Bringing together colleagues from the School of Health & Medical Sciences and School of Science & Technology, it explored how visualization tools have the potential to transform our interpretation and communication of medical data.
On Monday 16 June, colleagues from the School of Health & Medical Sciences and the School of Science & Technology participated in a novel ‘hackathon’ workshop together.
It was convened to foster collaborative problem solving between the two groups in order to engineer health data visualization solutions that fuse their respective expertise.
The event was organised and headed by members of both Schools; Professor Professor Stephanie Wilson, Dr Abi Roper, Professor Steve Gillard, Professor Madeline Cruice, Professor Jo Wood, Dr Mai Elshehaly and Dr Tracey Booth.
What is data visualization and why is it important?
Data visualization is the analysis and translation of complex information into visual content through graphics, such as maps, graphs or charts. The visual representations make the data more intelligible by using colours, shapes and fonts, which ultimately makes it easier to identify outliers or trends within the data.
Data visualization is particularly valuable in health research as it allows for depictions of information that healthcare professionals and patients can understand in simple terms. Within medical organisations, it can enhance patient care and research quality.
Hackathon highlights
The hackathon
In the workshop, participants assessed real-world health data sets, such as ones looking at the impacts of air quality on the lives and health of young people and aphasia (language problems after stroke) intervention, with the data taking both quantitative and qualitative forms.
- Quantitative data is data that is described with numbers and measurement
- Qualitative data is data which is described with words and interpreting opinions and experiences
Groups identified goals for visualizing the data (“wishful thinking”), then sketched possible visualizations (“vis prototyping”) and lastly crafted a narrative out of their insights (“storytelling”). Each approach aimed to make data more engaging for professionals and the public.
Participants reflected on the need to take time with reading data, noting a tension with the need to find quick solutions. They agreed that complex data visualization is split into two processes; the visualization itself and then relaying an explanation to the audience so that they can effectively understand it.
Dr. Roper, a Speech and Language technologist, shared:
Dr. Mai Elshehaly, Lecturer in Computer Science, further explained that in order to make sense of visualized data, we must first learn how to read visual marks and patterns. Interactive group activities, led by lecturer in Human-Computer Interaction, Dr Tracey Booth, stimulated discussions and ideas on this.
On the event’s successes and prospects, Dr Roper added:
Funding
'Enhancing Research Culture' funding from City St George's, University of London
Byline: this article was written by Andrea Costache, Communications Assistant, City St George's, University of London Press Office