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Reframing the Environment in Data-Intensive Health Sciences

Canali, Stefano and Leonelli, Sabina (2022) Reframing the Environment in Data-Intensive Health Sciences. [Preprint]

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Abstract

In this paper, we analyse the relation between the use of environmental data in contemporary health sciences and related conceptualisations and operationalisations of the notion of environment. We consider three case studies that exemplify a different selection of environmental data and mode of data integration in data-intensive epidemiology. We argue that the diversification of data sources, their increase in scale and scope, and the application of novel analytic tools have brought about three significant conceptual shifts. First, we discuss the EXPOsOMICS project, an attempt to integrate genomic and environmental data which suggests a reframing of the boundaries between external and internal environments. Second, we explore the MEDMI platform, whose efforts to combine health, environmental and climate data instantiate a reframing and expansion of environmental exposure. Third, we illustrate how extracting epidemiological insights from extensive social data collected by the CIDACS institute yields innovative attributions of causal power to environmental factors. Identifying these shifts highlights the benefits and opportunities of new environmental data, as well as the challenges that such tools bring to understanding and fostering health. It also emphasises the constraints that data selection and accessibility pose to scientific imagination, including how researchers frame key concepts in health-related research.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Canali, Stefanostefano.canali@polimi.it0000-0002-5948-3874
Leonelli, Sabinas.leonelli@exeter.ac.uk0000-0002-7815-6609
Keywords: Epidemiology; Big Data; Environment; Exposure
Subjects: General Issues > Data
Specific Sciences > Environmental Science
General Issues > Evidence
Specific Sciences > Medicine
General Issues > Technology
Depositing User: Dr. Stefano Canali
Date Deposited: 29 Apr 2022 03:48
Last Modified: 29 Apr 2022 03:48
Item ID: 20525
Subjects: General Issues > Data
Specific Sciences > Environmental Science
General Issues > Evidence
Specific Sciences > Medicine
General Issues > Technology
Date: 2022
URI: http://philsci-archive.pitt.edu/id/eprint/20525

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