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  1. Big Data, new epistemologies and paradigm shifts.Rob Kitchin - 2014 - Big Data and Society 1 (1).
    This article examines how the availability of Big Data, coupled with new data analytics, challenges established epistemologies across the sciences, social sciences and humanities, and assesses the extent to which they are engendering paradigm shifts across multiple disciplines. In particular, it critically explores new forms of empiricism that declare ‘the end of theory’, the creation of data-driven rather than knowledge-driven science, and the development of digital humanities and computational social sciences that propose radically different ways to make sense of culture, (...)
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  • The ethics of big data: current and foreseeable issues in biomedical contexts.Brent Daniel Mittelstadt & Luciano Floridi - 2016 - Science and Engineering Ethics 22 (2):303–341.
    The capacity to collect and analyse data is growing exponentially. Referred to as ‘Big Data’, this scientific, social and technological trend has helped create destabilising amounts of information, which can challenge accepted social and ethical norms. Big Data remains a fuzzy idea, emerging across social, scientific, and business contexts sometimes seemingly related only by the gigantic size of the datasets being considered. As is often the case with the cutting edge of scientific and technological progress, understanding of the ethical implications (...)
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  • What difference does quantity make? On the epistemology of Big Data in biology.Sabina Leonelli - 2014 - Big Data and Society 1 (1):2053951714534395.
    Is Big Data science a whole new way of doing research? And what difference does data quantity make to knowledge production strategies and their outputs? I argue that the novelty of Big Data science does not lie in the sheer quantity of data involved, but rather in the prominence and status acquired by data as commodity and recognised output, both within and outside of the scientific community and the methods, infrastructures, technologies, skills and knowledge developed to handle data. These developments (...)
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  • Datatrust: Or, the political quest for numerical evidence and the epistemologies of Big Data.Gernot Rieder & Judith Simon - 2016 - Big Data and Society 3 (1).
    Recently, there has been renewed interest in so-called evidence-based policy making. Enticed by the grand promises of Big Data, public officials seem increasingly inclined to experiment with more data-driven forms of governance. But while the rise of Big Data and related consequences has been a major issue of concern across different disciplines, attempts to develop a better understanding of the phenomenon's historical foundations have been rare. This short commentary addresses this gap by situating the current push for numerical evidence within (...)
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  • Big Data: A Revolution That Will Transform How We Live, Work, and Think.[author unknown] - 2013
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  • What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets.Gavin McArdle & Rob Kitchin - 2016 - Big Data and Society 3 (1).
    Big Data has been variously defined in the literature. In the main, definitions suggest that Big Data possess a suite of key traits: volume, velocity and variety, but also exhaustivity, resolution, indexicality, relationality, extensionality and scalability. However, these definitions lack ontological clarity, with the term acting as an amorphous, catch-all label for a wide selection of data. In this paper, we consider the question ‘what makes Big Data, Big Data?’, applying Kitchin’s taxonomy of seven Big Data traits to 26 datasets (...)
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  • How should we do the history of Big Data?David Beer - 2016 - Big Data and Society 3 (1).
    Taking its lead from Ian Hacking’s article ‘How should we do the history of statistics?’, this article reflects on how we might develop a sociologically informed history of Big Data. It argues that within the history of social statistics we have a relatively well developed history of the material phenomenon of Big Data. Yet this article argues that we now need to take the concept of ‘Big Data’ seriously, there is a pressing need to explore the type of work that (...)
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  • The Promise and Perils of Open Medical Data.Sharona Hoffman - 2016 - Hastings Center Report 46 (1):6-7.
    Not long ago I visited the Personal Genome Project's website. The PGP describes its mission as “creating public genome, health, and trait data.” In the “Participant Profiles” section, I found several entries that disclosed the names of individuals along with their date of birth, sex, weight, height, blood type, race, health conditions, medications, allergies, medical procedures, and more. Other profiles did not feature names but provided all of the other details. I had no special access to this information. It is (...)
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