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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.

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.

Contemporary society is characterized by extreme acceleration (Rosa, 2010). Time has become a scarce resource and individuals are forced to adhere to the demands of speediness. This condition is connected to the increased performance now required in many areas of daily life, an increase so profound that some authors refer to ours as a “doping society.”

This chapter argues that the practice of quantification exponentially increases the “managerializing” of the user. In this sense, the quantified-self (QS) can be thought of as something that helps people to organize their activities in the manner of the market. Individuals thus become self-entrepreneurs who, in keeping with the standard aims of neoliberalism, make use of their collected data in a fashion analogous to the way results are determined in a corporation’s Research & Development department. The self becomes an assortment of analyses by which measures of behaviors and habits are made, all in the name of producing an “objective report” on the user’s characteristics. The ultimate aim of all this is to improve certain parts of life so as to increase and optimize our productivity.

What counts as evidence of good performance, behaviour or character? While quantitative metrics have long been used to measure performance and productivity in schools, factories and workplaces, what is striking today is the extent to which these calculative methods and rationalities are being extended into new areas of life through the global spread of performance indicators (PIs) and performance management systems. What began as part of the neoliberalising projects of the 1980s with a few strategically chosen PIs to give greater state control over the public sector through contract management and mobilising ‘users’ has now proliferated to include almost every aspect of professional work. The use of metrics has also expanded from managing professionals to controlling entire populations. This chapter focuses on the rise of these new forms of audit and their effects in two areas: first, the alliance being formed between state-collected data and that collected by commercial companies on their customers through, for example loyalty cards and credit checks. Second, China’s new social credit system, which allocates individual scores to each citizen and uses rewards of better or privileged service to entice people to volunteer information about themselves, publish their ‘ratings’ and compete with friends for status points. This is a new development in the use of audit simultaneously to discipline whole populations and responsibilise individuals to perform according to new state and commercial norms about the reliable/conforming ‘good’ citizen.

The purpose of this paper is to explore the meaning of information literacy (IL) in food logging, the activity of recording food intake and monitoring weight and other health conditions that may be affected by diet, using applications (apps) accessed through mobile devices and personal computers.

Data were gathered from a small group of food logging app users through a focus group and interviews. Analysis was informed by practice theory and the growing interest in IL outside educational settings.

Food logging revolves around the epistemic modality of information, but it is the user who creates information and it is not textual. Food logging is associated with a discourse of focussing on data and downplaying the corporeal information associated with eating and its effect on the body. Social information was an important source for choosing an app, but data were rarely shared with others. Food loggers are very concerned with data quality at the point of data entry. They have a strong sense of learning about healthy eating. They were not well informed about the data privacy and access issues.

Food loggers need to be better informed about data risks around food logging.

This is the first study of food logging from an IL perspective.

This paper aims to examine how metadata taxonomies in embodied computing databases indicate context (e.g. a marketing context or an ethical context) and describe ways to track the evolution of the embodied computing industry over time through digital media archiving.

The authors compare the metadata taxonomies of two embodied computing databases by providing a narrative of their top-level categories. After identifying these categories, they describe how they structure the databases around specific themes.

The growing wearables market often hides complex sociotechnical tradeoffs. Marketing products like Vandrico Inc.’s Wearables Database frame wearables as business solutions without conveying information about the various concessions users make (about giving up their data, for example). Potential solutions to this problem include enhancing embodied computing literacy through the construction of databases that track media about embodied computing technologies using customized metadata categories. Databases such as FABRIC contain multimedia related to the emerging embodied computing market – including patents, interviews, promotional videos and news articles – and can be archived through user-curated collections and tagged according to specific themes (privacy, policing, labor, etc.). One of the benefits of this approach is that users can use the rich metadata fields to search for terms and create curated collections that focus on tradeoffs related to embodied computing technologies.

This paper describes the importance of metadata for framing the orientation of embodied computing databases and describes one of the first attempts to comprehensively track the evolution of embodied computing technologies, their developers and their diverse applications in various social contexts through media archiving.