Eye in the sky

This is the author accepted manuscriptAlan Turing Institut

Till data do us part: Understanding data-based value creation in data-intensive infrastructures

Much of the literature on value creation in social media-based infrastructures has largely neglected the pivotal role of data and their processes. This paper tries to move beyond this limitation and discusses data-based value creation in data-intensive infrastructures, such as social media, by focusing on processes of data generation, use and reuse, and on infrastructure development activities. Building on current debates in value theory, the paper develops a multidimensional value framework to interrogate the data collected in an embedded ethnographical case study of the development of PatientsLikeMe, a social media network for patients. It asks when, and where, value is created from the data, and what kinds of value are created from them, as they move through the data infrastructure; and how infrastructure evolution relates to, and shapes, existing data-based value creation practices. The findings show that infrastructure development can have unpredictable consequences for data-based value creation, shaping shared practices in complex ways and through a web of interdependent situations. The paper argues for an understanding of infrastructural innovation that accounts for the situational interdependencies of data use and reuse. Uniquely positioned, the paper demonstrates the importance of research that looks critically into processes of data use in infrastructures to keep abreast of the social consequences of developments in big data and data analytics aimed at exploiting all kinds of digital traces for multiple purposes.This research is funded by the European Research Council (ERC) under the European Union's Seventh Framework Programme (FP7/2007–2013)/ERC grant agreement number 335925

Science Through the “Golden Security Triangle”: Information Security and Data Journeys in Data-intensive Biomedicine.

37th International Conference on Information Systems, Dublin, Ireland, 11-14 December 2016This is the author accepted manuscript. The final version is available from the Association for Information Systems via the URL in this record.This paper talks about ways in which infrastructure for biomedical data-intensive discovery is operationalized. Specifically, it is interested in information security solutions and how the processes of scientific research through data-intensive infrastructures are shaped by them. The implications of information security for big data biomedical research have not been discussed in depth by the extant IS literature. Yet, information security might exert a strong influence on the processes and outcomes of data sharing efforts. In this research-in-progress paper I present a developing, in-depth study of a leading information linkage infrastructure that is representative of the kind of opportunities that big data technologies are occasioning in the medical field. This research calls for IS to extend the discussion to consider, building on the empirical detail of intensive case studies, a whole range of relations between provisions for information security and the processes of scientific research and data work.This research is funded by the European Research Council under the European Union's 7th Framework Programme (FP7/2007-2013) / ERC grant agreement n° 335925

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 the material, social and regulatory landscapes of research. We consider the 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 from the University of Exeter, the London School of Hygiene and Tropical Medicine, the Met Office and Public Health England 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 operationalised 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 re-usability of biomedical data, while encouraging exploratory analyses of secondary data sources

Is the genie out of the bottle? Digital platforms and the future of clinical trials

This is the final version. Available on open access from Taylor & Francis via the DOI in this recordIs it possible to conduct impartial clinical trials in a world full of digital networking tools that patients can use to coordinate themselves and act against research protocols? This paper builds on an ethnography of PatientsLikeMe, a company running an Internet social media network where patients with different conditions share their clinical data with standardised questionnaires. The company faced a serious dilemma in 2011 when some ALS patients, members of the site, started sharing data about a phase II clinical trial of an experimental drug (NP001) in which some of them were participating, to anticipate the experiment’s outcomes and understand each one’s allocation over trial arms. In parallel, some other patients were using the site and other web tools to coordinate and run their own replication of the trial with homebrew mixes of industrial grade chemicals. PatientsLikeMe researchers reflected on their position as networks managers and eventually decided to use the collected data to develop their own analysis of the efficacy of the original compound, and of the homebrewers’ compound. They presented the NP001 events as a case in point for articulating a new social contract for clinical research. This paper analyses these events, first, by understanding the clinical trial as an experiment organisation form that can succeed only as long as its protocol can be enforced; second, we observe how web networks make it dramatically easier for the trial protocol to be violated; finally, we point out how a potentially dangerous confluence of interests over web networks could incubate developments that disrupt the status quo without creating a robust and safe alternative for experimentation. We conclude by warning about the interests of the pharmaceutical industry in exploiting patients’ methodological requests to its own advantage.European Research CouncilEngineering and Physical Sciences Research Council (EPSRC

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

This is the author accepted manuscript. The final version is available from SAGE Publications via the DOI in this record.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 the material, social and regulatory landscapes of research. We consider the 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 from the University of Exeter, the London School of Hygiene and Tropical Medicine, the Met Office and Public Health England 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 operationalised 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 re-usability of biomedical data, while encouraging exploratory analyses of secondary data sources.This research was funded by ERC grant award 335925 (DATA_SCIENCE), the Australian Research Council (Discovery Project DP160102989) and a MEDMI pilot project funded through MEDMI by MRC and NERC (MR/K019341/1)

Patients’ online interventions can scupper clinical trials

This is the author accepted manuscriptAlan Turing Institut

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

This is the author accepted manuscript. The final version is available from Springer via the DOI in this record.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 reuse, 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.This research was funded by ERC grant award 335925 (DATA_SCIENCE), the Australian Research Council (Discovery Project DP160102989), a MEDMI pilot project funded through MEDMI by MRC and NERC (MR/K019341/1) and ESRC project (ES/P011489/1). SL also benefited from the hospitality of the Centre for Logic and Philosophy of Science at the University of Ghent while revising the manuscript

Visual Metaphors: Howardena Pindell, Video Drawings, 1975

This is the final version. Available on open access from Springer via the DOI in this recordClosing reflections on data journeys through the contemplative reading of a visual work by Howardena Pindell

Data curation-research: Practices of data standardization and exploration in a precision medicine database

This is the author accepted manuscript. The final version is available from Taylor & Francis via the DOI in this recordKey to precision medicine is the development of expert database projects that gather data, integrate them in the pre-existing database, and publish the product of their processing for others to make use of. Increasingly, it is required that data infrastructure managers and curators pursue and lead research projects on the data so as to learn about new ways data could be used or information that could be potentially generated from them. I call these efforts ‘data curation-research’ and use the case study of COSMIC, the Catalogue of Somatic Mutations in Cancer, to analyze the contextual factors shaping the science of data curation research. I build on March’s organizational learning categories of exploitation and exploration to place these factors within a theory of organizational change and innovation, and contribute to a richer picture of the social drivers of cancer genomics.Alan Turing Institut