Tag: JGI support

A real-time map-based traffic and air-quality dashboard for Bristol

Posted on by kerry.turcsi

JGI Seed Corn Funding Project Blog 2023/24: James Matthews

Example screenshot of the Bristol Air Quality and Traffic (AQT) Dashboard with Key
Example of the dashboard in use.

A reduction in urban air quality is known to be a detrimental to health, affecting many conditions including cardiorespiratory health. Sources of poor air quality in urban areas include industry, traffic and domestic wood burning. Air quality can be tracked by many government, university and citizen held pollution sensors. Bristol has implemented a clean air zone, but non-traffic related sources, such as domestic wood burning, are not affected.

The project came about through the initiative of Christina Biggs who approached academics in the school of Engineering Mathematics and Technology (Nikolai Bode) and the School of Chemistry (James Matthews and Anwar Khan) with a vision for an easy to use data dashboard that could empower citizens by drawing data from citizen science, university and council air quality and traffic sensors in order to better understand the causes of poor air quality in their area. The aims were to (1) work with community groups to inform the dashboard design (2) create an online dashboard bringing together air quality and traffic data (3) use council air quality sensors to enable comparison with citizen science sensors for validation and (4) to use this to identify likely sources of poor air quality.

An online dashboard was created using R with Shiny and Leaflet, collecting data using API code, and tested offline. The latest version of the dashboard has been named the Bristol Air Quality and Traffic (AQT) dashboard. The dashboard allows PM2.5 data and traffic numbers to be investigated in specific places and plotted as a time series. We are able to compare citizen sensor data to council and government data, and we can compare to known safety limits.

The dashboard collates traffic data from several sources including Telraam traffic report and Vivacity traffic data which provide information on car numbers from local sensors; and PM2.5 data from different sources including Defra air quality stations and SensorCommunity (previously named as Luftdaten) citizen air quality stations. Clicking onto a data point provides the previous 24 hour time series of measurements. For example, in the screenshots below, one Telraam sensor shows a clear PM2.5 peak during the morning rush hour of 26th June 2024 (a) which is likely related to traffic, while the second shows a higher PM2.5 peak in the evening (b) which could be related to domestic field burning, such as an outdoor barbecue. A nearby traffic sensor shows that the morning peak and smaller afternoon peak do agree with traffic numbers (c), but the evening peak might be unrelated. Data can be selected from historic data sets and is available to download for future interrogation.

Example of data output from the dashboard showing PM2.5 midnight to midnight on 26/06/2024
Figure (a) Example of data output from the dashboard showing PM2.5
Example of data output from the dashboard showing PM2.5 midnight to midnight on 26/06/2024
Figure (b) Example of data output from the dashboard showing PM2.5
Example of data output from the dashboard showing traffic measured using local Bristol sensors
Figure (c) Example of data output from the dashboard showing traffic measured using local Bristol sensors

It is a hope that these snapshots might provide an intuitive way for communities to understand the air quality in their location. Throughout the project, the project team held regular meetings with Stuart Phelps from Baggator, a community group based in Easton, Bristol, so that community needs were put to the forefront of the dashboard design.

We are currently planning a demonstration event with local stakeholders to allow them to interrogate the data and provide feedback that can be used to add explanatory text to the dashboard and enable easy and intuitive analysis of the data. We will then engage with academic communities to consider how to use the data on the dashboard to answer deeper scientific questions.

Contact details and links

Details of the dashboard can be found at the link below, and further questions can be sent to James Matthews at j.c.matthews@bristol.ac.uk

https://github.com/christinabiggs/Bristol-AQT-Dashboard/tree/main

Ask JGI Student Experience Profiles: Rachael Laidlaw

Posted on by kerry.turcsi

Rachael Laidlaw (Ask-JGI Data Science Support 2023-24) 

I first came into contact with the Jean Golding Institute last year at The Alan Turing Institute’s annual AI UK conference in London, and then again in the early stages of the DataFace project in collaboration with Cheltenham Science Festival. This meant that before I officially joined the team back in October, I already knew what a lovely group of people I’d be getting involved with! Having nice colleagues, however, was not my only motivation for applying to be an Ask-JGI student. On top of that, I’d decided that whilst starting out in my ecological computer-vision PhD niche, I didn’t want to forget all of the statistical skills that I’d developed back in my MSc degree. Plus, it sounded really fun to keep myself on my toes by exercising my mind tackling a variety of data-oriented requests from across the university’s many departments. 

Rachael Laidlaw in centre with two JGI staff members to the left and one JGI staff member to the right pointing towards a Data pin board at the JGI stall
Rachael Laidlaw (centre), second-year PhD student in Interactive Artificial Intelligence, and other JGI staff members at the JGI stall

During the course of my academic life, I’ve taken the plunge of changing disciplines twice, moving from pure mathematics to applied statistics and then again to computer science, and I liked the idea of supporting others to potentially do the same thing as they looked to enhance their work by delving into data. Through Ask-JGI, I kept my weeks interesting by having something other than my own research to sometimes switch my focus to, and it felt very fulfilling to be able to offer useful technical advice to those who were in the same position that I myself had been in not so long ago too! I therefore got stuck in with anything and everything, from training CNNs for rainfall forecasting or performing statistical tests to compare the antibiotic resistance of different bacteria, to modelling the outcomes of university spinouts or advising on the ethical considerations and potential bias present when designing and deploying a questionnaire-based study. And, of course, by exposing myself to these problems (alongside additional outreach initiatives and showcase events), I also learned a lot along the way, both from my own exploration and from the rest of the team’s insights. 

One especially exciting query revolved around automating the process of identifying from images which particular underground printing presses had been used to produce various historical political pamphlets, based on imperfections in the script. This piqued my interest immediately as it drew parallels with my PhD project, highlighting the copious amount of uses of computer vision and how it can save us time by speeding up traditionally manual processes: from the monitoring of animal biodiversity to carrying out detective work on old written records. 

All in all, this year has broadened my horizons by giving me great consultancy-style work experience through the opportunity to share my expertise and help a wide range of researchers. I would absolutely encourage other curious PhD students to apply and see what they can both give to and gain from the role! 

Ask JGI Student Experience Profiles: Mike Nsubuga

Posted on by kerry.turcsi

Mike Nsubuga (Ask-JGI Data Science Support 2023-24) 

Embarking on a New Path 

Mike Nsubuga
Mike Nsubuga, first year PhD Student in Computational Biology and Bioinformatics

In the early days at Bristol, even before I began my PhD, I stumbled upon something extraordinary. AskJGI, a university initiative that provides data science support to researchers from all disciplines, caught my attention through a recruitment advert circulated by my PhD supervisor for support data scientists.

My journey started with hesitation. As a brand-new PhD student, who had just relocated to the UK, I questioned whether I was ready or suitable for such a role. Despite my reservations, my supervisor saw potential in me and encouraged me to seize this opportunity. Yielding to their encouragement, I applied, not fully realizing then how this decision would profoundly shape both my academic and professional paths. 

A World of Opportunities 

Joining AskJGI opened a door to a dynamic world brimming with ideas and innovations. My background in bioinformatics and computational biology meant that working on biomedical queries was particularly rewarding. These projects varied from analyzing protein expression data to studying infectious diseases, allowing me to use data science in meaningful ways. 

Among the initiatives I was involved in was developing models to predict protein production efficiency in cells from their genetic sequences. Our goal was clear yet impactful: to identify patterns in genetic sequences that indicate protein production efficiency. We employed advanced data analysis and machine learning techniques to achieve effective predictions. 

Additionally, I contributed to a project analyzing the severity of dengue infections by using statistical models to identify key biological markers. We pinpointed certain markers as critical for distinguishing between mild and severe cases of the infection. 

These projects showcased the transformative power of data science in understanding and potentially managing diseases, directly impacting public health strategies. 

Making Science Accessible: Community Engagement at City Hall

A highlight of my tenure with AskJGI was participating in Data Science Week at bustling Bristol City Hall. The event was not merely a showcase of data science but an opportunity to demystify complex concepts for the public. Engaging in lively discussions and simplifying intricate algorithms for curious visitors was incredibly fulfilling, especially seeing their excitement as they understood the concepts that are often discussed in our professional circles. 

Audience sitting in City Hall. Some audience members are raising there hand. There is a projector and a speaker at the front of the hall
AI and the Future of Society event as part of Bristol Data Week 2024

Fostering Connections and Gaining Insights 

AskJGI enhanced my technical skills and broadened my understanding of the academic landscape at the University of Bristol. The connections I forged were invaluable, sparking collaborations that would have been unthinkable in the more isolated environment of my earlier academic career. Reflecting on my transformative journey with AskJGI, I am convinced more than ever of the importance of interdisciplinary collaboration and the critical role of data science in tackling complex challenges. I encourage any researcher at the University of Bristol who is uncertain about their next step to explore what AskJGI has to offer. For PhD students looking to get involved, it represents not just a learning opportunity but a chance to make a significant societal impact. 

24/25 Ask-JGI Application

Ask JGI Student Experience Profiles: Emma Hazelwood

Posted on by kerry.turcsi

Emma Hazelwood (Ask-JGI Data Science Support 2023-24) 

Emma Hazelwood
Emma Hazelwood, final year PhD Student in Population Health Sciences

I am a final year PhD student in Population Health Sciences. I found out about the opportunity to support the JGI’s data science helpdesk through a friend who had done this job previously. I thought it sounded like a great way to do something a bit different, especially on those days when you need a bit of a break from your PhD topic.

I’ve learnt so many new skills from working within the JGI. The team are very friendly, and everyone is learning from each other. It’s also been very beneficial for me to learn some new skills, for instance Python, when considering what I want to do after my PhD. I’ve been able to see how the statistical methods that I know from my biomedical background be used in completely different contexts, which has really changed the way I think about data. 

I’ve worked on a range of topics through JGI, which have all been as interesting as they have been different. I’ve helped people with coding issues, thought about new ways to visualise data, and discussed what statistical methods would be most suitable for answering research questions. In particular, I’ve loved getting involved with a project in the Latin American studies department, where I’ve been mapping key locations from conferences throughout the early 20th century onto satellite images, bringing to life the routes that the conference attendees would have taken. 

This has been a great opportunity working with a very welcoming team, and one I’d recommend to anyone considering it!

Ask JGI Student Experience Profiles: Emilio Romero

Posted on by kerry.turcsi

Emilio Romero (Ask-JGI Data Science Support 2023-24)

Emilio Romero
Emilio Romero, 2nd year PhD Student in Translational Health Sciences

Over the past year, my experience helping with the Ask-JGI service has been really rewarding. I was keen to apply as I wanted to get more exposure to the research world in Bristol, meet different researchers and explore with them different ways of working and approaching data.  

From a technical perspective, I had the opportunity to work on projects related to psychometric data, biological matrices, proteins, chemometrics and mapping. I also worked mainly with R and in some cases SPSS, which offered different alternatives for data analysis and presentation. 

One of the most challenging projects was working with chemometric concentrations of different residues of chemical compounds extracted from vessels used in human settlements in the past. This challenge allowed me to talk to specialists in the field and to work in a multidisciplinary way in developing data matrices, extracting coordinates and creating maps in R. The most rewarding part was being able to use a colour scale to represent the variation in concentration of specific compounds across settlements. This was undoubtedly a great experience and a technique that I had never had the opportunity to practice. 

ASK-JGI also promoted many events, especially Bristol Data Week, which allowed many interested people to attend courses at different levels specialising in the use of data analysis software such as Python and R. 

The Ask-JGI team have made this year an enjoyable experience. As a cohort, we have come together to provide interdisciplinary advice to support various projects. I would highly recommend anyone with an interest in data science and statistics to apply. It is an incredible opportunity for development and networking and allows you to immerse yourself in the wider Bristol community, as well as learning new techniques that you can use during your time at the University of Bristol.