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Challenges and limitations of data sharing

A video and an article discussing the limitations of data sharing
Hi, I’m Ewan Harrison. And I’m deputy director of COG-UK. Before the pandemic and now, I’m an academic microbiologist, particularly interested in bacterial genomics.
The challenges of data sharing inside countries and across international boundaries is obviously, an important one. For example, within the UK, there are four nations that make up there the UK. England, Wales, Scotland, and Northern Ireland. And particularly Scotland and Northern Ireland, have slightly different legal systems and laws that mean that we have to take that into consideration when we were setting up the UK-wide consortium. So that meant that, we had to consult widely with public health agencies, so that we could generate a consensus that everybody was happy for, that would fit with their legal systems.
Likewise, with international data sharing, there are different laws between different countries, there are different populations, some of which may be more sensitive to data sharing, or there’s greater risk at adoptive disclosure so more remote communities. One piece of information about a sample in a remote community could basically identify somebody. So it depends on whereabouts you’re taking samples from, the populations, and the population density. And I know that globally, many countries have faced different issues around these individual factors. What we’ve always decided to do, in terms of our data release from COG-UK, was to keep it very simple. To minimise that risk of adoptive disclosure, we only release the date of the sample, and the country that it came from.
So thus, reducing any risk of remote or rural communities a sample being identified as an individual. Data sharing, as part of a genomic surveillance, is one of the foundational principles. And I think, the pandemic has demonstrated the importance of this. We can see, for example, with the emergence of, for example in the UK, potentially of the detection of the Alpha variant. Very rapidly that data was shared. That allows scientists around the world to crowdsource and analyse that data. Then when it showed up in other countries, those genome sequences could be compared. Likewise, with the Delta variant and now with the Omicron variant. International data sharing is a critical component of that.
Also because scientists around the world are interested to work on that data. And having more minds looking at a piece of data can only really be a good thing.

In this video, Dr Ewan Harries tells his experiences dealing with legal considerations when sharing data among partners from different countries. Read more about the challenges and limitations of data sharing in the text below.

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.

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 is re-identification of subjects in existing data sets that have had the obvious personal identifying information removed.

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.


Ethical and practical issues to consider in the governance of genomic and human research data and data sharing in South Africa: a meeting report

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