Where health and environment meet: the use of invariant parameters in big data analysis.

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.

Actionable data for precision oncology: Framing trustworthy evidence for exploratory research and clinical diagnostics.

Huge amounts of genomic data produced by researchers around the world undermine data-centred discovery and therapeutic development. This paper considers how researchers make decisions about the actionability of specific datasets and the conditions that allow such data to be trusted. We discuss the case of COSMIC, a leading cancer genomics database which aggregates a large amount of sources. We research what the actionability of cancer data means in different situations of use, contrasting exploratory and diagnostics research. They highlight different questions and concerns upon genomic data use in medical research. At the same time, strategies and justifications pursued to evaluate and re-use can also share important similarities. To explain differences and similarities, we argue for an understanding of actionability and trust in data that depends on the goals and resources within the situation of inquiry, and the social epistemology of standards.

Concealment and discovery: The role of information security in biomedical data re-use.

This paper analyses the role of information security (IS) in shaping the dissemination and re-use of biomedical data, as well as the embedding of such data in material, social and regulatory landscapes of research. We consider data management practices adopted by two UK-based data linkage infrastructures: the Secure Anonymised Information Linkage, a Welsh databank that facilitates appropriate re-use of health data derived from research and routine medical practice in the region, and the Medical and Environmental Data Mash-up Infrastructure, a project bringing together researchers to link and analyse complex meteorological, environmental and epidemiological data. Through an in-depth analysis of how data are sourced, processed and analysed in these two cases, we show that IS takes two distinct forms: epistemic IS, focused on protecting the reliability and reusability of data as they move across platforms and research contexts, and infrastructural IS, concerned with protecting data from external attacks, mishandling and use disruption. These two dimensions are intertwined and mutually constitutive, and yet are often perceived by researchers as being in tension with each other. We discuss how such tensions emerge when the two dimensions of IS are operationalized in ways that put them at cross purpose with each other, thus exemplifying the vulnerability of data management strategies to broader governance and technological regimes. We also show that whenever biomedical researchers manage to overcome the conflict, the interplay between epistemic and infrastructural IS prompts critical questions concerning data sources, formats, metadata and potential uses, resulting in an improved understanding of the wider context of research and the development of relevant resources. This informs and significantly improves the reusability of biomedical data, while encouraging exploratory analyses of secondary data sources.