I am seeking to reimagine speculative models of internet of things (IoT) devices for the advancement of my academic field of interest, digital sociology; my corporate partner, Nestlé; and Horizon, academia and wider society, developing acceptable technical and ethical frameworks surrounding the utilisation of personal data in the process. The objective is to transition from traditional social and market-research orientated, data-driven methodologies that describe, model and make a prediction on social behaviour – namely consumption - toward data-eliciting capabilities purposefully built into consumer interactions. The goal for all stakeholders in this regard is a demonstrable increase in the ‘value’ of the proposal; whether product, service or consumer/producer experience.
I envisage 3 distinct and fully-formed deliverables or ‘products’ by September 2022, each of which will contribute to one or more of the core research themes of ‘my life in data’; these being ‘people and society’; ‘enabling technologies’ and ‘global impact’. These are a working prototype for the delivering of coffee product or service enabling the elicitation of user data; ‘intellectual property’ in terms of a novel and gap-filling contribution to both digital sociology and consumer research applications; and the thesis, recounting the journey from literature, theory and hypothesis testing; to methodology, findings ethical and practical implications built upon during the process. I aim to contribute to innovation in personal data usage, ideation and prototyping in the commercial space, and novelty and acceptability of methodology in digital social research and sociology.
Consumer value propositions have been identified by my research team and I, as common to all stakeholders in this process. Theory building and speculative design will centre on new and innovative means of discovering ‘value’ in consumer experiences. Value is sociologically interesting as it is not easily quantified (beyond financial qualities for example) or knowable beyond the individual, and thus demands more comprehensive investigation from multiple standpoints. Responding to contemporary thought in quantitative sociology surrounding the disciplines’ scope in the face of ‘Big Data’ approaches  I will pursue a methodology that attends to describing, explaining and predicting phenomena starting with established ‘multilevel’ analyses . Inspired by colleagues in the School of Computer Science, I am also exploring the integration of ‘fuzzy measures’  into predictive models in an attempt to understand variables traditionally classed as inherently qualitative in nature. Popular literature cautions against the use of personal data in an age of increased ‘surveillance capitalism’ , and balancing this with multidisciplinary academic practices stemming from development of the ‘cultural’ and ‘technical’ probe  will be a key methodological and ethical consideration throughout this project.
 Boucher, A and Gaver, W (2017) Designing and Making the Datacatchers: Batch Producing Location-Aware Mobile Devices, in Proceedings of the Eleventh International Conference on Tangible, Embodied, Imbeded Interaction
 Burrows, R and Savage, M (2014) After the Crisis? Big Data and the methodological challenges of empirical sociology, in Big Data and Society, April-June 2014: 1-6, Sage
 Neilson, L.A; Paxton, P (2010) Social Capital and Political Consumerism: A Multilevel Analysis, in Social Problems, 57(1) pp. 5-24
 O’Hara, K and Shadbolt, N (2008) The Spy in the Coffee Machine: The end of privacy as we know it, Oneworld Publications
 Wagner, C; Havens, T.C; Anderson, D.T 2017) The arithmetic recursive average as an instance of the recursive weighted power mean, IEEE International Conference on Fuzzy Systems
 Zuboff, S (2019) The Age of Surveillance Capitalism: The fight for a human future at the new frontier of power, Profile Books
This author is supported by the Horizon Centre for Doctoral Training at the University of Nottingham (RCUK Grant No. EP/L015463/1) and Nestlé.