Evolution of regulatory models for public health data ecosystems from a linked democracy perspective
Abstract
Public healthcare is a data-intensive environment that manages ever-increasing volumes of biomedical data resulting from medical data-generating technologies. In this paper, the authors discuss strategies to regulate the collection and use of biomedical data and metadata to build sustainable public health data ecosystems; this can assist citizens to get control of dataflows by defining identity in the public domain and shaping the capacity to use the web of data: get access to healthcare services and receive benefits and appropriate care. The authors suggest that a strategy based on the linked democracy governance model and safeguards, implemented through the meta-rule of law, enables better design of regulatory tools to handle semantically driven data flows. This strategy ties well in with models of deliberative and epistemic democracy, focused on relationships between people, data, and institutions. The authors investigate privacy, security, and data protection issues, applying existing ethical and legal frameworks for public health data and the theory of justice; they discuss the implementation of strategies to articulate the public domain and propose intermediate, anchoring institutions at the meso-level by building ontologies, selecting technical functionalities and algorithms, and embedding protections of the rule of law into specific public health data ecosystems.
Keyword : public health data ecosystems, linked democracy governance model, privacy, data protection, meta-rule of law, web of data, Electronic Health Record (EHR), identity
How to Cite
Lokshina, I., & Lanting, C. (2023). Evolution of regulatory models for public health data ecosystems from a linked democracy perspective. New Trends in Computer Sciences, 1(2), 70–96. https://doi.org/10.3846/ntcs.2023.19166
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Aizenberg, E., & van den Hoven, J. (2020). Designing for human rights in AI. Big Data & Society, 7(2). https://doi.org/10.1177/2053951720949566
Badawi, O., Brennan, T., Celi, L., Feng, M., Ghassemi, M., Ippolito, A., Johnson, A., Mark, R., Mayaud, L., Moody, G., Moses, C, Naumann, T., Nikore, V., Pimentel, M., Pollard, T., Santos, M., Stone, D., & Zimolzak, A. (2014, August). Making big data useful for health care: A summary of the inaugural MIT Critical Data Conference. JMIR Medical Informatics, 2(2), Article e22. https://doi.org/10.2196/medinform.3447
Barrett, M., Humblet, O., Hiatt, R., & Adler, N. (2013). Big Data and disease prevention: from qualified self to quantified communities. Big Data, 1(3), 168–175. https://doi.org/10.1089/big.2013.0027
Berners-Lee, T. (2007, November). Giant global graph. https://web.archive.org/web/20160713021037/http://dig.csail.mit.edu/breadcrumbs/node/215
Boddington, P. (2016). Big data, small talk: Lessons from the ethical practices of interpersonal communication for the management of biomedical Big Data. In B. Mittelstadt & L. Floridi (Eds.), Law, governance and technology series: Vol. 29. The ethics of biomedical data. (pp. 277–305). Springer. https://doi.org/10.1007/978-3-319-33525-4_13
Bohman, J. (2009). Epistemic value and deliberative democracy. The Good Society, 18(2), 28–34. https://doi.org/10.1353/gso.0.0079
Bruggemann, T., Hansen, J., Dehling, T., & Sunyaev, A. (2016, September). An information privacy risk index for mHealth apps. Proceedings Annual Privacy Forum 2016. SSRN. https://doi.org/10.1007/978-3-319-44760-5_12
Casanovas, P. (2015). Semantic web regulatory models: Why ethics matter. Philosophy and Technology, 28(1), 33–55. https://doi.org/10.1007/s13347-014-0170-y
Casanovas, P., Mendelson, D., & Poblet, M. (2017). A linked democracy approach for regulating public health data. Health Technology, 7, 519–537. https://doi.org/10.1007/s12553-017-0191-5
Casanovas, P., Hashmi, M., & de Koker, L. (2021). The rule of law and compliance: Legal quadrant and conceptual clustering. In V. Rodríguez-Doncel, M. Palmirani, M. Araszkiewicz, P. Casanovas, U. Pagallo, & G. Sartor (Eds.), Lecture notes in computer science: Vol. 13048. AI approaches to the complexity of legal systems XI-XII. AICOL AICOL XAILA 2020 2018 2020 (pp. 215–229). Springer. https://doi.org/10.1007/978-3-030-89811-3_15
Casanovas, P., & Poblet, M. (2021). Adding semantics to the legal domain. La Trobe. https://doi.org/10.26181/61109185d2007
Casanovas, P., Gonzalez-Conejero, J., & de Koker, L. (2023). Legal compliance by design (LCbD) and through design (LCtD): Preliminary Survey. La Trobe. https://doi.org/10.26181/22910891.v1
Cavoukian, A., & Chibba, M. (2016). Cognitive cities, Big Data, and citizen participation: The essentials of privacy and security. In E. Portmann & M. Finger (Eds.), Studies in systems, decision and control: Vol. 63. Towards cognitive cities (pp. 61–82). Springer, Cham. https://doi.org/10.1007/978-3-319-33798-2_4
Chun, S., & MacKellar, B. (2012, March). Social health data integration using semantic web. In SAC ‘12: Proceedings of the 27th annual ACM symposium on applied computing (pp. 392–397). https://doi.org/10.1145/2245276.2245351
Colesky, M., Hoepman, J., & Hillan, C. (2016). Critical analysis of privacy design strategies. 2016 IEEE Security and Privacy Workshops (SPW) (pp. 33–40). https://doi.org/10.1109/SPW.2016.23
Estlund, D. (2008). Epistemic approaches to democracy. Episteme: A Journal of Social Epistemology, 5(1), 1–4. https://doi.org/10.3366/E1742360008000191
Gharib, M., Giorgini, P., & Mylopoulos, J. (2016). Ontologies for privacy requirements engineering: A systematic literature review. ArXiv. https://doi.org/10.48550/arXiv.1811.12621
Gillespie, T. (2014, October). The relevance of algorithms. in T. Gillespie, P. J. Boczkowski, & K. A. Foot (Eds.), Media technologies: Essays on communication, materiality, and society. MIT Press. https://doi.org/10.7551/mitpress/9780262525374.001.0001
Gronlund, K., Bachtiger, A., & Setalas, M. (2014). Deliberative mini-publics: Involving citizens in the democratic process. ECPR Press.
Gutwirth, R., & Leenes, P. (2016). Data protection on the move. Current developments in ICT and privacy/data protection. Springer. https://doi.org/10.1007/978-94-017-7376-8
Hardy, Q. (2016, June). The web’s creator looks to reinvent it. New York Times. https://www.nytimes.com/2016/06/08/technology/the-webs-creator-looks-to-reinvent-it.html
Hockings, E. (2016). Critical examination of policy. Developments in information governance and biosciences. In B. Mittelstadt, & L. Floridi (Eds.), Law, governance and technology series: Vol. 29. The ethics of biomedical Big Data (pp. 95–115). Springer. https://doi.org/10.1007/978-3-319-33525-4_5
Klitou, D. (2012). A solution, but not a panacea for defending privacy: challenges, criticism, and limitations of privacy by design. In B. Preneel & D. Ikonomou (Eds.), Lecture notes in computer science: Vol. 8319. Privacy technologies and policy. APF 2012 pp. 86–110). Springer. https://doi.org/10.1007/978-3-642-54069-1_6
Koops, B.-J., & Leenes, R. (2014). Privacy regulation cannot be hardcoded. A critical comment on the “privacy by design” provision in data-protection law. International Review of Law, Computers, and Technology, 28(2), 159–171. https://doi.org/10.1080/13600869.2013.801589
Kuyper, J. (2015). Democratic deliberation in the modern world: The systemic turn. Critical Review, 27(1), 49–63. https://doi.org/10.1080/08913811.2014.993891
Landemore, H. (2013). Democratic reason: Politics, collective intelligence, and the rule of the many. Princeton University Press. https://doi.org/10.23943/princeton/9780691155654.001.0001
Lokshina, I., & Lanting, C. (2018). Addressing ethical concerns of Big Data as a prerequisite for a sustainable Big Data industry. International Journal of Interdisciplinary Telecommunications and Networking, 10(3), 33–54. https://doi.org/10.4018/IJITN.2018070104
Lokshina, I., Lanting, C., & Durkin, B. (2018). IoT- and Big Data-driven data analysis services for third parties, strategic implications, and business opportunities. International Journal of Social Ecology and Sustainable Development, 9(3), 34–52. https://doi.org/10.4018/IJSESD.2018070103
Lokshina, I., Gregus, M., & Thomas, W. (2019). Application of integrated building information modeling, IoT and blockchain technologies in system design of a smart building. Procedia Computer Science, 160, 497–502. https://doi.org/10.1016/j.procs.2019.11.058
Lokshina, I., & Lanting, C. (2019). A qualitative evaluation of IoT-driven eHealth: knowledge management, business models and opportunities, deployment, and evolution. In N. Kryvinska & M. Gregus (Eds.), Lecture notes on data engineering and communications technologies: Vol. 20. Data-centric business and applications (pp. 23–52). Springer. https://doi.org/10.1007/978-3-319-94117-2_2
Lokshina, I., Lanting, C., & Durkin, B. (2020). Evaluation of strategic opportunities and resulting business models for SMEs: Employing IoT in their data-driven ecosystems. In M. Jennex (Eds.), Knowledge management, innovation, and entrepreneurship in a changing world (pp. 148–186). IGI Global. https://doi.org/10.4018/978-1-7998-2355-1.ch007
Lokshina, I., & Lanting, C. (2021). A study on the wide-ranging ethical implications of Big Data technology in a digital society: How likely are data accidents during COVID-19? Journal of Business Ecosystems, 2(1), 32–57. https://doi.org/10.4018/JBE.2021010103
Lokshina, I., & Lanting, C. (2023). Development of public health data regulatory models from a linked democracy perspective. In P. Geril & M. Polanska (Eds.), Science fiction prototyping conference (pp. 21–28). EUROSIS-ETI. Ghent, Belgium.
Luo, J., Wu, M., Gopukumar, D., & Zhao, Y. (2016). Big data application in biomedical research and healthcare: A literature review. Biomedical Informatics Insights, 8, 1–10. https://doi.org/10.4137/BII.S31559
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. https://doi.org/10.1111/1467-9566.12109
Mathews, R. (2016). On protecting and preserving personal privacy in interoperable global healthcare venues. Health Technology, 6, 53–73. https://doi.org/10.1007/s12553-016-0126-6
Mendelson, D., & Wolf, G. (2016, December). “My electronic health record” – cui bono (for whose benefit)? 24 Journal of Law and Medicine. SSRN. https://ssrn.com/abstract=2881787
Mendelson, D., & Mendelson, D. (2017). Legal protections for personal health information in the age of Big Data – a proposal for regulatory framework. Ethics, Medicine and Public Health, 3(1), 37–55. https://doi.org/10.1016/j.jemep.2017.02.005
Mendelson, D. (2020). National electronic health record systems and consent to processing of health data in the European Union and Australia. In M. Corrales Compagnucci, N. Forgo, T. Kono, S. Teramoto, & E. Vermeulen (Eds.), Legal tech and the new sharing economy. Perspectives in law, business and innovation (pp. 115–131). Springer. https://doi.org/10.1007/978-981-15-1350-3_6
Middleton, K. (2016, October). Millions of Australians caught in health records breach. The Saturday Paper. https://www.thesaturdaypaper.com.au/news/politics/2016/10/08/millions-australians-caught-health-records-breach/14758452003833
Mittelstadt, B., & Floridi, L. (2016, April). The ethics of Big Data: Current and foreseeable issues in biomedical contexts. Science and Engineering Ethics, 22(2), 303–341. https://doi.org/10.1007/s11948-015-9652-2
Nissenbaum, H. (2010). Privacy in context: Technology, policy, and the integrity of social life. Stanford University Press. https://doi.org/10.1515/9780804772891
Pagallo, U., Casanovas, P., & Madelin, R. (2019). The middle-out approach: Assessing models of legal governance in data protection, artificial intelligence, and the web of data. The Theory and Practice of Legislation, 7(1), 1–25. https://doi.org/10.1080/20508840.2019.1664543
Schwartzberg, M. (2015). Epistemic democracy and its challenges. Annual Review of Political Science, 18, 187–203. https://doi.org/10.1146/annurev-polisci-110113-121908
Staab, S., & Studer, R. (2003). Handbook on ontologies. Springer Science Business Media. https://doi.org/10.1007/978-3-540-24750-0
Stevens, L. (2017, March). Big read: What does Google DeepMind want with the NHS? Digital Health. https://www.digitalhealth.net/2017/03/deepmind-mustafa-suleyman-interview
UNESCO. (2005, October). Universal declaration on bioethics and human rights.
Walzer, M. (1984). Liberalism and the art of separation. Political Theory, 12(3), 315–330. https://doi.org/10.1177/0090591784012003001
Woods, S. (2016). Big Data governance: solidarity and the patient voice. In B. Mittelstadt & L. Floridi (Eds.), Law, governance and technology series: Vol. 29. The ethics of biomedical big data. Springer. https://doi.org/10.1007/978-3-319-33525-4_10
Badawi, O., Brennan, T., Celi, L., Feng, M., Ghassemi, M., Ippolito, A., Johnson, A., Mark, R., Mayaud, L., Moody, G., Moses, C, Naumann, T., Nikore, V., Pimentel, M., Pollard, T., Santos, M., Stone, D., & Zimolzak, A. (2014, August). Making big data useful for health care: A summary of the inaugural MIT Critical Data Conference. JMIR Medical Informatics, 2(2), Article e22. https://doi.org/10.2196/medinform.3447
Barrett, M., Humblet, O., Hiatt, R., & Adler, N. (2013). Big Data and disease prevention: from qualified self to quantified communities. Big Data, 1(3), 168–175. https://doi.org/10.1089/big.2013.0027
Berners-Lee, T. (2007, November). Giant global graph. https://web.archive.org/web/20160713021037/http://dig.csail.mit.edu/breadcrumbs/node/215
Boddington, P. (2016). Big data, small talk: Lessons from the ethical practices of interpersonal communication for the management of biomedical Big Data. In B. Mittelstadt & L. Floridi (Eds.), Law, governance and technology series: Vol. 29. The ethics of biomedical data. (pp. 277–305). Springer. https://doi.org/10.1007/978-3-319-33525-4_13
Bohman, J. (2009). Epistemic value and deliberative democracy. The Good Society, 18(2), 28–34. https://doi.org/10.1353/gso.0.0079
Bruggemann, T., Hansen, J., Dehling, T., & Sunyaev, A. (2016, September). An information privacy risk index for mHealth apps. Proceedings Annual Privacy Forum 2016. SSRN. https://doi.org/10.1007/978-3-319-44760-5_12
Casanovas, P. (2015). Semantic web regulatory models: Why ethics matter. Philosophy and Technology, 28(1), 33–55. https://doi.org/10.1007/s13347-014-0170-y
Casanovas, P., Mendelson, D., & Poblet, M. (2017). A linked democracy approach for regulating public health data. Health Technology, 7, 519–537. https://doi.org/10.1007/s12553-017-0191-5
Casanovas, P., Hashmi, M., & de Koker, L. (2021). The rule of law and compliance: Legal quadrant and conceptual clustering. In V. Rodríguez-Doncel, M. Palmirani, M. Araszkiewicz, P. Casanovas, U. Pagallo, & G. Sartor (Eds.), Lecture notes in computer science: Vol. 13048. AI approaches to the complexity of legal systems XI-XII. AICOL AICOL XAILA 2020 2018 2020 (pp. 215–229). Springer. https://doi.org/10.1007/978-3-030-89811-3_15
Casanovas, P., & Poblet, M. (2021). Adding semantics to the legal domain. La Trobe. https://doi.org/10.26181/61109185d2007
Casanovas, P., Gonzalez-Conejero, J., & de Koker, L. (2023). Legal compliance by design (LCbD) and through design (LCtD): Preliminary Survey. La Trobe. https://doi.org/10.26181/22910891.v1
Cavoukian, A., & Chibba, M. (2016). Cognitive cities, Big Data, and citizen participation: The essentials of privacy and security. In E. Portmann & M. Finger (Eds.), Studies in systems, decision and control: Vol. 63. Towards cognitive cities (pp. 61–82). Springer, Cham. https://doi.org/10.1007/978-3-319-33798-2_4
Chun, S., & MacKellar, B. (2012, March). Social health data integration using semantic web. In SAC ‘12: Proceedings of the 27th annual ACM symposium on applied computing (pp. 392–397). https://doi.org/10.1145/2245276.2245351
Colesky, M., Hoepman, J., & Hillan, C. (2016). Critical analysis of privacy design strategies. 2016 IEEE Security and Privacy Workshops (SPW) (pp. 33–40). https://doi.org/10.1109/SPW.2016.23
Estlund, D. (2008). Epistemic approaches to democracy. Episteme: A Journal of Social Epistemology, 5(1), 1–4. https://doi.org/10.3366/E1742360008000191
Gharib, M., Giorgini, P., & Mylopoulos, J. (2016). Ontologies for privacy requirements engineering: A systematic literature review. ArXiv. https://doi.org/10.48550/arXiv.1811.12621
Gillespie, T. (2014, October). The relevance of algorithms. in T. Gillespie, P. J. Boczkowski, & K. A. Foot (Eds.), Media technologies: Essays on communication, materiality, and society. MIT Press. https://doi.org/10.7551/mitpress/9780262525374.001.0001
Gronlund, K., Bachtiger, A., & Setalas, M. (2014). Deliberative mini-publics: Involving citizens in the democratic process. ECPR Press.
Gutwirth, R., & Leenes, P. (2016). Data protection on the move. Current developments in ICT and privacy/data protection. Springer. https://doi.org/10.1007/978-94-017-7376-8
Hardy, Q. (2016, June). The web’s creator looks to reinvent it. New York Times. https://www.nytimes.com/2016/06/08/technology/the-webs-creator-looks-to-reinvent-it.html
Hockings, E. (2016). Critical examination of policy. Developments in information governance and biosciences. In B. Mittelstadt, & L. Floridi (Eds.), Law, governance and technology series: Vol. 29. The ethics of biomedical Big Data (pp. 95–115). Springer. https://doi.org/10.1007/978-3-319-33525-4_5
Klitou, D. (2012). A solution, but not a panacea for defending privacy: challenges, criticism, and limitations of privacy by design. In B. Preneel & D. Ikonomou (Eds.), Lecture notes in computer science: Vol. 8319. Privacy technologies and policy. APF 2012 pp. 86–110). Springer. https://doi.org/10.1007/978-3-642-54069-1_6
Koops, B.-J., & Leenes, R. (2014). Privacy regulation cannot be hardcoded. A critical comment on the “privacy by design” provision in data-protection law. International Review of Law, Computers, and Technology, 28(2), 159–171. https://doi.org/10.1080/13600869.2013.801589
Kuyper, J. (2015). Democratic deliberation in the modern world: The systemic turn. Critical Review, 27(1), 49–63. https://doi.org/10.1080/08913811.2014.993891
Landemore, H. (2013). Democratic reason: Politics, collective intelligence, and the rule of the many. Princeton University Press. https://doi.org/10.23943/princeton/9780691155654.001.0001
Lokshina, I., & Lanting, C. (2018). Addressing ethical concerns of Big Data as a prerequisite for a sustainable Big Data industry. International Journal of Interdisciplinary Telecommunications and Networking, 10(3), 33–54. https://doi.org/10.4018/IJITN.2018070104
Lokshina, I., Lanting, C., & Durkin, B. (2018). IoT- and Big Data-driven data analysis services for third parties, strategic implications, and business opportunities. International Journal of Social Ecology and Sustainable Development, 9(3), 34–52. https://doi.org/10.4018/IJSESD.2018070103
Lokshina, I., Gregus, M., & Thomas, W. (2019). Application of integrated building information modeling, IoT and blockchain technologies in system design of a smart building. Procedia Computer Science, 160, 497–502. https://doi.org/10.1016/j.procs.2019.11.058
Lokshina, I., & Lanting, C. (2019). A qualitative evaluation of IoT-driven eHealth: knowledge management, business models and opportunities, deployment, and evolution. In N. Kryvinska & M. Gregus (Eds.), Lecture notes on data engineering and communications technologies: Vol. 20. Data-centric business and applications (pp. 23–52). Springer. https://doi.org/10.1007/978-3-319-94117-2_2
Lokshina, I., Lanting, C., & Durkin, B. (2020). Evaluation of strategic opportunities and resulting business models for SMEs: Employing IoT in their data-driven ecosystems. In M. Jennex (Eds.), Knowledge management, innovation, and entrepreneurship in a changing world (pp. 148–186). IGI Global. https://doi.org/10.4018/978-1-7998-2355-1.ch007
Lokshina, I., & Lanting, C. (2021). A study on the wide-ranging ethical implications of Big Data technology in a digital society: How likely are data accidents during COVID-19? Journal of Business Ecosystems, 2(1), 32–57. https://doi.org/10.4018/JBE.2021010103
Lokshina, I., & Lanting, C. (2023). Development of public health data regulatory models from a linked democracy perspective. In P. Geril & M. Polanska (Eds.), Science fiction prototyping conference (pp. 21–28). EUROSIS-ETI. Ghent, Belgium.
Luo, J., Wu, M., Gopukumar, D., & Zhao, Y. (2016). Big data application in biomedical research and healthcare: A literature review. Biomedical Informatics Insights, 8, 1–10. https://doi.org/10.4137/BII.S31559
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. https://doi.org/10.1111/1467-9566.12109
Mathews, R. (2016). On protecting and preserving personal privacy in interoperable global healthcare venues. Health Technology, 6, 53–73. https://doi.org/10.1007/s12553-016-0126-6
Mendelson, D., & Wolf, G. (2016, December). “My electronic health record” – cui bono (for whose benefit)? 24 Journal of Law and Medicine. SSRN. https://ssrn.com/abstract=2881787
Mendelson, D., & Mendelson, D. (2017). Legal protections for personal health information in the age of Big Data – a proposal for regulatory framework. Ethics, Medicine and Public Health, 3(1), 37–55. https://doi.org/10.1016/j.jemep.2017.02.005
Mendelson, D. (2020). National electronic health record systems and consent to processing of health data in the European Union and Australia. In M. Corrales Compagnucci, N. Forgo, T. Kono, S. Teramoto, & E. Vermeulen (Eds.), Legal tech and the new sharing economy. Perspectives in law, business and innovation (pp. 115–131). Springer. https://doi.org/10.1007/978-981-15-1350-3_6
Middleton, K. (2016, October). Millions of Australians caught in health records breach. The Saturday Paper. https://www.thesaturdaypaper.com.au/news/politics/2016/10/08/millions-australians-caught-health-records-breach/14758452003833
Mittelstadt, B., & Floridi, L. (2016, April). The ethics of Big Data: Current and foreseeable issues in biomedical contexts. Science and Engineering Ethics, 22(2), 303–341. https://doi.org/10.1007/s11948-015-9652-2
Nissenbaum, H. (2010). Privacy in context: Technology, policy, and the integrity of social life. Stanford University Press. https://doi.org/10.1515/9780804772891
Pagallo, U., Casanovas, P., & Madelin, R. (2019). The middle-out approach: Assessing models of legal governance in data protection, artificial intelligence, and the web of data. The Theory and Practice of Legislation, 7(1), 1–25. https://doi.org/10.1080/20508840.2019.1664543
Schwartzberg, M. (2015). Epistemic democracy and its challenges. Annual Review of Political Science, 18, 187–203. https://doi.org/10.1146/annurev-polisci-110113-121908
Staab, S., & Studer, R. (2003). Handbook on ontologies. Springer Science Business Media. https://doi.org/10.1007/978-3-540-24750-0
Stevens, L. (2017, March). Big read: What does Google DeepMind want with the NHS? Digital Health. https://www.digitalhealth.net/2017/03/deepmind-mustafa-suleyman-interview
UNESCO. (2005, October). Universal declaration on bioethics and human rights.
Walzer, M. (1984). Liberalism and the art of separation. Political Theory, 12(3), 315–330. https://doi.org/10.1177/0090591784012003001
Woods, S. (2016). Big Data governance: solidarity and the patient voice. In B. Mittelstadt & L. Floridi (Eds.), Law, governance and technology series: Vol. 29. The ethics of biomedical big data. Springer. https://doi.org/10.1007/978-3-319-33525-4_10