The quantified-self archive: documenting lives through self-tracking data

Ciaran B. Trace (School of Information, University of Texas, Austin, Texas, USA)
Yan Zhang (School of Information, University of Texas, Austin, Texas, USA)

Journal of Documentation

ISSN: 0022-0418

Publication date: 23 August 2019

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Keywords

Acknowledgements

This work was supported by the Governor Bill Daniel Fellowship from the School of Information, The University of Texas at Austin.

Citation

Trace, C.B. and Zhang, Y. (2019), "The quantified-self archive: documenting lives through self-tracking data", Journal of Documentation, Vol. 76 No. 1, pp. 290-316. https://doi.org/10.1108/JD-04-2019-0064

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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