Benefits and barriers in the design of harmonized access agreements for international data sharing
Open accessAbstract
In the past decade, there has been a surge in the number of sensitive human genomic and health datasets available to researchers via Data Access Agreements (DAAs) and managed by Data Access Committees (DACs). As this form of sharing increases, so do the challenges of achieving a reasonable level of data protection, particularly in the context of international data sharing. Here, we consider how excessive variation across DAAs can hinder these goals, and suggest a core set of clauses that could prove useful in future attempts to harmonize data governance.
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Other non-machine-learning challenges affect multi-omics studies, including study design, multi-site sample collection and management, data sharing and governance, visualisation, ethical standards, reproducibility and translation.
“However, there are few other challenges related to multi-omics studies which are not ML related such as study design (Haas et al., 2017), multi-site sample collection & management (Pinu et al., 2019), multi-site data sharing and governance (Saulnier et al., 2019), visualisation (Mougin et al., 2018), ethical standards (Lévesque et al., 2018), and finally making the research reproducible (Conesa”
From Using machine learning approaches for multi-omics data analysis: A review (2021) · cites this paper as Saulnier et al., 2019
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Using machine learning approaches for multi-omics data analysis: A review
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- Authors
- Saulnier, K. M., Bujold, D., Dyke, S. O. M., Dupras, C., Beck, S., Bourque, G., & Joly, Y.
- Affiliations
- McGill University (CA)
- McGill University and Génome Québec Innovation Centre (CA)
- Montreal Neurological Institute and Hospital (CA)
- University College London (GB)
- Corresponding author
- Saulnier, Katie M.
- ORCID
- Venue
- Scientific Data
- Published
- 2019-12-02
- Volume
- 6
- Issue
- 1
- Pages
- 297-297
- ISSN
- 2052-4463 (ISSN-L)
- PMC
- PMC6889499
- OpenAlex
- W2990212745
- Cited by
- 32
- References
- 20
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 8 · 2023: 6 · 2022: 3 · 2021: 4 · 2020: 6
- Type
- data paper
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Scientific Data (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- DH | National Institute for Health Research (BRC369/CN/SB/101310)
- Topics
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics in Clinical Research
- Social Sciences › Law › Digitalization, Law, and Regulation
- Keywords
- data access agreement, international data sharing, data governance, harmonization, genomic data, health data, data protection, data access committees, sensitive data
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