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Better governance, better access: practising responsible data sharing in the METADAC governance infrastructure
Madeleine J Murtagh1, Mwenza T Blell2, Olly W Butters3
1Newcastle University, Newcastle upon Tyne, UK. Madeleine.Murtagh@newcastle.ac.uk.
Human Genomics
|April 27, 2018
Summary
Responsible data governance in genomic and biosocial research ensures participant trust and ethical data sharing. Key features include independence, transparency, interdisciplinary collaboration, and participant-centered decision-making for managing sensitive data access.
Area of Science:
- Genomic and biosocial research
- Data governance and ethics
- Longitudinal cohort studies
Background:
- Proliferating genomic and biosocial data present opportunities and challenges for integration and use.
- Open science principles conflict with managed data access systems in UK longitudinal studies, which prioritize participant consent and trust.
- Responsible data management and governance are crucial for maintaining trustworthiness in genomic and biosocial research.
Purpose of the Study:
- To explore foundational principles of a data governance infrastructure for managing ethico-social, technical, and administrative issues in data access.
- To present an ethnographic case study of the Managing Ethico-social, Technical and Administrative issues in Data ACcess (METADAC) governance model.
- To identify key structural features for responsible data sharing in genomic and biosocial research.
Main Methods:
- Ethnographic case study of the METADAC governance infrastructure.
- Analysis of the operational principles of the METADAC Access Committee.
- Examination of data access agreements for phenotype, genotype, and 'omic' data from UK longitudinal studies.
Main Results:
- Three foundational features for responsible data sharing: independence and transparency, interdisciplinarity, and participant-centric decision-making.
- The METADAC model demonstrates a human-mediated approach to ensuring reasoned and responsible data use decisions.
- Proactive international efforts aim to optimize research data use by integrating it with health, social care, and administrative data.
Conclusions:
- Effective governance of complex data assemblages requires diverse expertise, including input from study participants.
- The METADAC model offers a practical example of a governance structure that balances data access with ethical considerations.
- Participant-centric decision-making is central to achieving responsible and trustworthy data sharing practices in genomic and biosocial research.
Keywords:
Data Access Committee (DAC)Data accessData ethicsData governanceEthnographyGovernanceInterdisciplinarityParticipant involvementQualitative researchMore Related Videos
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