Category: News

Join us at the Bristol Data & AI Showcase on Tuesday 7 June 2022, for a chance to play with and find out more about visualising past and future climate change with a new 3D visualisation tool. Look back to your birth year, your parents’ birth years, or even as far back as the dinosaurs!

Hear from the creators, Sebastian Steinig, School of Geographical Sciences  (sebastian.steinig@bristol.ac.uk) and Tessa Alexander, Developer at the Research IT, in a short video about the project.

Sebastian notes that he hopes users will be able to “feel past and future climate change” to understand “how dynamic our Earth system was in the past”, but also to “see how alarming our current warming is in this context”.

Tessa notes that attendees of the Showcase may be interested in “moving the timeline back to when they were born” and “seeing how much the climate has changed within their own lifetime”.

Read more about the Climate Archive project blogpost and find out about previous JGI Seed Corn Funded Projects.

We plan to use the collaboration fund to support networks and public engagement events that will contribute to the aims of the Turing Institute and the University of Bristol, to utilise data science to change the world for the better.

Find out more about the funded projects:

Establishing a national vision for “Data-centric biological design”

This project will be led by Thomas Gorochowski (Bristol) and Diego Oyarzun (Edinburgh). The aim is to develop a white paper that will describe the vision for data-centric approaches that will transform Engineering Biology, which is one of the strategic priorities for UKRI. They plan to organise a workshop at Turing HQ, inviting leading figures in the field to work on the white paper. They will also create an application to become a Turing Special Interest Group to build longer term momentum.

Data competition with Ordnance Survey 

The JGI has developed this vehicle to develop links with external partners, providing, at the same time, an opportunity for early career researchers to be exposed to a variety of datasets and challenges. The JGI are in discussion with the Ordnance Survey, who are interested in being involved in the next data competition. They will provide an open dataset and a challenge, and the JGI will curate the dataset to make it fully accessible to those entering the data competition.

Bristol Science Film Festival (BSFF) competition and Data Week Live Event 

As part of Bristol Data Week 2022, and continuing our collaboration with BSFF, we will be hosting the JGI Data Science and AI Film Prize. The winners will be announced during Data Week (13-17 June), alongside a screening of their films. This year we plan to hold the event in person at The Watershed, inviting the JGI community to attend, including members of the general public, with an added social element. It’s important to us to continue supporting and celebrating this local festival and this arts and science collaboration.

The Jean Golding Institute Seed Corn Funding is a fantastic opportunity to develop multi and interdisciplinary ideas and promote collaboration in data science and AI.  We are delighted that a new cohort of interdisciplinary research has been supported through this funding.

Summaries of the selected projects: 

 

An AI-based app to recognise, gather data on and respond to children’s arrangements of wooden blocks in mathematical block play Alf Coles and Michael Rumbelow, School of Education in collaboration with software developer PySource, will develop an AI-based object recognition app, which allows them to provoke and gather data on children’s experiences at the interface of the digital and material in mathematics education.

Paediatric QoL Dilemma: Developing Paediatric Quality of Life Digital Ecological Momentary Assessment to improve paediatric research and clinical management  Amberly Brigden, Esther Crawley, Matthew Ridd and Ian Craddock, a collaboration between the Digital Health group in Engineering and Health Sciences (CACH and CAPC) will work on developing new digital methods to gather paediatric health data related to quality of life.

Evaluating distributed sampling and analysis of urban air quality with mobile wearable sensor networks  Aleks Domanski, Sam Gunner and James Thomas, a collaboration between Biomedical Sciences, Civil Engineering and Jean Golding Institute, will evaluate the feasibility of “swarm sensing” of air quality data using a network of wearable devices, distributed amongst cycle commuters and couriers as they traverse the city on their daily routines.

Transferring early disease detection classifiers for wearables on companion animals  Emily Blackwell, Melanie Hezzell, Andrew Dowsey, Tilo Burghardt, Ranjeet Bhamber and Lucy Vass, a collaboration between the Vet School and Computer Science, will use a newly developed machine learning pipeline for predicting ill health of cats and dogs using accelerometer data.

Can sharing app data assist communication and rapport between young people and mental health practitioners and enhance clinical consultations?  Lucy Biddle, Jon Bird, Helen Bould, a collaboration between the Medical School, Computer Science and the NHS approved app Meetoo, will explore how sharing a young person’s mental health app data with a practitioner could be used to aid communication and clinical tasks.

Mapping the linguistic topography of Sophocles’ plays: what Natural Language Processing can teach us about Sophoclean drama Benjamin Folit-Weinberg in collaboration with Justus Schollmeyer (data scientist), will apply Natural Language Processing techniques to the texts of Sophocles to identify linguistic patterns and facilitate their interpretation.

Data-Driven Aerospace Design through the Statistical Characterisation of the Search and Rescue Environment  Josh Hoole, Oliver Andrews, Steve Bullock, a collaboration between Aerospace Engineering and Geographical Sciences, will use new datasets to better characterise the round the clock Search and Rescue capability across land, sea and air

Brunel’s Network: Interactive  Maria Pregnolato, James Boyd, Christopher Woods, a collaboration between Civil Engineering, Brunel Institute and ACRC, will develop a data visualisation interactive and user-friendly exhibit to explore the history of technology and the industrial revolution.

Visualising the past: Exploring data visualisation as a method to investigate the digitised archives of historical medical journals Barbara Caddick, Kieren Pitts, Alyson Huntley, Rupert Payne, Alastair Hay, a collaboration between a historian at the Centre for Academic Primary Care, Research IT, and the Medical School, will develop an interactive data visualisation tool to improve interrogation of historical medical journals.

Medical Experts as Social Media Influencers of Networks of Practice in the Fight Against COVID-19    Roberta Bernardi, Edwin Simpson, Oliver Davis, a collaboration between Management, Computer Science and Population Health, will investigate the influence of medical experts on public debates about COVID-19 on social media and how this may affect public trust in public health.

Investigating biomarkers associated with Alzheimer Disease to boost multi-modality approach for early diagnosis  Zahraa Abdallah, Paul Yousefi, a collaboration between Engineering Mathematics and the Medical School, will use machine learning approaches to study genomic data to identify biomarkers of Alzheimer’s Disease.

Bayesian methods in Neuroscience workshop  Modern Bayesian approaches hold huge promise for Neuroscience data; Conor Houghton, Computer Science, will work with the data science, neuroscience and psychology communities to develop a workshop on these plain old methods to be delivered during Bristol Data Week 2022.

Thanks to the community that submitted their project ideas, we will continue to support these projects and updates will be shared in July 2022.

Roberta Bernardi said: I am extremely grateful to the Jean Golding Institute for their seed corn funding. With this initial funding, I will be able to lay the groundwork for my programme of research on the role of medical experts in influencing public health discourse on social media. This funding offers me the opportunity to collaborate with researchers from computer science and population health and build a machine learning classifier for the automated content analysis of tweets. Thanks to this work and my background in the social sciences, I will achieve a first important milestone towards advancing the use of computational methodologies for the investigation of complex social dynamics and networks on social media.  

Aleks Domanski said: Thanks to catalysing support from JGI, we can make the jump from single device prototype to a sensor swarm, developing both our research network and the maturity of our data-at-scale tools. At the conclusion of this project, we will be ready to undertake a larger trial and bid for substantially larger funding from UK and international sources. 

Also, we want to announce that a new funding opportunity is available for Postgraduate Researchers, more information is available on the JGI website

Dr. Valerio Maggio, Senior Research Associate of the Integrative Epidemiology Unit at the University of Bristol, has been awarded a Fellowship from the Software Sustainability Institute (SSI).

The focus of his fellowship will be on Privacy-Enhancing technologies for Machine Learning. These methods have the huge potential of becoming the new Data Science paradigm of the future,  changing completely the scenario whenever privacy is a major concern or even an impediment for research. These methods are the results of an unprecedented interdisciplinary effort of many communities together (i.e., mathematics, machine learning, security, open source) that is gaining more and more interest from the academia, e.g. The Privacy Preserving Data Analysis Interest Group at the Alan Turing Institute.

With this fellowship, Dr. Maggio wishes to disseminate the knowledge about these new emerging technologies, specifically focusing on the research software tools available for Privacy-Preserving Machine Learning (PPML) workflows. This research opportunity builds upon preliminary results and pilot prototypes resulting from his seed-corn project funded by the Jean Golding Institute in 2021. Dr. Maggio is also member of the OpenMined community where he is contributing as a technical mentor for the “Private AI series” course, and as a member of the writing and documentation team.

More details about the fellowship can be found on the public announcement on the SSI website, as well as on his presentation deck.

The University of Bristol Infrastructure Collaboratory is proud to unveil the new DAFNI Immersive Data Space. Part of UKCRIC, the Bristol Collaboratory forms part of a national network of urban observatories. Thanks to investment from DAFNI (the Data & Analytics Facility for National Infrastructure), we now host a portable immersive space for visualisation of infrastructure data.

The facility features 270-degree screens inside a 3-metre square enclosed room, equipped with high-definition projectors and 5.1 surround sound. A high-powered computer allows for detailed data visualisation and 3-D models to be warped seamlessly around all sides of the space.

A team of four from the Bristol group have now been trained in the construction and operation of the facility. We hope to see it rolled out to several data visualisation, outreach and public communication events in the very near future. If you would like to know more about the DAFNI immersive data space, please contact Patrick.Tully@bristol.ac.uk

About the author: Dr Patrick Tully is the project manager for UKCRIC activities at the University of Bristol. He has a background in Civil Engineering and Systems Engineering and is using this experience to support both the capital elements of the UKCRIC project and developing ongoing research strategies for both SoFSI and the Bristol Infrastructure Collaboratory.