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Ten simple rules for responsible big data research

Zook, Matthew, Barocas, Solon, Boyd, Danah, Crawford, Kate, Keller, Emily, Gangadharan, Seeta Peña, Goodman, Alyssa, Hollander, Rachelle, Koenig, Barbara A., Metcalf, Jacob, Narayanan, Arvind, Nelson, Alondra and Pasquale, Frank (2017) Ten simple rules for responsible big data research. PLoS Computational Biology, 13 (3). pp. 1-10. ISSN 1553-734X

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Identification Number: 10.1371/journal.pcbi.1005399

Abstract

The use of big data research methods has grown tremendously over the past five years in both academia and industry. As the size and complexity of available datasets has grown, so too have the ethical questions raised by big data research. These questions become increasingly urgent as data and research agendas move well beyond those typical of the computational and natural sciences, to more directly address sensitive aspects of human behavior, interaction, and health. The tools of big data research are increasingly woven into our daily lives, including mining digital medical records for scientific and economic insights, mapping relationships via social media, capturing individuals’ speech and action via sensors, tracking movement across space, shaping police and security policy via “predictive policing,” and much more.

Item Type: Article
Official URL: http://journals.plos.org/ploscompbiol/
Additional Information: © 2017 The Authors © CC0 1.0
Divisions: Media and Communications
Subjects: H Social Sciences > HM Sociology
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Sets: Departments > Media and Communications
Date Deposited: 03 Apr 2017 13:59
Last Modified: 12 Sep 2019 13:27
Projects: IIS-1413864
Funders: National Science Foundation
URI: http://eprints.lse.ac.uk/id/eprint/72161

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