Datification describes the process of digitally mapping and thus quantifying more and more aspects of life through the evaluation of data (1,2). This is aided by algorithmic decision-making processes that evaluate large amounts of data and can thus identify and predict individual actions and preferences with – purportedly – great accuracy. The production and evaluation of data is increasingly accepted as the basis of social processes. Algorithmic systems can, for example, determine the individual health status by evaluating health data as well as data on consumer behaviour and social behaviour. Health insurance companies can use this result to adjust their rates. Commercial providers can offer customised products based on this (individualised advertising). These examples show that data generated in “private” self-tracking practices ends up outside the access of those who generated it and thus belongs to commercial entities (like mHealth apps) or governmental organisations. However, the analysis of private data is in turn used to influence personal, individual decision-making processes.

  1. Ruckenstein, M., & Dow Schüll, N. (2016). The Datafication of Health. Annual Review of Anthropology, 46, 1–18.
  2. Lupton, D. (2016): You are Your Data: Self-tracking Practices and Concepts of Data. In: Selke, S. (Eds..): Lifelogging. Digital self-tracking and Lifelogging – between disruptive technology and cultural transformation. Wiesbaden: Springer VS, 61-79.
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