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dc.contributor.authorCanali, S
dc.contributor.authorLeonelli, S
dc.date.accessioned2022-03-28T10:33:31Z
dc.date.issued2022-05-13
dc.date.updated2022-03-28T08:21:19Z
dc.description.abstractIn 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.en_GB
dc.description.sponsorshipDeutsche Forschungsgemeinschaft (DFG)en_GB
dc.description.sponsorshipEuropean Research Council (ERC)en_GB
dc.description.sponsorshipAlan Turing Instituteen_GB
dc.identifier.citationVol. 93, pp. 203 - 214en_GB
dc.identifier.doi10.1016/j.shpsa.2022.04.006
dc.identifier.grantnumber254954344/GRK2073en_GB
dc.identifier.grantnumber335925en_GB
dc.identifier.grantnumberEP/N510129/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/129181
dc.identifierORCID: 0000-0002-7815-6609 (Leonelli, Sabina)
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.rights© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectepidemiologyen_GB
dc.subjectbig dataen_GB
dc.subjectenvironmenten_GB
dc.subjectexposureen_GB
dc.titleReframing the environment in data-intensive health sciencesen_GB
dc.typeArticleen_GB
dc.date.available2022-03-28T10:33:31Z
dc.identifier.issn0039-3681
dc.descriptionThis is the final version. Available on open access from Elsevier via the DOI in this reocrden_GB
dc.identifier.journalStudies in History and Philosophy of Scienceen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2022-03-22
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2022-03-22
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2022-03-28T08:21:22Z
refterms.versionFCDAM
refterms.dateFOA2022-06-14T12:30:07Z
refterms.panelCen_GB


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© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).