Year: 2018
Type: article
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.
Source: Synthese
Authors: Sabina Leonelli, Niccolò Tempini
Institution: University of Exeter
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,190
Awards: Linking Human Health and Wellbeing with Weather, Climate, and the Environment: MED-MI (Medical and Environmental Data - a Mash-up Infrastructure), G123158180, Organisms and Us: How Living Things Help Us To Understand Our World, G3489803962, Social sensing of health and wellbeing impacts from pollen and air pollution, G8051973743, G8810447461
OpenAlex ID: W2805470867