‘Social change through innovation’ Open Call
DDI ‘Social change through innovation’ Open Call Funding
The DDI Small Grants call has funded ten projects focusing on using data driven innovation to tackle ‘social change through innovation’. Projects range from using augmented reality to help animal conservation to understanding air quality using bike-mounted sensors.
Projects’ total value: £191,252
Improving wildlife conservation through immersive technology: the use of virtual reality
Principal Investigator: Kirsten Cowan
Award Value: £25,722
The project sought to understand how virtual reality (VR) can help people understand more about wildlife conservation. Based on conversations with with Edinburgh zoo and in collaboration with the Liege Aquarium Museum in Belgium, a VR game was created, providing information about why specific sharks are not kept in aquariums and how individual actions can help conserve marine wildlife.
Results suggest that VR games about wildlife can inspire people to think and behave differently. Individuals suggested that connecting their own actions to effects on nature would have a strong influence on their long-term takeaways from the game. Likewise, because individuals felt close to nature, they felt more responsible for conservation.
Two VR experiments examined the influence of wildlife proximity. In one version, the sharks swam close to participants, while in the other, they swam further away. When the sharks were close, participants reported a higher likelihood of donating to shark conservation, even when they felt low attachment to the sponsoring source (e.g. local zoo). Interestingly, fear of sharks and perceived individual power also influenced the relationship between the VR game and willingness to donate. Individuals who feared sharks were more likely to donate following the game where sharks were closer. Likewise, individuals who felt more powerless, were more likely to donate to marine conservation when sharks were closer versus further away.
The VR game will be used by the Aquarium-Museum to share the rationale for changing their shark exhibit, increase and educate visitors.
Addressing measurement error in dietary intake assessment
Principal Investigator: Amelia Finaret
Award Value: £8,700
Dietary patterns are a major determinant of health, beginning in childhood, with poor-quality diets increasing the risk of cardiovascular disease, diabetes, and cancer. However, measuring diets is challenging and requires incorporating statistics – especially for vulnerable children.
A Research Coordinator for the Electronic Data Research and Innovation Service (eDRIS) helped the project team use Community Health Index (CHI) data to secure participants and estimate the dietary intake of children aged 2 – 15 years of age. For data collection and analysis, the team set up a website, updated its sampling strategy and completed a pilot data collection. After analysis and reporting of findings, the resulting dataset will be used as a resource for future projects.
The team completed a draft course proposal for a CPD course, Nutrition Statistics, which will be available online. Lecture materials are ready for the final version of the course, which is aimed at professionals, clinicians, and researchers studying nutrition and dietary intake.
Outputs so far are websites to outline the study to potential participants, including its privacy notice, and a lecture slide deck, Introduction to estimating usual dietary intake, which describes current dietary assessment methods, defines key terms, explores challenges to estimating usual intake, and introduces the NCI method and the SIMPLE Macro.
UniCycle sensor platform
Principal Investigator: Simon Chapple
Award Value: £9,999
This project modified an electric bike to carry GPS and Ambient Air Quality (AQM) sensor devices powered by the onboard battery and reporting readings in real-time via a LoRaWAN-based radio network. Key participants were the University of Edinburgh Internet of Things (IoT) service to create the sensor for attachment to the bike, and Sensational Systems, a local Edinburgh specialist IoT company to provide suitable DC powering from the bike battery to the onboard sensor package.
Initial trials of the AQM sensor demonstrated a need to change the design of the packaging to incorporate indirect airflow through the particulates sensor to protect it from rain and road splash – the resultant design redirects airflow to the back of the unit where the sensor is mounted. The final version of the AQM sensor-equipped bike was ridden through streets in Edinburgh City centre on several occasions, delivering combined GPS location and particulate PM1, 2.5, 10 sensor readings in real-time.
The research team aims to complete the particulate mapping of central Edinburgh by bike and, in particular, the region for the extended low emission zone, which comes into full force in June 2024. They will analyse data on current Edinburgh street level hot spots for particulate pollution, and seek additional funding for more AQM sensors based on the working prototype, which would enable a live map of particulate pollution across central Edinburgh.
Push-pull energy futures: supporting discussions on data-driven models for local energy storage, distribution and consumption
Principal Investigator: Larissa Pschetz
Award Value: £9,643
The application and expansion of renewable energy depends on technologies to smooth out peaks and troughs of supply. Researchers developed the Karma Kettle game as a playful way to discuss potential scenarios of distributed energy that rely on networked batteries and algorithmic transactions. The connected kettles allow individuals to visualise a local grid and give them the option to use, store, or push energy back to the grid, receiving or losing karma points based on whether their actions contribute to balancing the grid.
High availability in the grid and low regional storage would give a positive score for those who store energy. Low availability would give a higher score for those who push it back into the grid, etc. The points fluctuate according to each player’s profile, which is defined based on the UK Census for energy consumption. This proportionally lowers the reward values and increases the cost values of positive and negative actions to profiles with higher energy consumption patterns, and vice versa. This illustrates an instance of potential systemic biases originated from algorithmic profiling.
The amount of energy in the grid and local storage changes constantly within a 24-hour scenario. At each interval, participants pick a context card and decide which action to take. The player or group of players with the highest karma score wins. The game was trialled at the British Science Week in March 2023, and subsequently developed into a stand-alone and portable installation. Watch the explainer video.
Building community evidence for urban parklets in Edinburgh
Principal Investigator: Simon Bell
Award Value: £9,898
Parklets are small, temporary structures typically built on one or two kerb-side parking spaces to add a community space to streets otherwise lacking this. Though these programmes exist in other cities, there is no precedent for parklets in Edinburgh. This research aimed to identify local interest in parklets to help build the case for whether future support should be considered by the Council.
Research was undertaken primarily through a questionnaire distributed city-wide for a six-week period. 787 valid results were analysed both statistically and spatially. There was a clear split in support, around half of respondents (58%) were in favour of parklets and 42% against them. There was a statistically significant correlation for people under the age of 45 years and non-car owning, being in support of parklets. Conversely, older, car-owning respondents who felt a strong sense of community were not in favour. In particular, there was a spatial pattern where appetite for parklets was focused more in certain districts, such as in Morningside, Leith Walk and Southside/Newington wards.
However, there were also districts with low numbers of respondents where the evidence base is less clear. Respondents in favour of parklets also suggested specific streets where they would like to see them. Therefore, while there were some limitations in reaching people across all parts of the city, the research provides sufficient and robust evidence to recommend that the Council further investigate the deliverability of this initiative in specific locations.
Data-driven innovation for Chronic Obstructive Pulmonary Disease (COPD)
Principal Investigator: Tim Walsh
Award Value: £50,000
The work between Lenus Health, Dataloch, and NHS Lothian aims to risk stratify patients with Chronic Obstructive Pulmonary Disease (COPD). Initially, work focused on data exploration and processing, looking at routine data from Lothian patients accessed through ‘Dataloch’, an NHS Lothian and University of Edinburgh collaborative service. These data come from primary (GPs) and secondary care (hospital-based) settings, including datasets containing demographics, prescriptions, lab results, admissions, and comorbidities. These data were made available within a single secure ‘space’ within DataLoch, called a Trusted Research Environment (TRE).
Data scientists within Lenus Health compared data provided with their accompanying data dictionaries and reported any differences. The data was then transformed such that it could be used with the bespoke processing scripts Lenus Health had developed specific to preparing COPD healthcare data. Lenus Health’s model suite was re-trained using the transformed Lothian data. Lenus Health’s models included: 12-month mortality prediction; 3-month readmission prediction; and COPD cohort risk stratification.
Once these models have been re-trained, bespoke features derived from Lothian data will be introduced. The aim is to include data such as spirometry, BMI and smoking status. The hope is that model performance would improve as a result. Additional new models will also be explored, for example, an admission prediction model. Ultimately, models like these will support clinical decision-making to improve care quality, reduce health inequalities, and contribute to better health outcomes for patients living with COPD.
VisActivities: an open online platform for collecting, browsing, and discussing activities for visualisation, empowerment and data literacy
Principal Investigator: Uta Hinrichs
Award Value: £9,870
Researchers designed a platform to capture, characterize, and share experiences of visualization activities, with the aim of increasing data literacy, and making data visualization more accessible and empowering. Data visualization is becoming more important for a data-literate, informed, and critical society, and the range of visualization tools is growing.
Visualization activities (e.g., sketching visual representations of personal data using pen and paper, or visualizing a data set using a particular visualization tool) play a vital role in learning how to think about data-related problems and using visualization tools in an informed and critical way. Although there is vast knowledge on how to teach visualization in an engaging way, this is not systematically captured and is often only shared informally or across blog posts, research articles, or book chapters.
This project’s VisActivities Platform allows users to browse data visualization activities from different perspectives. It characterizes existing visualization activities based on type, focus, and pedagogical goals, as well as the context in which the activity can be conducted, the types of materials or tools involved, the number of participants, as well as duration. DDI funding enabled the design and implementation of the prototype front- and backend of the platform. In collaboration with the Edinburgh Futures Institute and its visualization engineer, researchers will refine the platform and populate it with additional activities. Once the beta version is ready, the project team will advertise the platform, and integrate and test selected activities.
FND research platform
Principal Investigator: Jon Stone
Award Value: £12,100
Researchers aim to create a global digital research platform for Functional Neurological Disorder (FND) that creates better outcomes for patients. The DDI small grant enabled researchers to build a secure patient database attached to an existing digital platform, neurosymptoms.org.
FND is a common but hidden and stigmatised cause of disability in which people, typically in their 20s-40s develop symptoms like paralysis, tremor or seizures. There are approximately 100,000 people living with FND in the UK, with around 2,000 in Edinburgh and SE Scotland. Historically, FND was referred to as ‘hysteria’ and was ignored as ‘psychosomatic’. Knowledge among health professionals is often low. Patients face long waits for treatment, and there are still no individualised self-help online resources.
In 2022, the research team made the ‘FND formulator’ to improve patient-professional communication and mutual understanding of symptoms, causes and readiness for treatment. This is an innovative way for patients and clinicians to ‘co-formulate’ to reach a shared understanding of their nature, causes and potential treatment.
DDI funding allowed researchers for the first time to build a secure database for the neurosymptoms platform, enabling FND patients and their carers to make an account and track symptom / formulation reports.
FND patients visiting the site will have the option to consent to their data being used in research. The team plans to develop more individualised ways to deliver educational material for people with FND, enhancing the research potential of the platform.
Earth data hub – regional particulate matter sensor network
Principal Investigator: Patrick Kilduff
Award Value: £44,040
In 2013 Ella Roberta became the first person to have air pollution listed as a cause of death in their death registration. By 2019, global estimates expect 4,200,000 premature deaths resulting from poor outdoor air quality. Tackling this is a priority for the Scottish Government and the City of Edinburgh Council, who have instigated a Low Emission Zone, coming into force in June 2024.
Particulate matter (PM) is a major air pollutant contributing to multiple harmful effects on human health and the environment. This project describes a network of Internet of Things (IoT) PM sensor measurements forming the basis of a dense, low-cost air pollution network. The aim is to establish the quality of the sensors, so the eventual network delivers useful information. Analysis showed the sensors performed as expected, with the majority showing a high correlation with each other, thereby providing some confidence in the technology.
There was better agreement between sensors for PM1 (< 1 micron in diameter) and PM2.5 than PM10 (<10 micron in diameter), which is in agreement with similar studies. Longer-term validation of the low-cost sensor data is ongoing. When sufficient data are collected, the team will develop correction algorithms, if necessary, to account for any discrepancy between sensors. The project team has developed a network of site locations that will ensure the data collected will be valuable for studying air pollution across the city and help deliver policy-relevant information.
Collaborative Edinburgh festivals data: open audience insights from the Edinburgh Festival Fringe
Principal Investigator: Vikki Jones
Award Value: £11,280
This project addressed the challenge of making data about ticket-buying audiences open and accessible, democratising access to data for Fringe artists. The map was designed and delivered in partnership with the Edinburgh Festival Fringe Society. Existing datasets from other Edinburgh Culture and Communities Mapping research were tailored to this version of the map. Data for Fringe audiences from 2021 and 2022 were added.
The map’s core features included a scale for areas of high and low ticket buying; adding venues; documenting annual changes of ticket buyers in a postcode area. The draft version was tested with the Edinburgh Festival Fringe Society team, allowing researchers to present the map’s features and understand how they were communicating the data. Final changes were incorporated based on the comments from the workshop.
Such tools could allow artists, producers, and audiences to make decisions about how to manage their Fringe experience – from finding venues, to areas to promote shows, to areas which might offer new experiences outside of high footfall areas. Representations of annual change in ticket-buying offer insight into where promotion in certain postcode areas might have been successful in growing audiences. The project team hopes to develop more dynamic visualisations, including annual movement of Fringe venues; ways to map journeys; and mapping ticket-buying according to performance genres. Read the project blog.