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Cited by 375

The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.

Visualized and Interacted Life: Personal Analytics and Engagements with Data Doubles

Open access
Ruckenstein, Minna·2014·Societies
DOI 10.3390/soc4010068
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Abstract

A field of personal analytics has emerged around self-monitoring practices, which includes the visualization and interpretation of the data produced. This paper explores personal analytics from the perspective of self-optimization, arguing that the ways in which people confront and engage with visualized personal data are as significant as the technology itself. The paper leans on the concept of the “data double”: the conversion of human bodies and minds into data flows that can be figuratively reassembled for the purposes of personal reflection and interaction. Based on an empirical study focusing on heart-rate variability measurement, the discussion underlines that a distanced theorizing of personal analytics is not sufficient if one wants to capture affective encounters between humans and their data doubles. Research outcomes suggest that these explanations can produce permanence and stability while also profoundly changing ways in which people reflect on themselves, on others and on their daily lives.

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Metadata

Authors
Ruckenstein, M.
Venue
Societies
Publisher
MDPI AG
Published
2014-02-18
Volume
4
Issue
1
Pages
68-84
ISSN
2075-4698 (ISSN-L)
DOI
10.3390/soc4010068
OpenAlex
W2152714445
Cited by
375
References
28
FWCI
62.41
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Visualized and Interacted Life: Personal Analytics and Engagements with Data Doubles. https://app.cochat.ai/papers/10.3390/soc4010068
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Ruckenstein, M. (2014). Visualized and Interacted Life: Personal Analytics and Engagements with Data Doubles. Societies. https://doi.org/10.3390/soc4010068

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.