Everyday curation? Attending to data, records and record keeping in the practices of self-monitoring

Bibliographic Data

ID5260360
AuthorsKate Weiner (0000-0002-5115-8866, University of Sheffield, corresponding author), Catherine Will (0000-0001-7224-714X, University of Sussex), Flis Henwood (0000-0003-2706-3100, University of Brighton), Ros Williams (0000-0002-4295-2582, University of Sheffield), Rosalind Williams
Year2020
Volume7
Issue1
Pages205395172091827
Publication date2020-01-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBig Data & Society (JOURNAL)
Journal identifiersISSN: 2053-9517 • E-ISSN: 2053-9517
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/2053951720918275
OpenAlexW3017984661
LanguageEN
Citations received16
References cited43

This paper is concerned with everyday data practices, considering how people record data produced through self-monitoring. The analysis unpacks the relationships between taking a measure, and making and reviewing records. The paper is based on an interview study with people who monitor their blood pressure and/or body mass index/weight. Animated by discussions of 'data power' which are, in part, predicated on the flow and aggregation of data, we aim to extend important work concerning the everyday constitution of digital data. In the paper, we adopt and develop the idea of curation as a theory of attention. We introduce the idea of discerning work to characterise the skilful judgements people make about which readings they record, how readings are presented, and about the records they retain and those they discard. We suggest self-monitoring produces partial data, both in the sense that it embodies these judgements, and also because monitoring might be conducted intermittently. We also extend previous analyses by exploring the broad set of materials, digital and analogue, networked and not networked, involved in record keeping to consider the different ways these contributed to regulating attention to self-monitoring. By paying attention to which data is recorded and the occasions when data is not recorded, as well as the ways data is recorded, the research provides specificity to the different ways in which self-monitoring data may or may not flow or contribute to big data sets. We argue that ultimately our analysis contributes to nuancing our understanding of 'data power

Big data · Data curation · Data mining · Data science · Digital curation · Digital data · Epistemology · Everyday life · Self-monitoring · Sociology · World Wide Web · Computer Science · Innovative Human-Technology Interaction · Participatory Visual Research Methods · Psychology · Social Psychology

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Open DOISci-HubOpen Access