Evolution of regulatory models for public health data ecosystems from a linked democracy perspective


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

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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.
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Sep 27, 2023
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