Abstract
Citizen science is an emerging trend with an ever greater number of adherents. It involves the collection and contribution of large amounts of data by private individuals for scientific research. Often such data will concern the individuals themselves and will be collected through processes of self monitoring. This phenomenon has been greatly influenced by the Internet of Things (IoT) and the connectivity of a wide range monitoring devices through the internet. In collecting such data use will often be made of the services of various commercial organisations, for example that offer cloud storage services. The possibility of data portability is extremely important in citizen science as it allows individuals (or data subjects) to be able move their data from one source to another (i. e. to new areas of scientific research). This article explores the limits and possibilities that legal rights to data portability offer, in particular the new right as outlined by the European Union’s General Data Protection Regulation. In doing so this article will look at where this right (and how it operates in the international legal context) is able to facilitate the phenomenon of citizen science.
References
Bellazzi, R., and B. Zupan. 2008. “Predicitive Data Mining in Clinical Medicine: Current Issues and Guidelines.” International Journal of Medical Informatics 77: 81–97.10.1016/j.ijmedinf.2006.11.006Search in Google Scholar
Bonney, R., J. Shirk, T. Phillips, A. Wiggins, H. Ballard, A. Miller-Rushing, and K. Parish. 2014. “What Next for Citizen Science?.” Science 343 (6178): 1436–37.10.1126/science.1251554Search in Google Scholar
Bonney, Rick, Caren B. Cooper, Janis Dickinson, Steve Kelling, Tina Phillips, Kenneth V. Rosenberg, and Jennifer Shirk. 2009. “Citizen Science: A Developing Tool for Expanding Science Knowledge and Scientific Literacy.” BioScience 59(11): 977–84. doi:10.1525/bio.2009.59.11.9.Search in Google Scholar
Devictor, Vincent, Robert J. Whittaker, and Coralie Beltrame. 2010. “Beyond Scarcity: Citizen Science Programmes as Useful Tools for Conservation Biogeography.” Diversity and Distributions 16(3): 354–62. doi:10.1111/j.1472-4642.2009.00615.x.Search in Google Scholar
Dyer, C. 2007. “Stringent Constraints on Use of Patients’ Data are Harming Research.” British Medical Journal 335: 1114–15.10.1136/bmj.39412.352558.DBSearch in Google Scholar
Evans, Barbara J. 2017. “Barbarians at the Gate - Consumer Driven HEalth Data Commons and the Transformation of Citzen Science.” American Journal of Law & Medicine 42(4): 651–85. doi:10.1177/0098858817700245.Search in Google Scholar
Hoffman, S. 2015. “Citizen Science - the Law and the Ethics of Public Access to Medical Big Data.” Berkley Technology Law Journal 30 (3). doi:10.15779/Z385Z78.Search in Google Scholar
Hunter, P. 2016. “The Big Health Data Sale: As the Trade of Personal Health and Medical Data Expands, It Becomes Necessary to Improve Legal Frameworks for Protecting Patient Anonymity, Handling Consent and Ensuring the Quality of Data.” EMBO Rep 17(8): 1103–05. doi:10.15252/embr.201642917.Search in Google Scholar
Jensen, P., L. Jensen, and S. Brunak. 2012. “Mining Electronic Health Records: Towards Better Research Applications and Clinical Care.” Nature Reviews Genetics 13: 395–405.10.1038/nrg3208Search in Google Scholar
Kaye, J. 2012. “The Tension between Data Sharing and the Protection of Privacy in Genomics Research.” Annual Review of Genomics and Human Genetics 13: 415–31.10.1146/annurev-genom-082410-101454Search in Google Scholar
Kelling, S., D. Fink, F. A. La Sorte, A. Johnston, N. E. Bruns, and W. M. Hochachka. 2015. “Taking a ‘Big Data’ Approach to Data Quality in a Citizen Science Project.” Ambio 44(Suppl 4): 601–11. doi:10.1007/s13280-015-0710-4.Search in Google Scholar
Lagos, L. 2013. “Why the Right to Data Portability Likely Reduces Consumer Welfare- Antitrust and Privacy Critique.” Maryland Law Review 72 (2): 341–380.Search in Google Scholar
Lupton, D. 2016. The Quantified Self. Cambridge: John Wiley & Sons.Search in Google Scholar
Madison, M. 2014. “Commons at the Intersection of Peer Production, Citizen Science, and Big Data: Galaxy Zoo.” In Governing Knowledge Commons, edited by B. Frischmann, M. Madison and K. Strandburg. Oxford: Oxford University Press.10.1093/acprof:oso/9780199972036.001.0001Search in Google Scholar
Mantovani, E., and P. Quinn. 2013. “mHealth and Data Protection – The Letter and the Spirit of Consent Legal Requirements.” International Review of Law, Computers & Technology. doi:10.1080/13600869.2013.801581.Search in Google Scholar
Morris, M. E., and A. Aguilera. 2012. “Mobile, Social, and Wearable Computing and the Evolution of Psychological Practice.” Prof Psychol Res Pr 43(6): 622–626. doi:10.1037/a0029041.Search in Google Scholar
Murdoch, T., and A. Detsky. 2013. “The Inevitable Application of Big Data to Health Care.” Journal of the American Medical Association 309 (13): 1351–1352.10.1001/jama.2013.393Search in Google Scholar
Newman, Greg, Andrea Wiggins, Alycia Crall, Eric Graham, Sarah Newman, and Kevin Crowston. 2012. “The Future of Citizen Science: Emerging Technologies and Shifting Paradigms.” Frontiers in Ecology and the Environment 10(6): 298–304. doi:10.1890/110294.Search in Google Scholar
Purcel, R., and K. Rommelfanger. 2017. “Biometric Tracking from Professional Athletes to Consumers.” The American Journal of Bioethics 17 (1): 72–74.10.1080/15265161.2016.1251652Search in Google Scholar
Quinn, P. 2017. “The Anonymisation of Research Data — A Pyric Victory for Privacy that Should Not Be Pushed Too Hard by the EU Data Protection Framework?.” European Journal of Health Law 24. doi:10.1163/15718093-12341416.Search in Google Scholar
Quinn, P., A. Habbig, E. Mantovani, and P. De Hert. 2013. “The Data Protection and Medical Device Frameworks? Obstacles to the Deployment of mHealth across Europe?.” European Journal of Health Law 20 (2): 185–204.10.1163/15718093-12341267Search in Google Scholar
Silvertown, J. 2009. “A New Dawn for Citizen Science.” Trends Ecol Evol 24(9): 467–71. doi:10.1016/j.tree.2009.03.017.Search in Google Scholar
Swan, M. 2013. “The Quantified Self: Fundamental Disruption in Big Data Science and Biological Discovery.” Big Data 1(2): 85–99. doi:10.1089/big.2012.0002.Search in Google Scholar
Tene, O., and J. Polonetsky. 2013. “Big Data for All- Privacy and User Control in the Age of Analytics.” Northwestern Journal of Technology and Intellectual Property 11 (5): 239–74.Search in Google Scholar
© 2018 Walter de Gruyter GmbH, Berlin/Boston
