Living Digital Data research program

People’s encounters and entanglements with the personal digital data that they generate is a new and compelling area of research interest in this age of the ascendancy of digital data. Members of the public are now called upon to engage with a variety of forms of information about themselves and to confront the complexities of how these details are used by others. Personal digital data assemblages are configured as human bodies, digital devices, code, data, time and space come together.


Personal digital data assemblages smartart

Personal digital data assemblages


Over the past few years I have been researching the social aspects of personal digital data: how people understand and conceptualise these data, how they use their data, what people know about where their personal data go and how their data are used by second and third parties.I have analysed the metaphors that are used to describe digital data, the politics of digital data, the types of data that are collected by apps and self-tracking devices, how people use these software and devices and how personal digital data are materialised, or rendered into visualisations or three-dimensional objects. I have sought to theorise the ontology of personal digital data, drawing particularly sociomaterialism, feminist technoscience, cultural geography and sensory studies. (See My Recent Publications for further details.)

I am bringing these research questions together under a program that I have named ‘Living Digital Data’. This title builds on my conceptualisation of digital data as ‘lively’ in a number of ways.



Lively data smartart

Lively Data



The first element of the vitality of digital data relates to the ways in which they are generated and what happens thereafter. The personal digital information that is constantly generated contributes to data assemblages that are heterogeneous and dynamic, their character changing as more data points are added and others removed. Digital data may be described as having their own social lives as they circulate in the digital data economy and are purposed and repurposed. Second, digital data constitute forms of knowledge about human (and nonhuman) life itself and hence possess another type of vitality. Third, personal digital data have impacts on people’s lives, shaping the decisions and actions that people make and those that other people make about them.  The profiles constructed from these data can influence decisions about the opportunities people have to travel, access employment, credit or insurance, the people that they meet on online dating sites, the knowledges that they hold about themselves and their bodies and those of intimate others. Finally, personal digital data are forms of livelihoods, contributing to the commodification and capitalisation of information. Indeed, they may be described as a form of biocapital, which possesses many forms of value beyond the personal: for research, commercial, security, managerial and governmental agencies.

This approach recognises the entanglements of personal digital data assemblages with human action. Not only are personal digital data assemblages partly comprised of information about human action, but their materialisations are also the products of human action, and these materialisations can influence future human action.

Rather than refer to data literacy or data management skills, I take up the term ‘data sense’ to encapsulate a broader meaning of ‘data sense’ that includes human senses (sight, sound, touch, smell and taste) and how these are part of people’s responses to data and also acknowledges the role played by digital sensors in the act of ‘sense-making’; or coming to terms with digital data.


Data sense smartart

Data Sense


Interesting HCI research on self-tracking: a reading list

In a recent blog post, I published a reading list of critical social research into self-tracking. And in another recent post, I discussed what I saw as the intersections of digital sociology and human-computer interaction (HCI) research. I argued that researchers in each approach should pay attention to what the others are doing, as there are many shared interests.

In this post, I present a reading list of what I (as sociologist) have chosen to designate as ‘interesting’ HCI research on the same phenomenon. This is based on what I consider ‘interesting’ – studies that go beyond design or technical features of self-tracking technologies to address how people use them and incorporate the data into their everyday lives.

There is a wealth of HCI research on self-tracking. HCI researchers have published earlier and more often on self-tracking compared to sociologists and other social researchers. This is largely due to their publishing conventions, in which peer-reviewed conference papers have the status of journal articles, and allow people to publish their research much more quickly. Probably because they are located within the world of digital technology design, HCI researchers devoted their attention much earlier than social scientists to what was initially (and sometimes still) called ‘lifelogging’ and how digital devices were used by practitioners.

Some of the research below takes an explicitly critical or reflective approach to self-tracking – although I have found that this is quite rare in HCI, where the ‘persuasive computing’ approach dominates in research on this topic. A few articles report on speculative design approaches or ways of materialising data that are innovative. Others simply offer some interesting material on how and why people are engaging in self-tracking.

Barrass S. (2016) Diagnosing blood pressure with Acoustic Sonification singing bowls. International Journal of Human-Computer Studies 85: 68-71.

Choe EK, Lee NB, Lee B, Pratt W and Kientz JA. (2014) Understanding quantified-selfers’ practices in collecting and exploring personal data. Proceedings of the 32nd Annual ACM Conference on Human Factors in Computing Systems (CHI ’14). Toronto: ACM Press, 1143-1152.

Choe EK, Lee NB and Schraefel M. (2015) Revealing visualization insights from Quantified-Selfers’ personal data presentations. Computer Graphics and Applications 35: 28-37.

Cuttone A, Petersen MK and Larsen JE. (2014) Four data visualization heuristics to facilitate reflection in personal informatics. Universal Access in Human-Computer Interaction. Design for All and Accessibility Practice. Heraklion: Springer, 541-552.

Doherty AR, Caprani N, Conaire CÓ, Kalnikaite V, Gurrin C, Smeaton AF and O’Connor NE. (2011) Passively recognising human activities through lifelogging. Computers in Human Behavior 27: 1948-1958.

Doherty AR, Pauly-Takacs K, Caprani N, Gurrin C, Moulin CJA, O’Connor NE and Smeaton AF. (2012) Experiences of aiding autobiographical memory using the SenseCam. Human–Computer Interaction 27: 151-174.

Elsden C, Kirk D, Selby M and Speed C. (2015) Beyond personal informatics: designing for experiences with data. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing System (CHI ’15). Seoul: ACM Press, 2341-2344.

Elsden C, Kirk DS and Durrant AC. (2015) A quantified past: toward design for remembering with personal informatics. Human–Computer Interaction online first: 1-40.

Epstein D, Cordeiro F, Bales E, Fogarty J and Munson S. (2014) Taming data complexity in lifelogs: exploring visual cuts of personal informatics data. Proceedings of the 2014 Conference on Designing Interactive Systems (DIS ’14). Vancouver: ACM Press, 667-676.

Epstein DA, Ping A, Fogarty J and Munson SA. (2015) A lived informatics model of personal informatics. Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp ’15). Osaka: ACM Press, 731-742.

Fan C, Forlizzi J and Dey A. (2012) A spark of activity: exploring informative art as visualization for physical activity. Proceedings of the 2012 ACM Conference on Ubiquitous Computing (Ubicomp ’12). Pittsburgh: ACM Press, 81-84.

Gaver WW, Bowers J, Boehner K, Boucher A, Cameron DWT, Hauenstein M, Jarvis N and Pennington S. (2013) Indoor weather stations: investigating a ludic approach to environmental HCI through batch prototyping. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’13). Paris: ACM Press, 3451-3460.

Grönvall E and Verdezoto N. (2013) Beyond self-monitoring: Understanding non-functional aspects of home-based healthcare technology. Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp ’13). Zurich: ACM Press, 587-596.

Hoyle R, Templeman R, Anthony D, Crandall D and Kapadia A. (2015) Sensitive lifelogs: a privacy analysis of photos from wearable cameras. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI’ 15). ACM Press, 1645-1648.

Huang D, Tory M, Aseniero BA, Bartram L, Bateman S, Carpendale S, Tang A and Woodbury R. (2015) Personal visualization and personal visual analytics. Visualization and Computer Graphics 21: 420-433.

Kalnikaite V, Sellen A, Whittaker S and Kirk D. (2010) Now let me see where I was: understanding how lifelogs mediate memory. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’10). Atlanta: ACM Press, 2045-2054.

Khot R, Hjorth L and Mueller FF. (2014) Understanding physical activity through 3D printed material artifacts. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’14). Toronto: ACM Press, 3835-3844.

Khot R, Lee J, Munz H, Aggarwal D and Mueller F. (2014) Tastybeats: making mocktails with heartbeats. Designing Interactive Futures. Vancouver: ACM Press, 467-470.

Khot RA, Pennings R and Mueller FF. (2015) EdiPulse: supporting physical activity with chocolate printed messages. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’15). Seoul: ACM Press, 1391-1396.

Khovanskaya V, Baumer EP, Cosley D, Voida S and Gay G. (2013) Everybody knows what you’re doing: a critical design approach to personal informatics. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’13). Paris: ACM Press, 3403-3412.

Lawson S, Kirman B, Linehan C, Feltwell T and Hopkins L. (2015) Problematising upstream technology through speculative design: the case of quantified cats and dogs. Proceedings of the SIGCHI Conference on Human Factors in Computer Systems (CHI ’15). ACM Press, 2663-2672.

Lazar A, Koehler C, Tanenbaum J and Nguyen DH. (2015) Why we use and abandon smart devices. Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp ’15). Osaka: ACM Press, 635-646.

Lee M-H, Cha S and Nam T-J. (2015) Patina engraver: visualizing activity logs as patina in fashionable trackers. Proceedings of the SIGCHI Conference on Human Factors in Computing System (CHI ’15). Seoul: ACM Press, 1173-1182.

Li I, Dey AK and Forlizzi J. (2011) Understanding my data, myself: supporting self-reflection with ubicomp technologies. Proceedings of the International Conference on Ubiquitous Computing (Ubicomp ’11). Beijing: ACM, 405-414.

Liu W, Ploderer B and Hoang T. (2015) In bed with technology: challenges and opportunities for sleep tracking. Proceedings of the Annual Meeting of the Australian Special Interest Group for Computer Human Interaction (OzCHI ’15). ACM Press, 142-151.

Mathur A, Van den Broeck M, Vanderhulst G, Mashhadi A and Kawsar F. (2015) Tiny habits in the giant enterprise: understanding the dynamics of a quantified workplace. Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp ’15). Osaka: ACM Press, 577-588.

Nissen B and Bowers J. (2015) Data-Things: digital fabrication situated within participatory data translation activities. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI ’15). Seoul: ACM Press, 2467-2476.

Oh J and Lee U. (2015) Exploring UX issues in Quantified Self technologies. Eighth International Conference on Mobile Computing and Ubiquitous Networking. Hakodate, Japan: IEEE, 53-59.

Ploderer B, Smith W, Howard S, Pearce J and Borland R. (2012) Things you don’t want to know about yourself: ambivalence about tracking and sharing personal information for behaviour change. Proceedings of the 24th Australian Computer-Human Interaction Conference (OzCHI ’12). Melbourne: ACM Press, 489-492.

Purpura S, Schwanda V, Williams K, Stubler W and Sengers P. (2011) Fit4life: the design of a persuasive technology promoting healthy behavior and ideal weight. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Vancouver: ACM, 423-432.

Rooksby J, Rost M, Morrison A and Chalmers MC. (2014) Personal tracking as lived informatics. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Toronto: ACM, 1163-1172.

Snow S, Buys L, Roe P and Brereton M. (2013) Curiosity to cupboard: self reported disengagement with energy use feedback over time. Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration. Adelaide: ACM, 245-254.

Stusak S. (2015) Exploring the potential of physical visualizations. Proceedings of the Ninth International Conference on Tangible, Embedded, and Embodied Interaction (TEI ’15). Stanford, CA: ACM Press, 437-440.

Stusak S, Tabard A, Sauka F, Khot RA and Butz A. (2014) Activity sculptures: exploring the impact of physical visualizations on running activity. IEEE Transactions on Visualization and Computer Graphics 20: 2201-2210.

Whooley M, Ploderer B and Gray K. (2014) On the integration of self-tracking data amongst Quantified Self members. Proceedings of the 28th International BCS Human Computer Interaction Conference (HCI ’14). Southport, UK: BCS, 151-160.

Williams K. (2013) The weight of things lost: self-knowledge and personal informatics. Personal Informatics.  <; accessed 12 May 2014.

My new book: The Quantified Self

My new book The Quantified Self: A Sociology of Self-Tracking is due out with Polity Press this April. The publishers are offering a 20% discount for six months (from 18 January 2016 to 31 July 2016) if it is ordered via their website. Please use the code PY703 when you order to receive the discount.

Here is a PDF of the Introduction: Lupton 2016 Introduction to The Quantified Self.

Table of Contents



1          ‘Know Thyself’: Self-tracking Practices and Technologies

2          ‘New Hybrid Beings’: Theoretical Perspectives

3          ‘An Optimal Human Being’: the Body and Self in Self-Tracking Cultures

4          ‘You are Your Data’: Personal Data Meanings, Practices and Materialisations

5          ‘Data’s Capacity for Betrayal’: Personal Data Politics





POLITY-Lupton-Quantified Self Visuals-AUG24-3 (1)


My 2015 publications

Here are my publications that came out in 2015.


  • Lupton, D. (2015) Digital Sociology. London: Routledge.

Book chapters

  • Lupton, D. (2015) Digital sociology. In Germov, J. and Poole, M. (eds), Public Sociology: An Introduction to Australian Society, 3rd St Leonards: Allen & Unwin.
  • Lupton, D. (2015) Donna Haraway: the digital cyborg assemblage and the new digital health technologies. In Collyer, F. (ed), The Palgrave Handbook of Social Theory in Health, Illness and Medicine. Houndmills: Palgrave Macmillan.

Peer-reviewed journal articles


  • Lupton, D. and Pedersen, S. (2015) ‘What is Happening with Your Body and Your Baby’: Australian Women’s Use of Pregnancy and Parenting Apps. Available here.

Critical social research on self-tracking: a reading list

Self-tracking has recently become a new area of fascination for critical social researchers. A body of literature has now been established of research that has sought to investigate the social, cultural and political dimensions of self-tracking, nearly all of which has come out in the last few years. This literature complements an established literature in human-computer interaction research (HCI), first into lifelogging and then into self-tracking (or personal informatics/analytics, as HCI researchers often call it).

I am currently working on an article that is a comprehensive review of both literatures, in the attempt to outline what each can contribute to understanding self-tracking as an ethos and a practice, and its wider sociocultural implications. Here is a reading list of the work from critical social researchers that I am aware of. I will publish a similar list of interesting HCI research in a forthcoming post.

Albrechtslund, A, and P Lauritsen, (2013) Spaces of everyday surveillance: Unfolding an analytical concept of participation, Geoforum, 49: 310-16.

Allen, AL, (2008) Dredging up the past: Lifelogging, memory, and surveillance, The University of Chicago Law Review, 75 (1): 47-74.

Barta, K, and G Neff, (2015) Technologies for sharing: lessons from Quantified Self about the political economy of platforms, Information, Communication & Society, online first.

Bode, M, and DB Kristensen,  (2016) The digital doppelgänger within. In Assembling Consumption: Researching actors, networks and markets, edited by R. Canniford and D. Badje. London: Routledge, pp.

Bossewitch, J, and A Sinnreich, (2013) The end of forgetting: Strategic agency beyond the panopticon, New Media & Society, 15 (2): 224-42.

Copelton, D, (2010) Output that counts: pedometers, sociability and the contested terrain of older adult fitness walking, Sociology of Health & Illness, 32 (2): 304-18.

Crawford, K, J Lingel, and T Karppi, (2015) Our metrics, ourselves: A hundred years of self-tracking from the weight scale to the wrist wearable device, European Journal of Cultural Studies, 18 (4-5): 479-96.

Daly, A, (2015) The law and ethics of ‘self quantified’ health information: an Australian perspective, International Data Privacy Law, online first.

Dodge, M, and R Kitchin, (2007) ‘Outlines of a world coming into existence’: pervasive computing and the ethics of forgetting, Environment and Planning B: Planning & Design, 34 (3): 431-45.

Drew, DL, and JM Gore, (2014) Measuring up? The discursive construction of student subjectivities in the Global Children’s Challenge™, Sport, Education and Society, online first.

Fiore-Gartland, B, and G Neff, (2015) Communication, mediation, and the expectations of data: data valences across health and wellness communities, International Journal of Communication, 9: 1466-84.

Fox, NJ, (2015) Personal health technologies, micropolitics and resistance: a new materialist analysis, Health:, online first.

Gardner, P, and B Jenkins, (2015) Bodily intra-actions with biometric devices, Body & Society, online first.

Gerlitz, C, and C Lury, (2014) Social media and self-evaluating assemblages: on numbers, orderings and values, Distinktion: Scandinavian Journal of Social Theory, 15 (2): 174-88.

Gilmore, JN, (2015) Everywear: The quantified self and wearable fitness technologies, New Media & Society, online first.

Jethani, S, (2015) Mediating the body: Technology, politics and epistemologies of self, Communication, Politics & Culture, 47 (3): 34-43.

Klauser, FR, and A Albrechtslund, (2014) From self-tracking to smart urban infrastructures: towards an interdisciplinary research agenda on Big Data, Surveillance & Society, 12 (2): 273-86.

Lomborg, S, and K Frandsen, (2015) Self-tracking as communication, Information, Communication & Society: 1-13.

Lupton, D, (2012) M-health and health promotion: the digital cyborg and surveillance society, Social Theory & Health, 10 (3): 229-44.

Lupton, D, (2013a) The digitally engaged patient: self-monitoring and self-care in the digital health era, Social Theory & Health, 11 (3): 256-70.

Lupton, D, (2013b) Quantifying the body: monitoring and measuring health in the age of mHealth technologies, Critical Public Health, 23 (4): 393-403.

Lupton, D, (2013c) Understanding the human machine, IEEE Technology & Society Magazine, 32 (4): 25-30.

Lupton, D, (2014a) The commodification of patient opinion: the digital patient experience economy in the age of big data, Sociology of Health & Illness, 36 (6): 856-69.

Lupton, D, (2014b) Self-tracking cultures: towards a sociology of personal informatics. In Proceedings of the 26th Australian Computer-Human Interaction Conference (OzCHI ’14). Sydney: ACM Press.

Lupton, D. (2014c) Self-tracking modes: reflexive self-monitoring and data practices. Social Science Research Network  (accessed 27 August 2014).

Lupton, D. (2014d) You are your data: self-tracking practices and concepts of data. Social Science Research Network  (accessed 12 December 2015).

Lupton, D, (2015a) Data assemblages, sentient schools and digitised health and physical education (response to Gard), Sport, Education and Society, 20 (1): 122-32.

Lupton, D. (2015b) Lively data, social fitness and biovalue: the intersections of health self-tracking and social media. Social Science Research Network  (accessed 13 November 2015).

Lupton, D. (2015c) Personal data practices in the age of lively data. Social Science Research Network  (accessed 15 August 2015).

Lupton, D, (2015d) Quantified sex: a critical analysis of sexual and reproductive self-tracking using apps, Culture, Health & Sexuality, 17 (4): 440-53.

Lupton, D, (2016a) The diverse domains of quantified selves: self-tracking modes and dataveillance, Economy and Society, in press.

Lupton, D, (2016b) The Quantified Self: A Sociology of Self-Tracking Cultures. Cambridge: Polity Press.

Lynch, R, and S Cohn, (2015) In the loop: Practices of self-monitoring from accounts by trial participants, Health:, online first.

Millington, B, (2015) ‘Quantify the Invisible’: notes toward a future of posture, Critical Public Health, online first.

Moore, P, and A Robinson, (2015) The quantified self: What counts in the neoliberal workplace, New Media & Society, online first.

Nafus, D, (2013) The data economy of biosensors. In Sensor Technologies:  Healthcare, Wellness and Environmental Applications, edited by M. McGrath and C. N. Scanaill: Springer.

Nafus, D, (2014) Stuck data, dead data, and disloyal data: the stops and starts in making numbers into social practices, Distinktion: Scandinavian Journal of Social Theory, 15 (2): 208-22.

Nafus, D, and J Sherman, (2014) This one does not go up to 11: the Quantified Self movement as an alternative big data practice, International Journal of Communication, 8: 1785-94.

Neff, G, and D Nafus, (2016) Self-Tracking. Cambridge, MA: The MIT Press.

Niva, M, (2015) Online weight-loss services and a calculative practice of slimming, Health:, online first.

Pantzar, M, and M Ruckenstein, (2015) The heart of everyday analytics: emotional, material and practical extensions in self-tracking market, Consumption Markets & Culture, 18 (1): 92-109.

Reigeluth, TB, (2014) Why data is not enough: digital traces as control of self and self-control, Surveillance & Society, 12 (2): 243-54.

Rettberg, JW, (2014) Seeing Ourselves Through Technology: How We Use Selfies, Blogs and Wearable Devices to See and Shape Ourselves. Basingstoke: Palgrave Macmillan.

Ruckenstein, M, (2014) Visualized and interacted life: personal analytics and engagements with data doubles, Societies, 4 (1): 68-84.

Ruckenstein, M,  (2015) Uncovering everyday rhythms and patterns: food tracking and new forms of visibility and temporality in health care. In Techno-Anthropology in Health Informatics, edited by L. Botin, C. Nohr and P. Bertelsen. Amsterdam: IOS Press, pp. 28-40.

Ruckenstein, M, and M Pantzar, (2015a) Beyond the Quantified Self: thematic exploration of a dataistic paradigm, New Media & Society, online first.

Ruckenstein, M, and M Pantzar, (2015b) Datafied life: techno-anthropology as a site for exploration and experimentation, Techne, 19 (2): 191-210.

Sellen, AJ, and S Whittaker, (2010) Beyond total capture: a constructive critique of lifelogging, Communications of the ACM, 53 (5): 70-77.

Smith, WR, (2015) Communication, sportsmanship, and negotiating ethical conduct on the digital playing field, Communication & Sport, earlyview online.

Stragier, J, T Evens, and P Mechant, (2015) Broadcast yourself: an exploratory study of sharing physical activity on social networking sites, Media International Australia, 155 (1): 120-29.

Thomas, GM, and D Lupton, (2015) Threats and thrills: pregnancy apps, risk and consumption, Health, Risk & Society, online first.

Till, C, (2014) Exercise as labour: Quantified Self and the transformation of exercise into labour, Societies, 4 (3): 446-62.

Van Den Eede, Y,  (2015) Tracing the tracker: a postphenomenological inquiry into self-tracking technologies. In Postphenomenological Investigations: Essays on Human–Technology Relations, edited by R. Rosenberger and P.-P. Verbeek. Lanham, Maryland: Lexington Books, pp. 143-58.

Whitson, J, (2013) Gaming the quantified self, Surveillance & Society, 11 (1/2): 163-76.

Wilkinson, J, C Roberts, and M Mort, (2015) Ovulation monitoring and reproductive heterosex: living the conceptive imperative?, Culture, Health & Sexuality, 17 (4): 454-69.

Williamson, B, (2015) Algorithmic skin: health-tracking technologies, personal analytics and the biopedagogies of digitized health and physical education, Sport, Education and Society, 20 (1): 133-51.

Yang, Y, (2014) Saving the Quantified Self: How we come to know ourselves now, Boom: A Journal of California, 4 (4): 80-87.





Towards a new mode of self-tracking

In a conference paper and my forthcoming book The Quantified Self: A Sociology of Self-Tracking Cultures, I identify five modes of self-tracking. What I call ‘private self-tracking’ is undertaken for voluntary and personal reasons that are self-initiated. ‘Pushed self-tracking’ involves encouragement for people to monitor themselves from other agencies, while the mode of ‘communal self-tracking’ relies on people sharing their personal information with others. ‘Imposed self-tracking’ involves moving from encouragement to requiring people to collect or engage with data about themselves, so that they may have little choice in doing so. The ‘exploited self-tracking’ mode represents the ways in which personal data may be used by other actors and agencies for their own purposes, either overtly or covertly.

Since writing the initial conference paper, developing these ideas in my book and also for a journal article based on the paper, I have added some thoughts about the possibilities for forms of self-tracking that go beyond these modes. As I argue, self-tracking conforms to a conservative political agenda that represents citizens as automated/autonomous subjects, ideally engaging in self-responsibilised practices of monitoring and life optimisation and emitting valuable ‘data exhausts’ for repurposing by other actors and agencies.

As yet, there has been little discussion of the ways in which self-tracking may be used for resistant or strategic political interventions – as means to challenge accepted norms and assumptions about selves and bodies rather than conforming to these norms and assumptions. Few commentators have drawn attention to how self-tracking highlights certain forms of information about specific kinds of individuals or social groups while it neglects or ignores others, and how idealised citizen subjects are configured via dominant self-tracking cultures while those who fail to meet these ideals are stigmatised or disciplined.

Nascent moves towards a more political use of self-tracking are evident in some citizen sensing initiatives, when they are used to expose or challenge assumptions about geographical areas, the social determinants of ill-health, the environment and living conditions in the effort to draw attention towards social inequalities, government neglect or environmental mismanagement.

There is ample further scope for alternative approaches to self-tracking as a form of knowledge production that seek to identify, record and highlight details of socioeconomic disadvantage or social stigma rather than simply perpetuating them, or to generate knowledge of others rather than being directed at serving the solipsism of self-knowledge. Resistant self-tracking efforts may serve to make visible forms of power relations, injustice and inequalities that are currently hidden from view. It is here that a new mode of self-tracking may develop. The possibilities for a new form of data politics that takes up these more critical and challenging practices are intriguing.

Digitising female fertility and reproduction

Over the past few months, I have been working on writing about the findings of several research projects addressing the topic of digital technologies directed at female fertility and reproduction. These projects involve:

1) a critical content analysis of fertility and reproduction-related software and devices (especially apps);

2) an online survey of 410 Australian women’s use of pregnancy and parenting apps; and

3) focus groups and interviews with Australian and British women about their use of these technologies (these are still in progress).

Several outcomes have now been published drawing on these findings. They include a report (with Sarah Pedersen from Robert Gordon University, Aberdeen) outlining the findings of the online survey (this can be accessed here), an article on the gamification and ludification of pregnancy in apps (with Gareth Thomas from Cardiff University, available here) and a book chapter on the concept of the reproductive citizen and the range of digital technologies that are directed at helping women to monitor and regulate their fertility and reproduction (available here). Edit: two other articles have now been published: one based on the survey findings (here), and another on the pregnancy app study (here).

Some of the key findings are:

  • The survey showed that pregnancy and parenting apps were very popular among the survey respondents – three-quarters of the respondents (who were either pregnant or who had a baby in the past three years at the time of the survey) said that they had used at least one pregnancy app, while almost half had used at least one parenting app.
  • Googling information about pregnancy is very common among pregnant women, for whom too much information about pregnancy appears never to be enough (this finding emerged in the focus groups). They tend to invest their trust in the first few search findings that come up on their search engine, reasoning that because this is evidence of popularity, then these websites must be credible.
  • Despite the popularity of pregnancy and parenting apps, few women are contemplating the validity of the information presented in them, or demonstrated concern about the data security and privacy of the personal information that the apps may collect (this was evident in both the survey and the focus groups).
  • This genre of software is intensifying an already fervid atmosphere of self-surveillance, attempts at management and control and self-responsibility in which female fertility and reproduction are experienced and performed.
  • Stereotypical concepts of idealised female fertile and pregnant bodies are reproduced in apps and other software. They use highly aestheticised images and the promise of rational calculation and monitoring to seek to contain and control women’s fertility and reproduction.
  • Women in their fertile years – and particularly those contemplating pregnancy or already pregnant – are part of a highly commodified demographic. The information that they generate from their online practices possess a new form of value, biovalue, as part of the bioeconomy of personal health and medical data.

Self-tracking, social fitness and biovalue

I have just completed a chapter for the forthcoming volume The Sage Handbook of Social Media. The chapter addresses the intersections of self-tracking for health and medical purposes with social media platforms and rationales. As I argue in the chapter, the expanded array of digitised devices that are available for self-tracking and the capacity of many of these technologies to interact with social media platforms have encouraged self-trackers to share the details that they collect about themselves with others. I begin with a description of self-tracking and the sociomaterial theoretical foundations on which the chapter rests. This is followed with an overview of the technologies that are available for health and medical self-tracking and for self-trackers to share their data. The discussion section of the chapter presents an analysis of the new forms of value that personal health and medical data have attracted in the digital data economy, and the moral and political repercussions of encouraging people to participate as socially fit citizens. The chapter ends with outlining key questions for further research.

The full pre-print of the chapter is available here.

Who owns your personal health and medical data?

09/01/15 -- A moment during day 1 of the 2-day international Healthcare and Social Media Summit in Brisbane, Australia on September 1, 2015. Mayo Clinic partnered with the Australian Private Hospitals Association (APHA), a Mayo Clinic Social Media Health Network member to bring this first of it's kind summit to Queensland's Brisbane Convention & Exhibition Centre. (Photo by Jason Pratt / Mayo Clinic)

Presenting my talk at the Mayo Clinic Social Media and Healthcare Summit (Photo by Jason Pratt / Mayo Clinic)

Tomorrow I am speaking on a panel at the Mayo Clinic Healthcare and Social Media Summit on the topic of ‘Who owns your big data?’. I am the only academic among the panel members, who comprise of a former president of the Australian Medical Association, the CEO of the Consumers Health Forum, the Executive Director of a private hospital organisation and the Chief Executive of the Medical Technology Association of Australia. The Summit itself is directed at healthcare providers, seeking to demonstrate how they may use social media to publicise their organisations and promote health among their clients.

As a sociologist, my perspective on the use of social media in healthcare is inevitably directed at troubling the taken-for-granted assumptions that underpin the jargon of ‘disruption’, ‘catalysing’, ‘leveraging’ and ‘acceleration’ that tend to recur in digital health discourses and practices. When I discuss the big data phenomenon, I evoke the ‘13 Ps of big data‘ which recognise their social and cultural assumptions and uses.

When I speak at the Summit, I will note that the first issue to consider is for whom and by whom personal health and medical data are collected. Who decides whether personal digital data should be generated and collected? Who has control over these decisions? What are the power relations and differentials that are involved? This often very intimate information is generated in many different ways – via routine online transactions (e.g. Googling medical symptoms, purchasing products on websites) or more deliberately as part of people’s contributions to social media platforms (such as PatientsLikeMe or Facebook patient support pages) or as part of self-tracking or patient self-care endeavours or workplace wellness programs. The extent to which the generation of such information is voluntary, pushed, coerced or exploited, or indeed, even covert, conducted without the individual’s knowledge or consent, varies in each case. Many self-trackers collect biometric data on themselves for their private purposes. In contrast, patients who are sent home with self-care regimes may do so reluctantly. In some situations, very little choice is offered people: such as school students who are told to wearing self-tracking devices during physical education lessons or employees who work in a culture in which monitoring their health and fitness is expected of them or who may be confronted with financial penalties if they refuse.

Then we need to think about what happens to personal digital data once they are generated. Jotting down details of one’s health in a paper journal or sharing information with a doctor that is maintained in a folder in a filing cabinet in the doctor’s surgery can be kept private and secure. In this era of using digital tools to generate and archive such information, this privacy and security can no longer be guaranteed. Once any kind of personal data are collected and transmitted to the computing cloud, the person who generated the data loses control of it. These details become big data, part of the digital data economy and available to any number of second or third parties for repurposing: data mining companies, marketers, health insurance, healthcare and medical device companies, hackers, researchers, the internet empires themselves and even national security agencies, as Edward Snowden’s revelations demonstrated.

Even the large institutions that are trusted by patients for offering reliable and credible health and medical information online (such as the Mayo Clinic itself, which ranks among the top most popular health websites with 30 million unique estimated monthly visitors) may inadvertently supply personal details of those who use their websites to third parties. One recent study found that nine out of ten visits to health or medical websites result in data being leaked to third parties, including companies such as Google and Facebook, online advertisers and data brokers because the websites use third party analytic tools that automatically send information to the developers about what pages people are visiting. This information can then be used to construct risk profiles on users that may shut them out of insurance, credit or job opportunities. Data security breaches are common in healthcare organisations, and cyber criminals are very interested in stealing personal medical details from such organisations’ archives. This information is valuable as it can be sold for profit or used to create fake IDs to purchase medical equipment or drugs or fraudulent health insurance claims.

In short, the answer to the question ‘Who owns your personal health and medical data?’ is generally no longer individuals themselves.

My research and that of others who are investigating people’s responses to big data and the scandals that have erupted around data security and privacy are finding that concepts of privacy and notions of data ownership are beginning to change in response. People are becoming aware of how their personal data may be accessed, legally or illegally, by a plethora of actors and agencies and exploited for commercial profit. Major digital entrepreneurs, such as Apple CEO Tim Cook, are in turn responding to the public’s concern about the privacy and security of their personal information. Healthcare organisations and medical providers need to recognise these concerns and manage their data collection initiatives ethically, openly and responsibly.

Edited book ‘Beyond Techno-Utopia: Critical Approaches to Digital Health Technologies’ now out

Last year I guest-edited a special issue of the open-access sociology journal Societies that focused on critical perspectives on digital health technologies. The collection includes my editorial and another article I contributed (on the topic of apps as sociocultural artefacts), as well as eight other articles from scholars based in the UK, Australia, Finland, the USA and Sweden. Individual contributions may be accessed on the journal’s website here, and now the whole collection is available as an open access book PDF (or can be purchased as a hard copy), both available here.

The following outline of the special issue/book’s contents, an edited excerpt taken from my editorial, provides an overview of its contents.

The articles in this special issue build on a well-established literature in sociology, science and technology studies and media and cultural studies that has addressed the use of digital technologies in health and medicine… Several of these topics are taken up in the articles published in this special issue. All the authors use social and cultural theory to provide insights into the tacit assumptions, cultural meanings and experiences of digital health technologies. The articles cover a range of digital health technologies: devices used for the self-tracking of body metrics (Ruckenstein; Till; Rich and Miah; Lupton); social media platforms for discussing patients’ experiences of chronic disease (Sosnowy) and experiences of pregnancy and early motherhood (Johnson); health and medical apps (Till; Johnson; Christie and Verran; Lupton); telehealthcare systems (Hendy, Chrysanthaki and Barlow); and a digital public health surveillance system (Cakici and Sanches). While some articles focus on globalised digital media (Cakici and Sanches; Rich and Miah; Till; Lupton), others engage more specifically with a range of sociocultural groups, contexts and locations. These include Aboriginal people living in a remote region of Australia (Christie and Verran) and Australian mothers in urban Sydney (Johnson) as well as research participants in Helsinki, Finland (Ruckenstein), the United States (Sosnowy) and England (Hendy, Chrysanthaki and Barlow).

Understandings and experiences of selfhood and embodiment as they are generated and experienced via digital health devices are central preoccupations in the articles by Ruckenstein, Rich and Miah, Till, Lupton, Sosnowy and Johnson. Ruckenstein’s study of self-trackers found that they often conceptualised their bodies and their physical activities in different ways when these were being monitored and rendered into digital data. The data that were generated by these devices proved to be motivational and to give value to some activities (like housework) that otherwise lacked value or new meaning to functions such as sleep (which when digitised and quantified became viewed as a competence). Ruckenstein found that the digital data tended to be invested with greater validity than were other indicators of bodily wellbeing or activity, such as the individual’s physical sensations.

All of the above authors comment on the ways in which digital health devices such as wearable self-tracking devices, social media platforms, apps and patient support websites work as disciplinary tools. They invite users to conform to the ideals of healthism (privileging good health above other priorities) and the responsible self-management and self-monitoring of one’s health and body, including avoiding exposure to risk. Rich and Miah use the concept of “public pedagogy” to describe the socio-political dimensions of digital health technologies as they are employed to educate people about their bodies and promote self-management. As Johnson notes, for women who are pregnant or have the care of young children, this sphere of responsibility is extended to the bodies of others: the foetus or child. And as Till’s article emphasises, when employees are “encouraged” to engage in self-tracking, the ethos of responsibility extends from personal objectives to those of employers.

Ruckenstein, Till and Sosnowy also highlight the digital labour involved for people who engage with social media or self-tracking apps as part of their personal health or fitness practices. Sosnowy’s interviews with women with multiple sclerosis who blog about their condition emphasise the work involved in such engagement as an “active patient”. Till’s analysis of digital exercise self-tracking points to the appropriations of people’s labour by other actors for commercial reasons.

The article by Hendy, Chrysanthaki and Barlow moves in a somewhat different direction. Using ethnographic cases studies, they look at the managerial issues involved with implementing telehealthcare in English social and health care organisations. Their focus, therefore, is not on the recipients or targets of digital health technologies but rather those who are attempting to institute programs as part of their work as managers. These authors’ contribution highlights the messiness of introducing new systems and practices into large organisations, and the resistances that may emerge on the part of both workers and the targets of telehealthcare programs. Cakici and Sanches’ article also takes an organisational perspective in addressing a European Commission co-funded project directed at syndromic surveillance, or the use of secondary sources to detect outbreaks and patterns in diseases and medical conditions. Digital data are increasingly being use as part of syndromic surveillance: Google Flu Trends is one such example. Cakici and Sanches’ analysis highlights the role played by human decision-making and the affordances of digital technologies in structuring what kinds of data are retrieved for syndromic surveillance and how they are interpreted.

While there are as yet few detailed ethnographic accounts of how people are implementing, adopting or resisting contemporary digital health technologies, there are even fewer that investigate the use of these technologies by members of cultural groups outside the global North. The article by Christie and Verran takes a much-needed diversion from perspectives on white, privileged groups to Aboriginal people living in a remote part of Australia. As they argue, the concepts on health, illness and the body that are held by this cultural group differ radically from the tacit assumptions that are invested in mainstream health and medical apps. Any app that is developed to assist in health literacy that is targeted at this group must incorporate culturally-appropriate modes of communication: positioning people within their cultural and kinship networks of sociality, for example, rather than representing them as atomised actors.

The articles collected here in this special issue have gone some way in offering a critical response to digital health technologies, but they represent only a beginning. Many more compelling topics remain to be investigated. These include research into the ways in which lay people and healthcare professionals are using (or resisting the use) of social media, apps and self-monitoring devices for medicine and health-related purposes; the implications for medical power and the doctor-patient relationship; how citizen science and citizen sensing are operating in the public health domain; the development of new digital health technologies; the implications of big data and data harvesting in medicine and healthcare; the spreading out of health-related self-tracking practices into many social domains; the unintended consequences and ethical aspects of digital technology use and their implications for social justice; and data security and privacy issues.