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Where Health and Environment Meet: The Use of Invariant Parameters for Big Data Analysis

Leonelli, Sabina and Tempini, Niccolo (2018) Where Health and Environment Meet: The Use of Invariant Parameters for Big Data Analysis. [Preprint]

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Abstract

The use of big data to investigate the spread of infectious diseases or the impact of the built environment on human wellbeing goes beyond the realm of traditional approaches to epidemiology, and includes a large variety of data objects produced by research communities with different methods and goals. This paper addresses the conditions under which researchers link, search and interpret such diverse data by focusing on “data mash-ups” – that is the linking of data from epidemiology, biomedicine, climate and environmental science, which is typically achieved by holding one or more basic parameters, such as geolocation, as invariant. We argue that this strategy works best when epidemiologists interpret localisation procedures through an idiographic perspective that recognises their context-dependence and supports a critical evaluation of the epistemic value of geolocation data whenever they are used for new research purposes. Approaching invariants as strategic constructs can foster data linkage and re-use, and support carefully-targeted predictions in ways that can meaningfully inform public health. At the same time, it explicitly signals the limitations in the scope and applicability of the original datasets incorporated into big data collections, and thus the situated nature of data linkage exercises and their predictive power.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Leonelli, Sabinas.leonelli@exeter.ac.uk0000-0002-7815-6609
Tempini, Niccolon.tempini@exeter.ac.uk0000-0002-5100-5376
Additional Information: Accepted for publication in Synthese on June 1, 2018.
Keywords: epidemiology, geolocation, data linkage, data reuse, inference, data mash-ups, localisation, prediction, public health
Subjects: General Issues > Data
Specific Sciences > Biology
Specific Sciences > Medicine
Depositing User: Sabina Leonelli
Date Deposited: 04 Jun 2018 20:30
Last Modified: 04 Jun 2018 20:30
Item ID: 14741
Subjects: General Issues > Data
Specific Sciences > Biology
Specific Sciences > Medicine
Date: 4 June 2018
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/14741

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