Bodies of data: doubles, composites, and aggregates

Douglas‐Jones, Rachel

doi:10.1111/1467-9655.13486

Cited by 7 publications

(4 citation statements)

References 35 publications

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“…Initiators employed by Digital Life Norway envisioned the Digital Salmon as a “virtual meeting place for scientists interested in how fish feed affects the life and quality of the fish” (Eikenes 2018). Pitching the Digital Salmon as eventually enabling “artificial (marine) intelligence” (Eikenes 2018), the ambition was to bring to work a prediction-active, performative “data double” (Douglas-Jones 2021). Here, this data double was even casted as a “digital twin”—a real-time, continuously optimized model representation, originally used for technical systems (Korenhof, Giesbers, and Sanderse 2023), and now gaining prominence through artificial intelligence (AI) research.…”

Section: Aligning Salmon Extractions With Human Biomedicine: Feed And...mentioning

confidence: 99%

“…Today's digital platforms and data practices in the biosciences extend molecular sequence inventories beyond DNA (Waterton 2010;Leonelli 2016). Digital practices are shaped by and have transformed collecting and classification in botany and zoology, as well as more broadly in taxonomy and biodiversity studies (Ellis, Waterton, and Wynne 2010;Strasser 2019;Nadim 2021;Douglas-Jones 2021). In biology, datafication occurs through heterogeneous procedures at different scales across a broad range of laboratory and field settings.…”

Section: Introductionmentioning

confidence: 99%

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Seeing Like a Model Fish: How Digital Extractions Mediate Metabolic Relations

Bauer

2024

Science, Technology, & Human Values

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Digital models have become key sites of biological practice and science policy. This paper examines efforts to craft a digital salmon model for metabolic research. It traces the data configurations of feed, food, and health in Norway’s bioeconomy aspirations—from cell culture studies in the lab to an integrated digital repository and public health nutrition trials in schools. A response to policy calls for more sustainable aquaculture, digital models become lynchpins for intensified data sourcing. I describe how datafication and digital model integration enact a particular mode of management, focused on profitability and human preferences, when optimizing fish feed to sustainability goals. Integrating molecular biology and mathematical functions, digital modeling promotes the idea of a prediction machine for preemptive optimization of feed and food across settings. Yet, unforeseen disruptions to aquaculture, for instance, by algae and lice, expose the complexity of marine food webs and the limitations of digital models. Even while in the making, the digital fish model becomes performative and shapes knowledge practices much beyond the lab. As knowledge infrastructures, models participate in the remaking of metabolic relations, recalibrating decision-making, while feeding back into and co-shaping the very entities and environments they were crafted to investigate.

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Section: Aligning Salmon Extractions With Human Biomedicine: Feed And...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Seeing Like a Model Fish: How Digital Extractions Mediate Metabolic Relations

Bauer

2024

Science, Technology, & Human Values

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“…Schüll highlights the ‘creative vocabulary’ (2018: 35) introduced by scholars aiming to capture the intensive datafication of life in western societies. These include the use of terms such as ‘data doubles’ or data selves to describe emergent and temporary virtual/informational profiles that are aggregated from different data sources, sliced and circulated and through which selves become both objects and subjects of power in digital worlds (Douglas-Jones, 2021; Green and Svendsen, Haggerty and Ericson, 2000; Lupton, 2019). Thus, confronted by an advertising company's elaboration of the use of data to target a specific consumer – herself – Goriunova asks“What exactly is this digital entity that she identified as me?…”

Section: Doubles and Shadows – Life With Datamentioning

confidence: 99%

“…This ‘loop’ of (self-) representation and transformation is both recognised and valued by those involved in the development and capitalisation of data-driven tools. It is central to the premise of fitness and ‘wellness’ devices that aim to encourage reflexive interactions with the data self, whether for health or wealth (Douglas-Jones, 2021; Lupton, 2019).…”

Section: Doubles and Shadows – Life With Datamentioning

confidence: 99%

Digital phenotyping and the (data) shadow of Alzheimer's disease

2022

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In this paper, we examine the practice and promises of digital phenotyping. We build on work on the ‘data self’ to focus on a medical domain in which the value and nature of knowledge and relations with data have been played out with particular persistence, that of Alzheimer's disease research. Drawing on research with researchers and developers, we consider the intersection of hopes and concerns related to both digital tools and Alzheimer's disease using the metaphor of the ‘data shadow’. We suggest that as a tool for engaging with the nature of the data self, the shadow is usefully able to capture both the dynamic and distorted nature of data representations, and the unease and concern associated with encounters between individuals or groups and data about them. We then consider what the data shadow ‘is’ in relation to ageing data subjects, and the nature of the representation of the individual's cognitive state and dementia risk that is produced by digital tools. Second, we consider what the data shadow ‘does’, through researchers and practitioners’ discussions of digital phenotyping practices in the dementia field as alternately empowering, enabling and threatening.

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Data as Relation: Ontological Trouble in the Data-Driven Public Administration

Winthereik

2023

Comput Supported Coop Work

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This paper examines how the intense focus on data in political digitalization strategies takes effect in practice in a Danish municipality. Building on an ethnographic study of data-driven management, the paper argues that one of the effects of making data a driver for organizational decision-making is uncertainty as to what data are and can be taken to mean. While in political discourse and strategies, data are considered as a resource for collaboration across organizational units as well as for optimization of their performance, in practice, data are not this straightforward entity. The paper presents a kind of data work that identifies data as part of different worlds (ontologies). The management task that results from this is nurturing organizational spaces that articulate data as relational. The paper argues that being attentive to the troublesome experiences public sector employees have when encountering data may help mitigate some of the risks of seeing data merely as a resource. The paper concludes that as public sector managers learn to nurture spaces where differences in data can be articulated, they also protect core values of welfare bureaucracies. Acknowledging that data work is about what we take to be real and what not (ontological work) is a first step in this direction.

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Bodies of data: doubles, composites, and aggregates

Cited by 7 publications

References 35 publications

Seeing Like a Model Fish: How Digital Extractions Mediate Metabolic Relations

Seeing Like a Model Fish: How Digital Extractions Mediate Metabolic Relations

Digital phenotyping and the (data) shadow of Alzheimer's disease

Data as Relation: Ontological Trouble in the Data-Driven Public Administration

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