NOT-OD-22-029: Request for Information on Proposed Updates and Long-Term Considerations for the NIH Genomic Data Sharing Policy

“Respect for and protection of the interests of research participants are central tenets of the NIH GDS Policy and are fundamental to NIH’s stewardship of large-scale genomic data. Data derived from human research participants under the GDS Policy must be de-identified and provided with a random, unique code, the key to which is held by the submitting institution. NIH acknowledges that the concept of “identifiability” is a matter of ongoing deliberation within the scientific and bioethics communities. NIH relies on robust protections beyond de-identification, such as Institutional Review Board (IRB) consideration of risks associated with data submission, designating controlled access for certain data types, use of Data Access Committees to review requests, data use agreements to prohibit data disclosure and participant re-identification, and Certificates of Confidentiality[ii] to prohibit disclosure. As outlined in the NIH GDS Policy, the criteria for establishing de-identification are:

Identities of research participants cannot be readily ascertained or otherwise associated with the data by the repository staff or secondary data users (45 CFR 46.102(e) (Federal Policy for the Protection of Human Subjects); and
18 identifiers enumerated at 45 CFR 164.514(b)(2)(the HIPAA Privacy Rule) are removed.

The reliance on the 18 identifiers enumerated at 45 CFR 164.514(b)(2) (the HIPAA Privacy Rule) as the only acceptable method under the GDS Policy for de-identification has recently presented several challenges. Certain data elements considered potentially identifiable, such as date ranges shorter than a year, may have scientific utility, especially when studying disease progression (e.g., with COVID-19) or higher resolution location data than the regulatory standard (e.g., full ZIP codes or mobile location data), which may be valuable for studying the social determinants of health or environmental risk.

Challenges have also arisen recently around data linkage. It is difficult to know in advance which data sources may add scientific value when combined, so it is not always possible to tell participants about data linkage during their initial consent. Linking data refers to connecting two or more data sources (often multiple studies) to bring together information about a person, enabling researchers to learn more about a participant or small group of participants. For example, a participant might enroll in a study that uses their electronic health record as well as a separate study that uses a sample of their blood, and the data about them from those studies could later be linked in new research for more powerful analyses. This challenge in prospectively informing participants about data linkage raises questions about respecting individuals’ autonomy and what participants understand about how their data will be used. Furthermore, data from multiple sources may not have been obtained under the same consent and de-identification expectations as the GDS Policy….”

NOT-OD-22-029: Request for Information on Proposed Updates and Long-Term Considerations for the NIH Genomic Data Sharing Policy

“Respect for and protection of the interests of research participants are central tenets of the NIH GDS Policy and are fundamental to NIH’s stewardship of large-scale genomic data. Data derived from human research participants under the GDS Policy must be de-identified and provided with a random, unique code, the key to which is held by the submitting institution. NIH acknowledges that the concept of “identifiability” is a matter of ongoing deliberation within the scientific and bioethics communities. NIH relies on robust protections beyond de-identification, such as Institutional Review Board (IRB) consideration of risks associated with data submission, designating controlled access for certain data types, use of Data Access Committees to review requests, data use agreements to prohibit data disclosure and participant re-identification, and Certificates of Confidentiality[ii] to prohibit disclosure. As outlined in the NIH GDS Policy, the criteria for establishing de-identification are:

Identities of research participants cannot be readily ascertained or otherwise associated with the data by the repository staff or secondary data users (45 CFR 46.102(e) (Federal Policy for the Protection of Human Subjects); and
18 identifiers enumerated at 45 CFR 164.514(b)(2)(the HIPAA Privacy Rule) are removed.

The reliance on the 18 identifiers enumerated at 45 CFR 164.514(b)(2) (the HIPAA Privacy Rule) as the only acceptable method under the GDS Policy for de-identification has recently presented several challenges. Certain data elements considered potentially identifiable, such as date ranges shorter than a year, may have scientific utility, especially when studying disease progression (e.g., with COVID-19) or higher resolution location data than the regulatory standard (e.g., full ZIP codes or mobile location data), which may be valuable for studying the social determinants of health or environmental risk.

Challenges have also arisen recently around data linkage. It is difficult to know in advance which data sources may add scientific value when combined, so it is not always possible to tell participants about data linkage during their initial consent. Linking data refers to connecting two or more data sources (often multiple studies) to bring together information about a person, enabling researchers to learn more about a participant or small group of participants. For example, a participant might enroll in a study that uses their electronic health record as well as a separate study that uses a sample of their blood, and the data about them from those studies could later be linked in new research for more powerful analyses. This challenge in prospectively informing participants about data linkage raises questions about respecting individuals’ autonomy and what participants understand about how their data will be used. Furthermore, data from multiple sources may not have been obtained under the same consent and de-identification expectations as the GDS Policy….”

On informed consent and open licensing | Martin Paul Eve | Professor of Literature, Technology and Publishing

“I gave my final talk of the year, today, at the University of Leeds, on open access in the humanities disciplines. Perhaps predictably, all of the Q&A centred on open licensing and the concerns from humanists around the misuse of their work.

My basic line on all this has shifted over time, but I am more cautious now than I used to be and feel better about somewhat more restrictive CC licenses. Specifically, I do not want a situation where a colleague experiments with open access for the first time and ends up on the receiving end of a bad practice that they had not anticipated.

This comes down, to some degree, to “informed consent”. I am quite happy to take risks with my work and open licensing. I think that by being a “pioneer” I might be able to show that the risks are overblown. However, I am in no doubt as to what the risks are and what potential remedies are available. Other people in the humanities who do not know much about copyright law and also do not have the time or inclination to read and understand open licenses, are not in the same position.

I worry, though, that a lot of the advice we give around open licenses might be not providing an optimal level of informed consent. …”

Ethics Toolkit – the Canadian Open Neuroscience Platform

“In response to a growing need in the neuroscience community for concrete guidance concerning ethically sound and pragmatically feasible open data-sharing, the CONP has created an ‘Ethics Toolkit’, currently comprised of:

 

1. The CONP Consent Toolkit

 

2. The CONP Privacy and De-identification Toolkit

Together, these documents are meant to help researchers identify key elements in the design of their projects that are often required for the open sharing of neuroscience data, such as model consent language and approaches to de-identification….”

Beyond Copyright: the Ethics of Open Sharing | by Josie Fraser | Creative Commons: We Like to Share | Nov, 2021 | Medium

“In a world where internet and mobile technologies are mainstream, communities, groups and organisations routinely produce materials in a wide range of digital formats. This position paper looks at some of the ways in which the impacts of openly sharing these materials, or deciding not to, is an ethical decision. This paper also looks at some of the ways in which sharing openly can be considered in terms of an organisational commitment to social responsibility….

The decision to share openly (or not) is an ethical decision….”

 

Modernizing JCRS Online Case Reports: open access, signed pa… : Journal of Cataract & Refractive Surgery

“To better serve our readers and authors, we [JCRS Online Case Reports] will be moving to an Open Access publishing model, under a Creative Commons license to publish. The first step of this transition is to require signed consent from all patients included in case reports. Minor changes in the format of the abstract are also required.”

Integrating Qualitative Methods and Open Science: Five Principles for More Trustworthy Research* | Journal of Communication | Oxford Academic

Abstract:  Recent initiatives toward open science in communication have prompted vigorous debate. In this article, we draw on qualitative and interpretive research methods to expand the key priorities that the open science framework addresses, namely producing trustworthy and quality research. This article contributes to communication research by integrating qualitative methodological literature with open communication science research to identify five broader commitments for all communication research: validity, transparency, ethics, reflexivity, and collaboration. We identify key opportunities where qualitative and quantitative communication scholars can leverage the momentum of open science to critically reflect on and improve our knowledge production processes. We also examine competing values that incentivize dubious practices in communication research, and discuss several metascience initiatives to enhance diversity, equity, and inclusion in our field and value multiple ways of knowing.

 

The ethics of data sharing and biobanking in health research

Abstract:  The importance of data sharing and biobanking are increasingly being recognised in global health research. Such practices are perceived to have the potential to promote science by maximising the utility of data and samples. However, they also raise ethical challenges which can be exacerbated by existing disparities in power, infrastructure and capacity. The Global Forum on Bioethics in Research (GFBR) convened in Stellenbosch, South Africa in November 2018, to explore the ethics of data sharing and biobanking in health research. Ninety-five participants from 35 countries drew on case studies and their experiences with sharing in their discussion of issues relating to respecting research participants and communities, promoting equitable sharing, and international and national approaches to governing data sharing and biobanking. In this editorial we will briefly review insights relating to each of these three themes.

 

The Personal Genome Project-UK, an open access resource of human multi-omics data | Scientific Data

“Integrative analysis of multi-omics data is a powerful approach for gaining functional insights into biological and medical processes. Conducting these multifaceted analyses on human samples is often complicated by the fact that the raw sequencing output is rarely available under open access. The Personal Genome Project UK (PGP-UK) is one of few resources that recruits its participants under open consent and makes the resulting multi-omics data freely and openly available. As part of this resource, we describe the PGP-UK multi-omics reference panel consisting of ten genomic, methylomic and transcriptomic data. Specifically, we outline the data processing, quality control and validation procedures which were implemented to ensure data integrity and exclude sample mix-ups. In addition, we provide a REST API to facilitate the download of the entire PGP-UK dataset. The data are also available from two cloud-based environments, providing platforms for free integrated analysis. In conclusion, the genotype-validated PGP-UK multi-omics human reference panel described here provides a valuable new open access resource for integrated analyses in support of personal and medical genomics….”