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In this chapter, we draw on our study involving interviews with Australians who identify as current self-trackers to discuss why and how they monitor themselves. Our approach for analysing self-tracking practices is based on a sociomaterial perspective, viewing enactments of voluntary self-tracking as shifting heterogeneous assemblages, bringing together diverse actors who are both human and non-human. We use vignettes to illustrate the ways in which our participants enacted self-tracking and to identify some of the diverse meanings and motivations that mediate decisions to self-track and resultant uses of the information thus generated. We found that a varied range of self-tracking practices were taken up by our interviewees, including not only digital devices and methods, but also recording their details using pen-and-paper, or simply maintaining mental awareness and using memory. We identified several agential capacities in our participants’ accounts of why and how they monitor themselves. These capacities are interrelated, but can be loosely grouped under the headings of ‘self-improvement’, ‘exerting control’ and ‘identifying patterns and achieving goals’. They are motivators and facilitators of monitoring practices. The broader sociocultural contexts in which monitoring of the body/self is undertaken were also revealed in the participants’ accounts. These include ideas about the moral virtues of self-responsibility and the individual management of life circumstances to avoid chaos and risk, and the notion that monitoring practices can successfully achieve these virtues.

Nowadays there are many digital tools and mediatised ways for self-tracking for the sake of gaining self-knowledge through numbers. In his recent book ‘Resonance’, Hartmut Rosa suggests that artefacts can indeed resonate with people (Rosa, 2016, p. 381ff.) by affecting emotion, intrinsic interests and self-efficacy expectations. In contrast, Rosa characterises self-tracking as an attempt to measure the resource potential of individuals, confounding it with the good life itself (Rosa, 2016, p. 47). That is why we want to challenge Rosa’s concept of a good life and enhance the assertion of individual and social practices that can generate resonance.

With several case studies, we want to study empirically how people ‘resonate’ (or not) with and in self-tracking practices and to which degree Rosa’s hypothesis is verifiable or not. By empirically contrasting the quantifying practices and metric culture of self-tracking with the recently emerging sociological field of ‘world relationships’ and ‘resonance’, new insights on the embedding of the quantified with the qualified self will be gained.

The purpose of this article is to examine the ways in which self-tracking data have meaning and value in and after the life of the creator, including how such data could become part of the larger historical record, curated in an institutional archive. In doing so, the article expands upon existing shared interests among researchers working in the areas of self-tracking, human–computer interaction and archival science.

A total of 18 people who had self-tracked for six months or more were recruited for the study. Participants completed a survey which gathered demographic data and characteristics vis-à-vis their self-tracking behavior. In-person semi-structured interviews were then conducted to ascertain the beliefs of the participants regarding the long-term use and value of personal quantified-self data.

The findings reveal the value that people place on self-tracking data, their thoughts on proper modes for accessing their archive once it moves from the private to the public space, and how to provide fidelity within the system such that their experiences are represented while also enabling meaning making on the part of subsequent users of the archive.

Today’s quantified-self data are generally embedded in systems that create a pipeline from the individual source to that of the corporate warehouse, bent on absorbing and extracting insight from a totality of big data. This article posits that new opportunities for knowing and for design can be revealed when a public interest rationale is appended to rich personalized collections of small data.

This chapter provides an insider perspective on the Quantified Self (QS) community. It is argued that the overall approach and methods used in the QS community have not been adequately described. Consequently, the aim of the chapter is to give an account of the work performed by self-trackers in what we coin the 1-Person-Laboratory (1PL). Additionally, the chapter describes other aspects of the 1PL, for example the methods, procedures and instrumentation that are being used and the knowledge sharing taking place in the QS community. With a point of departure in empirical cases it is demonstrated how QS self-trackers put their own questions, observations and subjective experience front and centre by using their own instrumentation and data sets in their personal laboratories. In the 1PL, the causalities that are looked for are not aimed at generalisation to an entire population; on the contrary, the causal connections on the level of the person are essential for discovery by the individual.

This paper aims to fill this gap (infra, originality) by providing a conceptual framework for discussing “technologies of the self and other,” by showing that, in most cases, self-tracking also involves other-tracking.

In so doing, we draw upon Foucault’s “technologies of the self” and present-day literature on self-tracking technologies. We elaborate on two cases and practical domains to illustrate and discuss this mutual process: first, the quantified workplace; and second, quantification by wearables in a non-clinical and self-initiated context.

The main conclusion is that these shapings are never (morally) neutral and have ethical implications, such as regarding “quantified otherness,” a notion we propose to point at the risk that the other could become an object of examination and competition.

Although there is ample literature on the quantified self, considerably less attention is given to how the relation with the other is being shaped by self-tracking technologies that allow data sharing (e.g. wearables or apps such as Strava or RunKeeper).

Metrics, data, algorithms and numbers play an unmistakably powerful role in today’s society. Over the years, their use and function have expanded to cover almost every sphere of everyday life so much so that it can be argued that we are now living in a ‘metric culture’, a term indicating at once the growing cultural interest in numbers and a culture that is increasingly shaped by numbers, as Beer (2016) also argues. At the same time, metric culture is not only about numbers and numbers alone, but also links to issues of power and control, to questions of value and agency and to expressions of self and identity. Self-tracking practices are indeed a manifestation of this metric culture and a testimony to how measurement, quantification, documentation and datafication have all become important tropes for managing life and the living in contemporary society. In this introductory chapter, I provide a general contextualisation of the topic of this edited collection along with an overview of the different chapters and their key arguments.

Commercial entities (e.g. health and life insurance, airlines and supermarkets) in different countries have recently begun to introduce wearable technology as part of the consumer journey and as a means of enhancing the business value chain. While a firm’s decision to adopt such new technologies as wearable devices is often based on financial factors such as return on investment, costs and impact on profits, consumers may hold a different attitude toward the value of using smart wearables and sharing their personal data as part of their business-client relationships. The purpose of this paper is to investigate consumer perceptions of and reactions to persuaded self-tracking (PST) – a practice in which businesses actively encourage consumers to monitor, collect and share personal biometric data through wearable technologies in exchange for personalized incentives and rewards.

Using a qualitative research approach and a purposeful sampling method, the authors conducted personal in-depth interviews with 24 consumers (both users and non-users of wearable devices). Interviews were recorded and transcribed, resulting in 600 pages of transcripts comprising more than 203,000 words. Data coding and analysis were facilitated by using NVivo.

Consumers’ assessment of PST is based on perceived value-in-use, privacy/security concerns and perceived fairness/justice, resulting in four types of reactions to adopt or use PST (embracing, considering, debating and avoiding). Specifically, the authors identified two individual determinants (intrinsic motivation and extrinsic motivation) and four firm-related determinants (design of wearable device, assurance, transparency and controllability) that influence consumer perceptions of PST.

Results of this study have implications for both vendors of wearable devices and firms trying to leverage smart wearables in their value chains. Identifying consumers’ perceptions, as well as barriers and enablers of acceptance, will help firms to more effectively design and develop wearable device-based services, thus gaining consumer support for using fitness trackers. The primary limitation of the study is that using a thematic analysis method diminishes the generalizability of our findings.

This study addresses an under-researched area: the integration of wearable technologies in a firm’s value chain through the lens of the consumers. This study is one of the first, according to authors’ knowledge, to investigate consumer perceptions of PST.

The purpose of this paper is to understand what dimensions consumers prefer to track using wearable technology to achieve a healthier lifestyle and how these tracking dimensions are related.

An online survey was conducted with potential consumers in the USA, and a series of Pearson’s correlation and regression analysis and multiple regressions was conducted.

The most preferred self-tracking dimensions, tracking dimensions on others, most private tracking dimensions, most variable dimensions, and the dimensions that need to be improved were identified. The results of this study showed positive relationships overall among similar types of tracking dimensions, such as among dimensions of physical health condition (disease and disorder symptoms and general vital signs), mental health condition (stress level and mood/feeling), healthy lifestyle (fitness, and pose and posture), and productivity and task management (work productivity, location, and time management).

Designers are encouraged to make wearable technology products that are durable, easy to care for, attractive in design, comfortable to wear and use, able to track preferred dimensions, appropriate for various consumers, unobtrusive, portable, and small. This research will guide wearable technology and fashion industry professionals in the development process of wearable technology to benefit consumers by helping them be more self-aware, empowering them to develop a healthier lifestyle, and ultimately increasing their quality of life and well-being.

The chapter critically analyzes the concepts and the practices of surveillance in modern and postmodern societies along with their consequences. We show the changes in the systems, which are used to monitor individuals, and emphasize the transition toward soft surveillance systems, probably stimulated by digital technologies. This switch from top-down control to “lateral” monitoring systems encloses surveillance practices with suggestive names like interveillance, synopticon, and dataveillance. The dark side of digital health has a bright start. According to Topol’s (2016) vision of the future, we will soon be the “consumers,” the real protagonists, of the management of our health – thanks largely to the practically endless data about our bodies, behaviors, and lifestyles we will be able to collect and analyze. We will share our health information in real time with the doctors whom we will choose based on their score in clinical rankings (here, too, quantification rears its head). Yet, this simplified version of health makes it seem that there are always some solutions, which the algorithm can supply as long as it has enough information. Moreover, in the United States, some health-insurance companies have started to offer a discount on premiums to the members who agree to collect and share self-tracking data with them. Clearly, the discount is given only to the workers who have healthy habits. At first sight, this can seem as a win-win trade-off; however, what today is presented as an individual option can easily become a requirement tomorrow.