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11 J. Open Access L. 1 (2023)

handle is hein.journals/jopacc11 and id is 1 raw text is: Open Science and Data Protection: Engaging Scientific and Legal Contexts Ludovica Paseri* * Post-Doc Research Fellow at the Law Department, Universita degli Studi di Torino Abstract. This paper analyses the relationship between open science policies and data protection. In order to tackle the research data paradox of the contemporary science, i.e., the tension between the pursuit of data-driven scientific research and the crisis of repeatability or reproducibility of science, a theoretical perspective suggests a potential convergence between open science and data protection. Both fields regard governance mechanisms that shall take into account the plurality of interests at stake. The aim is to shed light on the processing of personal data for scientific re- search purposes in the context of open science. The investigation supports a threefold need: that of broadening the legal debate; of expanding the territorial scope of the analysis, in addition to the extra-territoriality effects of the European Union's law; and an interdisciplinary discussion. Based on these needs, four perspectives are then identified, that encompass the challenges related to data processing in the context of open science: (i) the contextual and epistemological perspectives; (ii) the legal co-ordination perspectives; (iii) the governance perspectives; and (iv) the technical perspectives. Keywords: Open Science; Data Protection; Privacy; Research Data; Data Sharing; Scientific Research; Governance Mechanisms. 1. Introduction: The Research Data Paradox of Contemporary Science The field of scientific research is currently experiencing a paradox: on the one hand, a considerable trend towards data-driven science is emerging (Leonelli, 2018); on the other hand, a profound crisis, the so-called reproducibility crisis, is taking place. The trend towards data-driven science requires an ever-increasing volume of data (Resnik, 2005), becoming essential for implementing research projects. As a consequence, there is a growing demand for computational power and methodologies that are able to take full ad- vantage of the elaboration of such data, in a process of technological convergence (Pagallo, Durante, Monteleone, 2017, 59). On the other hand, however, one of the major problems in contempo- rary science is the so-called crisis of reproducibility (Baker, 2016) or, adopting another categorization, crisis of repeatability (Nosek et al., 2022). The causes of this crisis are manifold. Difficulties may arise due

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