Common conditions of use elements. Atomic concepts for consistent and effective information governance.

Myriad policy, ethical and legal considerations underpin the sharing of biological resources, implying the need for standardised and yet flexible ways to digitally represent diverse 'use conditions'. We report a core lexicon of terms that are atomic, non-directional 'concepts of use', called Common Conditions of use Elements. This work engaged biobanks and registries relevant to the European Joint Programme for Rare Diseases and aimed to produce a lexicon that would have generalised utility. Seventy-six concepts were initially identified from diverse real-world settings, and via iterative rounds of deliberation and user-testing these were optimised and condensed down to 20 items. To validate utility, support software and training information was provided to biobanks and registries who were asked to create Sharing Policy Profiles. This succeeded and involved adding standardised directionality and scope annotations to the employed terms. The addition of free-text parameters was also explored. The approach is now being adopted by several real-world projects, enabling this standard to evolve progressively into a universal basis for representing and managing conditions of use.

Getting your DUCs in a row - standardising the representation of Digital Use Conditions.

Improving patient care and advancing scientific discovery requires responsible sharing of research data, healthcare records, biosamples, and biomedical resources that must also respect applicable use conditions. Defining a standard to structure and manage these use conditions is a complex and challenging task. This is exemplified by a near unlimited range of asset types, a high variability of applicable conditions, and differing applications at the individual or collective level. Furthermore, the specifics and granularity required are likely to vary depending on the ultimate contexts of use. All these factors confound alignment of institutional missions, funding objectives, regulatory and technical requirements to facilitate effective sharing. The presented work highlights the complexity and diversity of the problem, reviews the current state of the art, and emphasises the need for a flexible and adaptable approach. We propose Digital Use Conditions (DUC) as a framework that addresses these needs by leveraging existing standards, striking a balance between expressiveness versus ambiguity, and considering the breadth of applicable information with their context of use.

Open Data governance at the Canadian Open Neuroscience Platform (CONP): From the Walled Garden to the Arboretum.

Scientific research communities pursue dual imperatives in implementing strategies to share their data. These communities attempt to maximize the accessibility of biomedical data for downstream research use, in furtherance of open science objectives. Simultaneously, such communities safeguard the interests of research participants through data stewardship measures and the integration of suitable risk disclosures to the informed consent process. The Canadian Open Neuroscience Platform (CONP) convened an Ethics and Governance Committee composed of experts in bioethics, neuroethics, and law to develop holistic policy tools, organizational approaches, and technological supports to align the open governance of data with ethical and legal norms. The CONP has adopted novel platform governance methods that favor full data openness, legitimated through the use of robust deidentification processes and informed consent practices. The experience of the CONP is articulated as a potential template for other open science efforts to further build upon. This experience highlights informed consent guidance, deidentification practices, ethicolegal metadata, platform-level norms, and commercialization and publication policies as the principal pillars of a practicable approach to the governance of open data. The governance approach adopted by the CONP stands as a viable model for the broader neuroscience and open science communities to adopt for sharing data in full open access.

Reconciling the biomedical data commons and the GDPR: three lessons from the EUCAN ELSI collaboratory.

The coming-into-force of the EU General Data Protection Regulation (GDPR) is a watershed moment in the legal recognition of enforceable rights to informational self-determination. The rapid evolution of legal requirements applicable to data use, however, has the potential to outstrip the capabilities of networks of biomedical data users to respond to the shifting norms. It can also delegitimate established institutional bodies that are responsible for assessing and authorising the downstream use of data, including research ethics committees and institutional data custodians. These burdens are especially pronounced for clinical and research networks that are of transnational scale, because the legal compliance burden for outbound international data transfers from the EEA is especially high. Legislatures, courts, and regulators in the EU should therefore implement the following three legal changes. First, the responsibilities of particular actors in a data sharing network should be delimited through the contractual allocation of responsibilities between collaborators. Second, the use of data through secure data processing environments should not trigger the international transfer provisions of the GDPR. Third, the use of federated data analysis methodologies that do not provide analysis nodes or downstream users access to identifiable personal data as part of the outputs of those analyses should not be considered circumstances of joint controllership, nor lead to the users of non-identifiable data to be considered controllers or processors. These small clarifications of, or modifications to, the GDPR would facilitate the exchange of biomedical data amongst clinicians and researchers.

The Deceased, Public Health, and Research: Proposing Legal Reforms.

There is little guidance concerning biomedical research using tissues from deceased individuals. Unique ethical and legal challenges gained visibility during the coronavirus disease 2019 (COVID-19) pandemic, when important studies using genome sequencing required access to biological materials from deceased individuals. These studies proposed to determine whether specific genomic profiles were associated with important disease outcomes. Such research has previously required consent from next-of-kin or other surrogate decision makers. Ethics waivers for such consent vary within Canada. In Ontario, research ethics boards can grant waivers of consent if the Tri-Council Policy Statement-2 conditions are met. These include that the individual is not harmed, that the materials are essential to the research, and that privacy will be protected. Conversely, in Quebec, Civil Code article 22 imposes an obligation on researchers to seek consent from next-of-kin or another surrogate decision maker with no option for waivers. It became evident to researchers that these standards can sometimes impose an impracticable balance of risks and benefits, especially in public health emergencies. We seek to establish why and when consent requirements should be waived for public health and research involving the tissues of deceased individuals.

The Canadian Open Neuroscience Platform-An open science framework for the neuroscience community.

The Canadian Open Neuroscience Platform (CONP) takes a multifaceted approach to enabling open neuroscience, aiming to make research, data, and tools accessible to everyone, with the ultimate objective of accelerating discovery. Its core infrastructure is the CONP Portal, a repository with a decentralized design, where datasets and analysis tools across disparate platforms can be browsed, searched, accessed, and shared in accordance with FAIR principles. Another key piece of CONP infrastructure is NeuroLibre, a preprint server capable of creating and hosting executable and fully reproducible scientific publications that embed text, figures, and code. As part of its holistic approach, the CONP has also constructed frameworks and guidance for ethics and data governance, provided support and developed resources to help train the next generation of neuroscientists, and has fostered and grown an engaged community through outreach and communications. In this manuscript, we provide a high-level overview of this multipronged platform and its vision of lowering the barriers to the practice of open neuroscience and yielding the associated benefits for both individual researchers and the wider community.

Federated Analysis for Privacy-Preserving Data Sharing: A Technical and Legal Primer.

Continued advances in precision medicine rely on the widespread sharing of data that relate human genetic variation to disease. However, data sharing is severely limited by legal, regulatory, and ethical restrictions that safeguard patient privacy. Federated analysis addresses this problem by transferring the code to the data-providing the technical and legal capability to analyze the data within their secure home environment rather than transferring the data to another institution for analysis. This allows researchers to gain new insights from data that cannot be moved, while respecting patient privacy and the data stewards' legal obligations. Because federated analysis is a technical solution to the legal challenges inherent in data sharing, the technology and policy implications must be evaluated together. Here, we summarize the technical approaches to federated analysis and provide a legal analysis of their policy implications.

Open Data in the Era of the GDPR: Lessons from the Human Cell Atlas.

The Human Cell Atlas (HCA) is striving to build an open community that is inclusive of all researchers adhering to its principles and as open as possible with respect to data access and use. However, open data sharing can pose certain challenges. For instance, being a global initiative, the HCA must contend with a patchwork of local and regional privacy rules. A notable example is the implementation of the European Union General Data Protection Regulation (GDPR), which caused some concern in the biomedical and genomic data-sharing community. We examine how the HCA's large, international group of researchers is investing tremendous efforts into ensuring appropriate sharing of data. We describe the HCA's objectives and governance, how it defines open data sharing, and ethico-legal challenges encountered early in its development; in particular, we describe the challenges prompted by the GDPR. Finally, we broaden the discussion to address tools and strategies that can be used to address ethical data governance.

Bridging the European Data Sharing Divide in Genomic Science.

In this viewpoint, we argue for the importance of creating data spaces for genomic research that are detached from contexts in which fundamental rights concerns related to surveillance measures override a purpose-specific balancing of fundamental rights. Genomic research relies on molecular and phenotypic data, on comparing findings within large data sets, on searchable metadata, and on translating research results into a clinical setting. These methods require sensitive genetic and health data to be shared across borders. International data sharing between the European Union (EU) or the European Economic Area and third countries has accordingly become a cornerstone of genomics. The EU General Data Protection Regulation contains rules that accord privileged status to data processing for research purposes to ensure that strict data protection requirements do not impede biomedical research. However, the General Data Protection Regulation rules applicable to international transfers of data accord no such preferential treatment to international data transfers made in the research context. The rules that govern the international transfer of data create considerable barriers to international data sharing because of the cost-intensive procedural and substantive compliance burdens that they impose. For certain jurisdictions and select use cases, there exist practically no lawful mechanisms to enable the international transfer of data because of concerns about the protection of fundamental rights. The proposed solutions further fail to address the need to share large data sets of local and regional cohorts across national borders to enable joint analyses. The European Health Data Space is an emerging federated, EU-wide data infrastructure that is intended to function as an infrastructure bringing together EU health data to improve patient care and enable the secondary use of health-related data for research purposes. Such infrastructure is implementing new institutions to support its functioning and is being implemented in reliance on a new enabling law, the regulation on the European Health Data Space. This innovation provides the opportunity to facilitate EU contribution to international genomic research efforts. The draft regulation for this data space provides for a concept of data infrastructure intended to enable cross-border data exchange and access, including access to genetic and health data for scientific analysis purposes. The draft regulation also provides for obligations of national actors aimed at making data widely available. This effort is laudable. However, in the absence of further, more fundamental changes to the manner in which the EU regulates the secondary use of health data, it is reasonable to believe that EU participation in international genomic research efforts will remain impeded.

The international data governance landscape.

As the adoption of digital health accelerates health research increasingly relies on large quantities of biomedical data. Research institutions scattered across a large number of jurisdictions collaborate in producing and analyzing biomedical big data. National data protection legislation, for its part, grows increasingly complex and localized. To respond to heterogeneous legal requirements arising in numerous jurisdictions, decentralized health consortia must develop scalable organizational and 6 technological arrangements that enable data flows across jurisdictional boundaries. In this article, proposals are made to enable health sector organisations to align established biomedical ethics process and data analysis practices to shifting data protection norms through both public law co-regulation, private law tools, and design-oriented approaches.

Artificial Intelligence in Cardiovascular Imaging: "Unexplainable" Legal and Ethical Challenges?

Nowhere is the influence of artificial intelligence (AI) likely to be more profoundly felt than in health care, from patient triage and diagnosis to surgery and follow-up. Over the medium-term, these effects will be more acute in the cardiovascular imaging context, in which AI models are already successfully performing at approximately human levels of accuracy and efficiency in certain applications. Yet, the adoption of unexplainable AI systems for cardiovascular imaging still raises significant legal and ethical challenges. We focus in particular on challenges posed by the unexplainable character of deep learning and other forms of sophisticated AI modelling used for cardiovascular imaging by briefly outlining the systems being developed in this space, describing how they work, and considering how they might generate outputs that are not reviewable by physicians or system programmers. We suggest that an unexplainable tendency presents 2 specific ethico-legal concerns: (1) difficulty for health regulators; and (2) confusion about the assignment of liability for error or fault in the use of AI systems. We suggest that addressing these concerns is critical for ensuring AI's successful implementation in cardiovascular imaging.

Of Screening, Stratification, and Scores.

Technological innovations including risk-stratification algorithms and large databases of longitudinal population health data and genetic data are allowing us to develop a deeper understanding how individual behaviors, characteristics, and genetics are related to health risk. The clinical implementation of risk-stratified screening programmes that utilise risk scores to allocate patients into tiers of health risk is foreseeable in the future. Legal and ethical challenges associated with risk-stratified cancer care must, however, be addressed. Obtaining access to the rich health data that are required to perform risk-stratification, ensuring equitable access to risk-stratified care, ensuring that algorithms that perform risk-scoring are representative of human genetic diversity, and determining the appropriate follow-up to be provided to stratification participants to alert them to changes in their risk score are among the principal ethical and legal challenges. Accounting for the great burden that regulatory requirements could impose on access to risk-scoring technologies is another critical consideration.

Longitudinal Health Studies: Secondary Uses Serving the Future.

Our research compares the ethical and institutional conditions that govern the sharing and secondary use of longitudinal population health data from multiple cohorts. The data use and data sharing conditions applicable to 27 population health cohorts were assessed. This assessment was performed in consulting the informed consent materials and institutional policies applicable to the use of data. Descriptions drawn from the research ethics consent materials were refined through dialog with the institutional staff responsible for overseeing access to data, where possible. Our results demonstrate that data of longitudinal population health cohorts assessed can generally be shared and used for secondary purposes. However, the purposes of secondary use and the preconditions applicable thereto are highly variable. Heterogeneous use conditions can also impede the storage of legacy research data and the pooling thereof for the purpose of common reuse.

International transfers of personal data for health research following Schrems II: a problem in need of a solution.

On 16 July 2020, the Court of Justice of the European Union issued their decision in the Schrems II case concerning Facebook's transfers of personal data from the EU to the US. The decision may have significant effects on the legitimate transfer of personal data for health research purposes from the EU. This article aims: (i) to outline the consequences of the Schrems II decision for the sharing of personal data for health research between the EU and third countries, particularly in the context of the COVID-19 pandemic; and, (ii) to consider certain options available to address the consequences of the decision and to facilitate international data exchange for health research moving forward.

GA4GH: International policies and standards for data sharing across genomic research and healthcare.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.

Radical collaboration during a global health emergency: development of the RDA COVID-19 data sharing recommendations and guidelines.

Background: The coronavirus disease 2019 (COVID-19) global pandemic required a rapid and effective response. This included ethical and legally appropriate sharing of data. The European Commission (EC) called upon the Research Data Alliance (RDA) to recruit experts worldwide to quickly develop recommendations and guidelines for COVID-related data sharing. Purpose: The purpose of the present work was to explore how the RDA succeeded in engaging the participation of its community of scientists in a rapid response to the EC request. Methods: A survey questionnaire was developed and distributed among RDA COVID-19 work group members. A mixed-methods approach was used for analysis of the survey data. Results: The three constructs of radical collaboration (inclusiveness, distributed digital practices, productive and sustainable collaboration) were found to be well supported in both the quantitative and qualitative analyses of the survey data. Other social factors, such as motivation and group identity were also found to be important to the success of this extreme collaborative effort. Conclusions: Recommendations and suggestions for future work were formulated for consideration by the RDA to strengthen effective expert collaboration and interdisciplinary efforts.

An agenda-setting paper on data sharing platforms: euCanSHare workshop.

Various data sharing platforms are being developed to enhance the sharing of cohort data by addressing the fragmented state of data storage and access systems. However, policy challenges in several domains remain unresolved. The euCanSHare workshop was organized to identify and discuss these challenges and to set the future research agenda. Concerns over the multiplicity and long-term sustainability of platforms, lack of resources, access of commercial parties to medical data, credit and recognition mechanisms in academia and the organization of data access committees are outlined. Within these areas, solutions need to be devised to ensure an optimal functioning of platforms.

Correction to: Pandemics, privacy, and public health research.

In the section entitled "Responsive and responsible data sharing,".