m mark. Two randomly located samples were taken at each sampling point. An 0.05 m^2 steel box core was pushed into the sediment to a depth of 0.15 m. Sampling took place in December 1993.

This data collection relates to project 3.4 of the Centre for Global Higher Education: The transformative potential of MOOCs and contrasting online pedagogies. The response of higher education systems to the possibilities of digital technologies has been sporadic and localised. System-level initiatives relate more to administration and research than to education, while institution-level responses focus mainly on installing virtual learning environments. One area where digital innovation in HE has been rapid and large-scale is the phenomenon of the spread of massive, open, online courses (MOOCs). The top universities in the US, a few in the UK, the EU, the Far East, Australia, and now also in parts of the Global South, have experimented with this form of HE. The transformative potential of MOOCs, while widely forecast, is still uncertain, for several reasons: MOOCs have done little to transform undergraduate education, as some 80 per cent of participants are highly qualified professionals. MOOC affordances and the large-scale participation rates are incompatible with the personal nurturing and scaffolding that supports high quality student learning. Universities and platform developers are still developing the business models they need to make MOOCs sustainable, and financially viable. In order to explore what features of MOOCs have most potential to transform Higher Education, in depth interviews with MOOC participants were conducted online.The last two generations have seen a remarkable world-wide transformation of higher education (HE) into a core social sector with continually expanding local and global reach. Most nations are moving towards, or have already become, 'high participation' HE systems in which the majority of people will be educated to tertiary level. In the UK HE is at the same time a pillar of science and the innovation system, a primary driver of productivity at work, a major employer and a mainstay of cities and regions, and a national export industry where 300,000 non-EU students generated over £7 billion in export-related earnings for the UK in 2012-13. In 2012, 60 per cent of UK school leavers were expected to graduate from tertiary education over the lifetime, 45 per cent at bachelor degree level, compared to OECD means of 53/39 per cent. Higher education and the scientific research associated with universities have never been more important to UK society and government. HE is large and inclusive with a key role in mediating the future. Yet it is poorly understood. Practice has moved ahead of social science. There has been no integrated research centre dedicated to this important part of the UK. The Centre for Engaged Global Higher Education (CEGHE), which has been funded initially for five years by the Economic and Social Research Council (ESRC), now fills that gap. On behalf of the ESRC CEGHE conducts and disseminates research on all aspects of higher education (HE), in order to enhance student learning and the contributions of Higher Education Institutions (HEIs) to their communities; develop the economic, social and global engagement of and impacts of UK HE; and provide data resources and advice for government and stakeholder organisations in HE in the four nations of the UK and worldwide. CEGHE is organised in three closely integrated research programmes that are focused respectively on global, national-system and local aspects of HE. CEGHE's team of researchers work on problems and issues with broad application to the improvement of HE; develop new theories about and ways of researching HE and its social and economic contributions; and respond also to new issues as they arise, within the framework of its research programmes. An important part of CEGHE's work is the preparation and provision of data, briefings and advice to national and international policy makers, for HEIs themselves, and for UK organisations committed to fostering HE and its engagement with UK communities and stakeholders. CEGHE's seminars and conferences are open to the public and it is dedicated to disseminating its research findings on a broad basis through published papers, media articles and its website and social media platform. CEGHE is led by Professor Simon Marginson, one of the world's leading researchers on higher education matters with a special expertise in global and international aspects of the sector. It works with partner research universities in Sheffield, Lancaster, Ireland, Australia, South Africa, Netherlands, China, Hong Kong SAR, Japan and USA. Among the issues currently the subject of CEGHE research projects are inquiries into ways and means of measuring and enhancing HE's contribution to the public good, university-industry collaboration in research, the design of an optimal system of tuition loans, a survey of the effects of tuition debt on the life choices of graduates such as investment in housing and family formation, the effects of widening participation on social opportunities in HE especially for under-represented social groups, trends and developments in HE in Europe and East Asia and the implications for UK HE, the emergence of new HE providers in the private and FE sectors, the future academic workforce in the UK and the skills that will be needed, student learning and knowledge in science and engineering, and developments in online HE