The SODA Project explores data mobilities through multiparty computing.
Medical data from portable personal digital devices (e.g. fitbits, insulin pumps) may usefully converge with clinical data to form Biomedical Big Data, yielding new insight through machine learning and algorithmic categorization. In the process, it might be repurposed to great effect to inform medical research, shaping futures of care systems. However, medical data mobilities are currently regulated by legislation that can block data mobilities and require data controllers to spend significant time (weeks) before information can be shared. Difficulties can also arise, because the “benefits” of data sharing may not directly impact the data subject but promise better healthcare for future generations. In response, the EU-funded SODA project is exploring Multiparty Computing (MPC) to offer ‘real time’ access and ‘live’ data comparison, by making data available for encrypted processing.
Lancaster contributes with a series of workshops that focus on co-designing data with practitioners in living with and caring for people with chronic diseases, especially dementia, as well as practitioners in data analytics in relation to chronic diseases. The SODA team at Lancaster understands medical data as mobile practices which, far from neutral, are situated and subjected to gender, class, race, personal history and contextual politics.
In our workshops, we employ a cross-disciplinary co-design approach to explore spaces and knowledges that emerge from realizing data mobilities together with people affected by diseases (e.g. dementia, diabetes), caregivers, healthcare organisations, health and medical professionals and academic researchers. Co-designing medical data mobilities with subjects has the potential to be transformative as participants become co-owners of innovation.
The approach to ‘ethics through design’ that we have developed explores utopia and dystopia of MPC and ‘mobilises’ existing approaches, such as Value Sensitive Design, disclosive ethics, ethical impact assessment, and responsible research and innovation to design ways of mobilizing data in radically careful and carefully radical ways.
