The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts

Science and Engineering Ethics

Volumn 22, Issue 2, 2016, Pages 303-341

  Mittelstadt, Brent Daniel ^a   Floridi, Luciano ^a  

^a UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

Big data; Bioethics; Ethical foresight; Ethics; Information ethics; Medical ethics

Indexed keywords

BIOETHICS; CONFIDENTIALITY; ETHICS; HUMAN; INFORMATION PROCESSING; INFORMED CONSENT; KNOWLEDGE; MEDICAL RESEARCH; ORGANIZATION AND MANAGEMENT; PATIENT RIGHT; PRIVACY; STATISTICS;

BIOETHICAL ISSUES; BIOMEDICAL RESEARCH; CONFIDENTIALITY; DATA COLLECTION; HUMANS; INFORMED CONSENT; KNOWLEDGE; OWNERSHIP; PATIENT ACCESS TO RECORDS; PRIVACY; STATISTICS AS TOPIC;

EID: 84929645967     PISSN: 13533452     EISSN: 14715546     Source Type: Journal    
DOI: 10.1007/s11948-015-9652-2     Document Type: Review

References (127)

1. Advisory Council to Google on the Right to be Forgotten. (2015). Report of the advisory council to google on the right to be forgotten. Google Docs. https://drive.google.com/file/d/0B1UgZshetMd4cEI3SjlvV0hNbDA/view?pli=1&usp=embed_facebook. Accessed 19 Mar 2015.
2. Andrejevic, M. (2014). Big data, big questions the big data divide. International Journal of Communication, 8(0), 17. Accessed 7 Oct 2014.
3. Angrist, M. (2009). Eyes wide open: The personal genome project, citizen science and veracity in informed consent. Personalized Medicine,6, 691–699.
4. Apple. (2014). iBeacon for developers: Apple developer. https://developer.apple.com/ibeacon/. Accessed 17 Nov 2014.
5. Bail, C. A. (2014). The cultural environment: Measuring culture with big data. Theory and Society,43(3–4), 465–482. doi:10.1007/s11186-014-9216-5.
6. Barry, C. A., Stevenson, F. A., Britten, N., Barber, N., & Bradley, C. P. (2001). Giving voice to the lifeworld. More humane, more effective medical care? A qualitative study of doctor-patient communication in general practice. Social Science and Medicine,53, 487–505. doi:10.1016/s0277-9536(00)00351-8.
7. Beauchamp, T. L., & Childress, J. F. (2009). Principles of biomedical ethics. New York: Oxford University Press.
8. Berry, D. M. (2011). The computational turn: Thinking about the digital humanities. Culture Machine, 12(0). ftp://121.171.90.140/big.data/%EB%B9%85%EB%8D%B0%EC%9D%B4%ED%84%B02_20131024_sunup/THE%20COMPUTATIONAL%20TURN%20Digital-Humanities.pdf. Accessed 7 Oct 2014.
9. Bonilla, D. N. (2014). Information Management professionals working for intelligence organizations: Ethics and deontology implications. Security and Human Rights,24(3–4), 264–279. doi:10.1163/18750230-02404005.
10. Booch, G. (2014). The human and ethical aspects of big data. IEEE Software, 31(1), 20–22. Accessed 30 Sept 2014.
11. Bowker, G. C. (2013). Data flakes: An afterword to “Raw Data”is an oxymoron. Raw data” is an oxymoron. Cambridge: MIT Press. http://www.ics.uci.edu/~vid/Readings/bowker_data_flakes.pdf. Accessed 14 Oct 2014.
12. Bowker, G. C. (2014). Big data, big questions the theory/data thing. International Journal of Communication, 8(0), 5. Accessed 7 Oct 2014.
13. Boyd, D., & Crawford, K. (2012). Critical Questions for Big Data: Provocations for a cultural, technological, and scholarly phenomenon. Information Communication & Society,15(5), 662–679. doi:10.1080/1369118X.2012.678878.
14. Boye, N. (2012). Co-production of Health enabled by next generation personal health systems. Studies in health technology and informatics,177, 52–58.
15. Busch, L. (2014). Big data, big questions a dozen ways to get lost in translation: Inherent challenges in large scale data sets. International Journal of Communication, 8(0), 18. Accessed 7 Oct 2014.
16. Butler, D. (2013). When Google got flu wrong. Nature,494(7436), 155–156. doi:10.1038/494155a.
17. Callebaut, W. (2012). Scientific perspectivism: A philosopher of science’s response to the challenge of big data biology. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences,43(1), 69–80. doi:10.1016/j.shpsc.2011.10.007.
18. Cassa, C. A., Wieland, S. C., & Mandl, K. D. (2008). Re-identification of home addresses from spatial locations anonymized by Gaussian skew. International Journal of Health Geographics,7(1), 45. doi:10.1186/1476-072X-7-45.
19. Cheng, L., Shi, C., Wang, X., Li, Q., Wan, Q., Yan, Z., et al. (2013). Chinese biobanks: Present and future. Genetics Research,95(6), 157–164. doi:10.1017/S0016672313000190.
20. Choudhury, S., Fishman, J. R., McGowan, M. L., & Juengst, E. T. (2014). Big data, open science and the brain: Lessons learned from genomics. Frontiers in Human Neuroscience,8, 239. doi:10.3389/fnhum.2014.00239.
21. Clayton, E. W. (2005). Informed consent and biobanks. Journal of Law, Medicine & Ethics,33(1), 15–21. doi:10.1111/j.1748-720X.2005.tb00206.x.
22. Coll, S. (2014). Power, knowledge, and the subjects of privacy: Understanding privacy as the ally of surveillance. Information Communication & Society,17(10), 1250–1263. doi:10.1080/1369118X.2014.918636.
23. Collingridge, D. (1980). The social control of technology. Palgrave Macmillan.
24. Costa, F. F. (2014). Big data in biomedicine. Drug Discovery Today,19(4), 433–440. doi:10.1016/j.drudis.2013.10.012.
25. Craig, T. (2011). Privacy and big data. Sebastopol; Cambridge: O’Reilly.
26. Crawford, K. (2013). The hidden biases in big data. Harvard Business Review. http://blogs.hbr.org/2013/04/the-hidden-biases-in-big-data/. Accessed 10 Oct 2014.
27. Crawford, K., Gray, M. L., & Miltner, K. (2014). Critiquing big data: Politics, ethics, epistemology special section introduction. International Journal of Communication, 8, 10. Accessed 2 Oct 2014.
28. Currie, J. (2013). “Big Data” Versus “Big Brother”: On the appropriate use of large-scale data collections in pediatrics. Pediatrics,131(Supplement), S127–S132. doi:10.1542/peds.2013-0252c.
29. Davis, K. (2012). Ethics of big data. O’Reilly Media, Inc.
30. Dereli, T., Coskun, Y., Kolker, E., Guner, O., Agirbasli, M., & Ozdemir, V. (2014). Big data and ethics review for health systems research in LMICs: Understanding risk, uncertainty and ignorance-and catching the black swans? American Journal of Bioethics,14(2), 48–50. doi:10.1080/15265161.2013.868955.
31. Devos, Y., Maeseele, P., Reheul, D., Van Speybroeck, L., & De Waele, D. (2008). Ethics in the societal debate on genetically modified organisms: A (Re)Quest for sense and sensibility. Journal of Agricultural and Environmental Ethics,21(1), 29–61. doi:10.1007/s10806-007-9057-6.
32. Docherty, A. (2014). Big data: Ethical perspectives. Anaesthesia,69(4), 390–391. doi:10.1111/anae.12656.
33. Dove, E. S., Knoppers, B. M., & Zawati, M. H. (2014). Towards an ethics safe harbor for global biomedical research. Journal of Law and the Biosciences,1(1), 3–51. doi:10.1093/jlb/lst002.
34. Enjolras, B. (2014). Big Data and social research: New possibilities and ethical challenges. Tidsskrift for Samfunnsforskning,55(1), 80–89.
35. EURORDIS. (2013). Statement on the EP Report on the Protection of Personal Data. http://www.publichealth.ox.ac.uk/helex/Statement%20Data%20Prot%20FINAL.pdf. Accessed 22 Oct 2014.
36. Fairfield, J., & Shtein, H. (2014). Big data, big problems: Emerging issues in the ethics of data science and journalism. Journal of Mass Media Ethics,29(1), 38–51. doi:10.1080/08900523.2014.863126.
37. Fan, W., & Bifet, A. (2013). Mining big data: Current status, and forecast to the future. ACM SIGKDD Explorations Newsletter, 14(2), 1–5. Accessed 2 Oct 2014.
38. Floridi, L. (2008). The method of levels of abstraction. Minds and Machines,18(3), 303–329. doi:10.1007/s11023-008-9113-7.
39. Floridi, L. (2012). Big data and their epistemological challenge. Philosophy & Technology,25(4), 435–437. doi:10.1007/s13347-012-0093-4.
40. Floridi, L. (2013). The philosophy of information (Reprint ed.). Oxford: OUP Oxford.
41. Floridi, L. (Ed.). (2014a). The onlife manifesto. New York: Springer. http://www.springer.com/philosophy/epistemology+and+philosophy+of+science/book/978-3-319-04092-9. Accessed 2 Dec 2014.
42. Floridi, L. (2014b). Open data, data protection, and group privacy. Philosophy & Technology,27(1), 1–3. doi:10.1007/s13347-014-0157-8.
43. Gadamer, H. G. (1976). The historicity of understanding. Harmondsworth: Penguin Books Ltd.
44. Gadamer, H. G. (2004). Truth and method. London: Continuum International Publishing Group.
45. General Medical Council. (2008). Consent guidance. http://www.gmc-uk.org/guidance/ethical_guidance/consent_guidance_index.asp.
46. Gilligan, C. (1982). In a different voice. Cambridge: Harvard University Press.
47. Goodman, E. (2014). Design and ethics in the era of big data. Interactions, 21(3), 22–24. Accessed 1 Oct 2014.
48. Habermas, J. (1984). The theory of communicative action. Volume 1: Reason and the rationalization of society. Boston: Beacon.
49. Habermas, J. (1985). The theory of communicative action. Volume 2: Lifeworld and system: A critique of functionalist reason. Boston: Beacon.
50. Hansson, M. G. (2009). Ethics and biobanks. British Journal of Cancer,100(1), 8–12. doi:10.1038/sj.bjc.6604795.
51. Harris, J. (2005). Scientific research is a moral duty. Journal of Medical Ethics,31(4), 242–248. doi:10.1136/jme.2005.011973.
52. Hay, M., Miklau, G., Jensen, D., Towsley, D., & Weis, P. (2008). Resisting structural re-identification in anonymized social networks. Proceedings of the VLDB Endowment,1(1), 102–114. doi:10.14778/1453856.1453873.
53. Hayden, E. C. (2012). A broken contract. NATURE PUBLISHING GROUP MACMILLAN BUILDING, 4 CRINAN ST, LONDON N1 9XW, ENGLAND. http://environmentportal.in/files/file/informed%20consent.pdf. Accessed 7 Oct 2014.
54. Heidegger, M. (1967). Being and time. Oxford: Blackwell.
55. Helbing, D., & Balietti, S. (2011). From social data mining to forecasting socio-economic crises. European Physical Journal-Special Topics,195(1), 3–68. doi:10.1140/epjst/e2011-01401-8.
56. Higuchi, N. (2013). Three challenges in advanced medicine. Japan Medical Association Journal,56(6), 437–447.
57. Hoffman, S. (2014). Citizen science: The law and ethics of public access to medical big data (SSRN Scholarly Paper No. ID 2491054). Rochester, NY: Social Science Research Network. http://papers.ssrn.com/abstract=2491054. Accessed 13 Oct 2014.
58. Hoffman, S., & Podgurski, A. (2013). Big bad data: Law, public health, and biomedical databases. Journal of Law, Medicine and Ethics,41(Suppl. 1), 56–60. doi:10.1111/jlme.12040.
59. IBM. (2014). The four V’s of big data. http://www.ibmbigdatahub.com/infographic/four-vs-big-data. Accessed 23 Oct 2014.
60. Ioannidis, J. P. A. (2013). Informed consent, big data, and the oxymoron of research that is not research. American Journal of Bioethics,13(4), 40–42. doi:10.1080/15265161.2013.768864.
61. Joly, Y., Dove, E. S., Knoppers, B. M., Bobrow, M., & Chalmers, D. (2012). Data sharing in the post-genomic world: The experience of the international cancer genome consortium (ICGC) data access compliance office (DACO). PLoS Computational Biology,8(7), e1002549. doi:10.1371/journal.pcbi.1002549.
62. Kass, N. E. (2001). An ethics framework for public health. American Journal of Public Health,91(11), 1776–1782. doi:10.2105/AJPH.91.11.1776.
63. Kaye, J., Curren, L., Anderson, N., Edwards, K., Fullerton, S. M., Kanellopoulou, N., et al. (2012). From patients to partners: Participant-centric initiatives in biomedical research. Nature Reviews Genetics,13(5), 371–376. doi:10.1038/nrg3218.
64. Knobel, C. P. (2010). Ontic occlusion and exposure in sociotechnical systems. University of Pittsburgh. Retrieved from http://deepblue.lib.umich.edu/handle/2027.42/78763.
65. Krotoski, A. K. (2012). Data-driven research: Open data opportunities for growing knowledge, and ethical issues that arise. Insights: The UKSG Journal,25(1), 28–32. doi:10.1629/2048-7754.25.1.28.
66. Laney, D. (2001). 3D data management: Controlling data volume, velocity and variety. META Group Research Note, 6.
67. Larson, E. B. (2013). Building trust in the power of “big data” research to serve the public good. JAMA,309(23), 2443–2444. doi:10.1001/jama.2013.5914.
68. Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A.-L., Brewer, D., et al. (2009). Computational social science. Science,323(5915), 721–723. doi:10.1126/science.1167742.
69. Lewis, C. M., Obregón-Tito, A., Tito, R. Y., Foster, M. W., & Spicer, P. G. (2012). The Human Microbiome Project: Lessons from human genomics. Trends in Microbiology,20(1), 1–4. doi:10.1016/j.tim.2011.10.004.
70. Liyanage, H., de Lusignan, S., Liaw, S.-T., Kuziemsky, C. E., Mold, F., Krause, P., et al. (2014). Big data usage patterns in the health care domain: A use case driven approach applied to the assessment of vaccination benefits and risks. Contribution of the IMIA Primary Healthcare Working Group. Yearbook of medical informatics, 9(1), 27–35. doi:10.15265/IY-2014-0016.
71. Lomborg, S., & Bechmann, A. (2014). Using APIs for data collection on social media. Information Society,30(4), 256–265. doi:10.1080/01972243.2014.915276.
72. Lupton, D. (2014). The commodification of patient opinion: The digital patient experience economy in the age of big data. Sociology of Health & Illness,36(6), 856–869. doi:10.1111/1467-9566.12109.
73. Lynch, C. (2008). Big data: How do your data grow? Nature,455(7209), 28–29. doi:10.1038/455028a.
74. Lyon, D. (2003). Surveillance as social sorting: Privacy, risk, and digital discrimination. London: Routledge.
75. MacIntyre, A. (2007). After virtue: A study in moral theory (3rd ed.). London: Gerald Duckworth & Co Ltd.
76. Mahajan, R. L., Reed, J., Ramakrishnan, N., Mueller, R., Williams, C. B., & Campbell, T. A. (2012). Cultivating emerging and black swan technologies (Vol. 6, pp. 549–557). Presented at the ASME international mechanical engineering congress and exposition, proceedings (IMECE). doi:10.1115/IMECE2012-89339
77. Majumder, M. A. (2005). Cyberbanks and other virtual research repositories. Journal of Law, Medicine & Ethics,33(1), 31–39. doi:10.1111/j.1748-720X.2005.tb00208.x.
78. Markowetz, A., Błaszkiewicz, K., Montag, C., Switala, C., & Schlaepfer, T. E. (2014). Psycho-Informatics: Big Data shaping modern psychometrics. Medical Hypotheses,82(4), 405–411. doi:10.1016/j.mehy.2013.11.030.
79. Master, Z., Campo-Engelstein, L., & Caulfield, T. (2014). Scientists’ perspectives on consent in the context of biobanking research. European Journal of Human Genetics. doi:10.1038/ejhg.2014.143.
80. Mathaiyan, J., Chandrasekaran, A., & Davis, S. (2013). Ethics of genomic research. Perspectives in Clinical Research,4(1), 100. doi:10.4103/2229-3485.106405.
81. McGuire, A. L., Achenbaum, L. S., Whitney, S. N., Slashinski, M. J., Versalovic, J., Keitel, W. A., et al. (2012). Perspectives on human microbiome research ethics. Journal of Empirical Research on Human Research Ethics: An International Journal,7(3), 1–14. doi:10.1525/jer.2012.7.3.1.
82. McGuire, A. L., Colgrove, J., Whitney, S. N., Diaz, C. M., Bustillos, D., & Versalovic, J. (2008). Ethical, legal, and social considerations in conducting the Human Microbiome Project. Genome Research,18(12), 1861–1864. doi:10.1101/gr.081653.108.
83. McNeely, C. L., & Hahm, J. (2014). The Big (Data) Bang: Policy, prospects, and challenges. Review of Policy Research,31(4), 304–310. doi:10.1111/ropr.12082.
84. Mello, M. M., Francer, J. K., Wilenzick, M., Teden, P., Bierer, B. E., & Barnes, M. (2013). Preparing for responsible sharing of clinical trial data. New England Journal of Medicine,369(17), 1651–1658. doi:10.1056/NEJMhle1309073.
85. Mittelstadt, B. D., Fairweather, N. B., McBride, N., & Shaw, M. (2011). Ethical issues of personal health monitoring: A literature review. In ETHICOMP 2011 conference proceedings (pp. 313–321). Presented at the ETHICOMP 2011, Sheffield, UK.
86. Mittelstadt, B. D., Fairweather, N. B., McBride, N., & Shaw, M. (2013). Privacy, risk and personal health monitoring. In ETHICOMP 2013 conference proceedings (pp. 340–351). Presented at the ETHICOMP 2013, Kolding, Denmark.
87. Mittelstadt, B. D., Fairweather, N. B., Shaw, M., & McBride, N. (2014). The ethical implications of personal health monitoring. International Journal of Technoethics,5(2), 37–60.
88. Mittelstadt, B. D., Stahl, B. C., & Fairweather, N. B. (2015). How to shape a better future? Epistemic difficulties for ethical assessment and anticipatory governance of emerging technologies. Ethical Theory and Moral Practice, 1–21. doi:10.1007/s10677-015-9582-8.
89. Moor, J. (1985). What is computer ethics?*. Metaphilosophy,16(4), 266–275. doi:10.1111/j.1467-9973.1985.tb00173.x.
90. Moore, P., Xhafa, F., Barolli, L., & Thomas, A. (2013). Monitoring and detection of agitation in dementia towards real-time and big-data solutions. 2013 Eighth international conference on P2p, parallel, grid, cloud and internet computing (3pgcic 2013), pp 128–135. doi:10.1109/3PGCIC.2013.26
91. Mora, F. (2012). The demise of google health and the future of personal health records. International Journal of Healthcare Technology and Management, 13(5), 363–377. Accessed 11 Nov 2014.
92. National Science Foundation. (2014). Critical techniques and technologies for advancing big data science & engineer (BIGDATA): Program Solicitation NSF 14-543. http://www.nsf.gov/pubs/2014/nsf14543/nsf14543.pdf. Accessed 17 Oct 2014.
93. NHS England (2014). NHS England. The care.data programme: better information means better care. http://www.england.nhs.uk/ourwork/tsd/care-data/. Accessed 11 Nov 2014.
94. Niemeijer, A. R., Frederiks, B. J., Riphagen, I. I., Legemaate, J., Eefsting, J. A., & Hertogh, C. M. (2010). Ethical and practical concerns of surveillance technologies in residential care for people with dementia or intellectual disabilities: An overview of the literature. International Psychogeriatrics,22, 1129–1142.
95. Nissenbaum, H. (2004). Privacy as contextual integrity (SSRN Scholarly Paper No. ID 534622). Rochester, NY: Social Science Research Network. http://papers.ssrn.com/abstract=534622. Accessed 12 Mar 2013.
96. Noddings, N. (2013). Caring: A relational approach to ethics and moral education. Berkeley: University of California Press.
97. Nuffield Council on Bioethics. (2015). The collection, linking and use of data in biomedical research and health care: Ethical issues (p. 198). Nuffield Council on Bioethics. http://nuffieldbioethics.org/wp-content/uploads/Biological_and_health_data_web.pdf.
98. Nunan, D., & Di Domenico, M. (2013). Market research and the ethics of big data. International Journal of Market Research,55(4), 505. doi:10.2501/IJMR-2013-015.
99. Oboler, A., Welsh, K., & Cruz, L. (2012a). The danger of big data: Social media as computational social science. First Monday, 17(7). https://www.scopus.com/inward/record.url?eid=2-s2.0-84867308941&partnerID=40&md5=0e4cb2f657154c7f82a76c2a657259ab.
100. Oboler, A., Welsh, K., & Cruz, L. (2012b). The danger of big data: Social media as computational social science. First Monday, 17(7). http://journals.uic.edu/ojs/index.php/fm/article/view/3993. Accessed 1 Oct 2014.
101. Pariser, E. (2011). The filter bubble: What the Internet is hiding from you. London: Viking.
102. Patterson, M. E., & Williams, D. R. (2002). Collecting and analyzing qualitative data: Hermeneutic principles, methods and case examples (Vol. 9). Champaign, IL: Sagamore Publishing, Inc. http://www.treesearch.fs.fed.us/pubs/29421. Accessed 7 Nov 2012.
103. Pellegrino, E. D., & Thomasma, D. C. (1993). The virtues in medical practice. New York: Oxford University Press.
104. Prainsack, B., & Buyx, A. (2013). A solidarity-based approach to the governance of research biobanks. Medical Law Review,21(1), 71–91. doi:10.1093/medlaw/fws040.
105. Puschmann, C., & Burgess, J. (2014). Big data, big questions metaphors of big data. International Journal of Communication, 8(0), 20. Accessed 7 Oct 2014.
106. Reuters. (2014, October 3). Facebook plots first steps into healthcare. http://www.telegraph.co.uk/technology/facebook/11139606/Facebook-plots-first-steps-into-healthcare.html. Accessed 15 Nov 2014.
107. Richards, N. M., & King, J. H. (2013). Three paradoxes of big data. Stanford Law Review Online, 66, 41. Accessed 18 Feb 2015.
108. Rothstein, M. A., & Shoben, A. B. (2013). An unbiased response to the open peer commentaries on “Does Consent Bias Research?”. The American Journal of Bioethics,13(4), W1–W4. doi:10.1080/15265161.2013.769824.
109. Safran, C., Bloomrosen, M., Hammond, W. E., Labkoff, S., Markel-Fox, S., Tang, P. C., et al. (2006). Toward a national framework for the secondary use of health data: An American medical informatics association white paper. Journal of the American Medical Informatics Association,14(1), 1–9. doi:10.1197/jamia.M2273.
110. Schadt, E. E. (2012). The changing privacy landscape in the era of big data. Molecular Systems Biology, 8. doi:10.1038/msb.2012.47
111. Schaefer, G. O., Emanuel, E. J., & Wertheimer, A. (2009). The obligation to participate in biomedical research. JAMA, 302(1), 67–72. Accessed 19 Mar 2015.
112. Schroeder, R. (2014). Big data and the brave new world of social media research. Big Data & Society, 1(2). doi:10.1177/2053951714563194
113. Schroeder, R., & Cowls, J. (2014). Big data, ethics, and the social implications of knowledge production. http://dataethics.github.io/proceedings/BigDataEthicsandtheSocialImplicationsofKnowledgeProduction.pdf. Accessed 2 Oct 2014.
114. Schwandt, T. A. (2000). Three epistemological stances for qualitative inquiry: Interpretivism, hermeneutics, and social constructionism. Handbook of qualitative research (pp. 189–214). Thousand Oaks, CA: Sage.
115. Shilton, K. (2012). Participatory personal data: An emerging research challenge for the information sciences. Journal of the American Society for Information Science and Technology,63(10), 1905–1915. doi:10.1002/asi.22655.
116. Slashinski, M. J., McCurdy, S. A., Achenbaum, L. S., Whitney, S. N., & McGuire, A. L. (2012). “Snake-oil,”“quack medicine,” and “industrially cultured organisms:” biovalue and the commercialization of human microbiome research. BMC medical ethics, 13(1), 28. Accessed 13 Oct 2014.
117. Slote, M. (2007). The ethics of care and empathy (New Ed edition.). London, New York: Routledge.
118. Steinsbekk, K. S., Ursin, L. Ø., Skolbekken, J.-A., & Solberg, B. (2013). We’re not in it for the money—lay people’s moral intuitions on commercial use of “their” biobank. Medicine, Health Care and Philosophy,16(2), 151–162. doi:10.1007/s11019-011-9353-9.
119. Taylor, L., & Floridi, L. (Eds.). (2015). Group privacy: New challenges of data technologies. New York: Springer (forthcoming).
120. Tene, O., & Polonetsky, J. (2013). Big data for all: Privacy and user control in the age of analytics. http://heinonlinebackup.com/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/nwteintp11§ion=20. Accessed 2 Oct 2014.
121. Terry, N. (2012). Protecting patient privacy in the age of big data. UMKC L. Rev., 81, 385. Accessed 2 Oct 2014.
122. Terry, N. (2014). Health privacy is difficult but not impossible in a post-hipaa data-driven world. Chest,146(3), 835–840. doi:10.1378/chest.13-2909.
123. The NIH HMP Working Group, Peterson, J., Garges, S., Giovanni, M., McInnes, P., Wang, L., et al. (2009). The NIH human microbiome project. Genome Research,19(12), 2317–2323. doi:10.1101/gr.096651.109.
124. van den Berg, B., & van der Hof, S. (2012). What happens to my data? A novel approach to informing users of data processing practices. First Monday, 17(7). doi:10.5210/fm.v17i7.4010
125. van der Sloot, B. 2014. Privacy in the Post-NSA Era: Time for a fundamental revision? http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2432104. Accessed 17 Feb 2015.
126. Watson, R. W. G., Kay, E. W., & Smith, D. (2010). Integrating biobanks: Addressing the practical and ethical issues to deliver a valuable tool for cancer research. Nature Reviews Cancer,10(9), 646–651. doi:10.1038/nrc2913.
127. Wellcome Trust. (2013). Impact of the draft European data protection regulation and proposed amendments from the rapporteur of the LIBE committee on scientific research. Wellcome Trust. http://www.wellcome.ac.uk/stellent/groups/corporatesite/@policy_communications/documents/web_document/WTP055584.pdf. Accessed 22 Oct 2014.