1 Von Quetelet bis Quantified Self. Statistische Regulation im soziotechnischen Wandel

2021 ◽  
pp. 55-64
Keyword(s):  
Quantified Self

scholarly journals Co-evolving with self-tracking technologies

2018 ◽  
Vol 20 (10) ◽  
pp. 3624-3640 ◽  
Author(s):  
Dorthe Brogård Kristensen ◽  
Minna Ruckenstein
Keyword(s):  
Political Economy ◽  
Digital Technology ◽  
The Self ◽  
Quantified Self ◽  
Use Of Self ◽  
Technology Market

Seen in a longitudinal perspective, Quantified Self-inspired self-tracking sets up “a laboratory of the self,” where people co-evolve with technologies. By exploring ways in which self-tracking technologies energize everyday aims or are experienced as limiting, we demonstrate how some aspects of the self are amplified while others become reduced and restricted. We suggest that further developing the concept of the laboratory of the self renews the conversation about the role of metrics and technologies by facilitating comparison between different realms of the digital, and demonstrating how services and devices enlarge aspects of the self at the expense of others. The use of self-tracking technologies is inscribed in, but also runs counter to, the larger political-economy landscape. Personal laboratories can aid the exploration of how the techno-mediated selves fit into larger structures of the digital technology market and the role that metrics play in defining them.

scholarly journals Big Data in Science and Healthcare: A Review of Recent Literature and Perspectives

2014 ◽  
Vol 23 (01) ◽  
pp. 21-26 ◽  
Author(s):  
T. Miron-Shatz ◽  
A. Y. S. Lau ◽  
C. Paton ◽  
M. M. Hansen
Keyword(s):  
Health Care ◽  
Big Data ◽  
Health Care Providers ◽  
Data Privacy ◽  
Recent Literature ◽  
Unstructured Data ◽  
Small Scale ◽  
Small Data ◽  
Quantified Self ◽  
Care Providers

Summary Objectives: As technology continues to evolve and rise in various industries, such as healthcare, science, education, and gaming, a sophisticated concept known as Big Data is surfacing. The concept of analytics aims to understand data. We set out to portray and discuss perspectives of the evolving use of Big Data in science and healthcare and, to examine some of the opportunities and challenges. Methods: A literature review was conducted to highlight the implications associated with the use of Big Data in scientific research and healthcare innovations, both on a large and small scale. Results: Scientists and health-care providers may learn from one another when it comes to understanding the value of Big Data and analytics. Small data, derived by patients and consumers, also requires analytics to become actionable. Connectivism provides a framework for the use of Big Data and analytics in the areas of science and healthcare. This theory assists individuals to recognize and synthesize how human connections are driving the increase in data. Despite the volume and velocity of Big Data, it is truly about technology connecting humans and assisting them to construct knowledge in new ways. Concluding Thoughts: The concept of Big Data and associated analytics are to be taken seriously when approaching the use of vast volumes of both structured and unstructured data in science and health-care. Future exploration of issues surrounding data privacy, confidentiality, and education are needed. A greater focus on data from social media, the quantified self-movement, and the application of analytics to “small data” would also be useful.

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