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Here, Sharon Glaysher, Sam Robson and Angie Beckett, from the University of Portsmouth, review their experiences tackling the pandemic so far and present us with the main challenges of sampling during the pandemic and what they would do differently next time.
In this talk, Prof Senjuti Saha from the Child Health Research Foundation in Bangladesh discusses her views on ethics and data sharing during pandemics, or “wartime” and “peacetime” or periods between public health emergencies.
Stakeholders for data sharing and the importance to share
Who is a stakeholder
Sharing research data within the international scientific community is of increasing importance for research propagation and value. However, the ethical and social challenges this presents, particularly in the context of structural inequities and varied capacity in international research is of concern.
The involvement of the public and other stakeholders is essential to building locally responsive research policies, including data sharing. Stakeholders are individuals, groups, or organizations that are affected by or can affect a particular action undertaken by others. Biobanks, data repositories and other such central storage facilities or organisations encompass a number of different stakeholders such as donors, researchers, research institutions, regulatory bodies, funders, and others. These stakeholders can potentially have a strong influence on the organization and operation of any sample or data collection. A sound strategy for stakeholder engagement is therefore essential.
As such, for more and less research-experienced stakeholders, ethical research data sharing is likely to rest on the development and implementation of appropriate trust-building processes, linked to local perceptions of benefits and challenges.
Stakeholders involved in clinical research have different roles/responsibilities in the process of data and sample sharing toward the common goal of research and improving patient benefits. In general, the sharing process (Figure 1) can be defined in a number of iterative steps; donors providing data or samples to the collector; the collector providing the samples and/or data to the sponsor, who stores them in a database and/or biobank; data providers (sponsors of clinical study or database or biobank); data provider making data or samples upfront available, or requesters finding the data or material, requesting access via an intermediary or directly to the provider, negotiating, and-upon agreement-receiving the requested data or material by the requester.
Research data are a valuable resource, usually requiring much time and money to be produced. Many data have a significant value beyond usage for the original research. Data sharing benefits the researcher, research sponsors, data repositories, the scientific community, and the public. It encourages more connection and collaboration between scientists, and better science leads to better decision-making. Data sharing is typically encouraged within the scientific community, but it requires a great deal of effort, resources, and collaboration. Preparing data to be shared takes time and careful documentation of the research process and the data results. Sharing research data:
Encourages scientific enquiry and debate
Promotes innovation and potential new data uses
Leads to new collaborations between data users and data creators
Maximises transparency and accountability
Enables scrutiny of research findings
Encourages the improvement and validation of research methods
Reduces the cost of duplicating data collection
Increases the impact and visibility of research
Promotes the research that created the data and its outcomes
Can provide direct credit to the researcher as a research output in its own right
Provides important resources for education and training
The ease with which digital data can be stored, disseminated and made easily accessible online to users means that many institutions are keen to share research data to increase the impact and visibility of their research.
Opportunities for global collaboration in pathogen genomics
In this video, Dr Ewan Harrison tells his experiences in COG-UK dealing with legal considerations when sharing data among partners from different countries.
Obstacles to the release of data
We are living in an unprecedented era of information, leading to progress for open access to science and global research data. Funders around the world are increasingly mandating good data practices, such as data management plans and data sharing, and recognizing the importance of global collaboration on infrastructure and best practices. Across the research community, policy, strategy, and working groups are building momentum toward a future in which research data is widely Findable, Accessible, Interoperable, and Reusable (FAIR). In this section, we discuss a variety of challenges associated with data sharing, such as obstacles to the release of data, privacy and confidentiality issues, and informed-consent issues.
There are a variety of challenges associated with data release. Some are related to the concerns of the scientists who generated the data, some are related to the concerns of businesses or other organizations that paid for the data collection, and some are practical issues related to data administration.
Concerns About Adversarial Science
Regrettably, research can be highly contentious and confrontational at times. For example, industries that profit from the production or use of specific chemicals or goods may oppose research and/or data indicating that their specific chemicals or goods pose health risks.
Business Considerations Related to Data Sharing
When deciding whether to share data, businesses always consider a variety of factors. Two of the most significant are concerns about exposing themselves to liability and other costs, as well as concerns about losing the value of confidential business information.
The Business Value of Data
There is also the question of who pays for access to data that a company has paid for. Regulatory agencies are generally required to safeguard the commercial value of data collected by businesses. The most important fact is that the data generated by industry researchers have commercial value. Companies that collected data deserve and expect to be compensated for supplying that data to others; however, where should that compensation come from? If another company wants to use the data, the answer is obvious; however, if academic researchers want to use the data, the answer is less clear.
Administrative Issues
Data sharing is also complicated by a number of administrative issues, one of which is who owns the data. This is especially problematic when data has been collected by groups of companies or institutions. Other administrative challenges include the fact that organizational policies and procedures, as well as logistical issues, may differ from one organization to the next. For example, different universities' institutional review boards may have different rules governing data sharing procedures.
The cost of Data Sharing
The cost of extensive data sharing is a major impediment. The issue is that most budgets do not cover the costs of data sharing. If data are to be made publicly available, the funds to do so must come from somewhere, perhaps from direct research support.
Privacy and confidentiality issues
One of the barriers to data release is ensuring the privacy of the persons whose data has been obtained as much as possible, as some of these data, such as medical history data or employment data, can be highly sensitive. Organizations are putting plans to share data on hold due to concerns over re-identification. A key question is how likely the re-identification of subjects in existing data sets is that have had the obvious personal identifying information removed.
Informed-consent issues
Before an individual can take part in a scientific or medical research study, it is generally necessary for that person to provide “informed consent.” The problem is that when you ask someone for consent, especially broad consent, neither the requestor nor the person being sought has any idea what that means in terms of how it will be utilized because we don't even know what it will be used for down the road. The second point is that when people asked for consent a long time ago, we knew that consent meant you weren't going to provide anything to someone else, but as long as we removed your name from it, it was fine.
Insufficient tools and technology
The technological challenges highlighted include transferring large datasets, particularly to the African region. Furthermore, technology is viewed as simplifying data-related operations rather than adding complexity. However, many alternative cloud data providers are now accessible, each with their own set of data access rules. As data teams continue to rapidly embrace numerous cloud data platforms, this heterogeneous patchwork of capabilities frequently fails to scale effectively across different cloud data platforms. As a consequence, either too tight data rules that prevent data exchange entirely, or overly wide policies that allow sensitive data to slip through the gaps, resulting in a data breach or leak.