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Better governance, better access: practising responsible data sharing in the METADAC governance infrastructure

Overview of attention for article published in Human Genomics, April 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#48 of 564)
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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31 X users

Citations

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34 Dimensions

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102 Mendeley
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Title
Better governance, better access: practising responsible data sharing in the METADAC governance infrastructure
Published in
Human Genomics, April 2018
DOI 10.1186/s40246-018-0154-6
Pubmed ID
Authors

Madeleine J. Murtagh, Mwenza T. Blell, Olly W. Butters, Lorraine Cowley, Edward S. Dove, Alissa Goodman, Rebecca L. Griggs, Alison Hall, Nina Hallowell, Meena Kumari, Massimo Mangino, Barbara Maughan, Melinda C. Mills, Joel T. Minion, Tom Murphy, Gillian Prior, Matthew Suderman, Susan M. Ring, Nina T. Rogers, Stephanie J. Roberts, Catherine Van der Straeten, Will Viney, Deborah Wiltshire, Andrew Wong, Neil Walker, Paul R. Burton

Abstract

Genomic and biosocial research data about individuals is rapidly proliferating, bringing the potential for novel opportunities for data integration and use. The scale, pace and novelty of these applications raise a number of urgent sociotechnical, ethical and legal questions, including optimal methods of data storage, management and access. Although the open science movement advocates unfettered access to research data, many of the UK's longitudinal cohort studies operate systems of managed data access, in which access is governed by legal and ethical agreements between stewards of research datasets and researchers wishing to make use of them. Amongst other things, these agreements aim to respect the reasonable expectations of the research participants who provided data and samples, as expressed in the consent process. Arguably, responsible data management and governance of data and sample use are foundational to the consent process in longitudinal studies and are an important source of trustworthiness in the eyes of those who contribute data to genomic and biosocial research. This paper presents an ethnographic case study exploring the foundational principles of a governance infrastructure for Managing Ethico-social, Technical and Administrative issues in Data ACcess (METADAC), which are operationalised through a committee known as the METADAC Access Committee. METADAC governs access to phenotype, genotype and 'omic' data and samples from five UK longitudinal studies. Using the example of METADAC, we argue that three key structural features are foundational for practising responsible data sharing: independence and transparency; interdisciplinarity; and participant-centric decision-making. We observe that the international research community is proactively working towards optimising the use of research data, integrating/linking these data with routine data generated by health and social care services and other administrative data services to improve the analysis, interpretation and utility of these data. The governance of these new complex data assemblages will require a range of expertise from across a number of domains and disciplines, including that of study participants. Human-mediated decision-making bodies will be central to ensuring achievable, reasoned and responsible decisions about the use of these data; the METADAC model described in this paper provides an example of how this could be realised.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 102 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 16%
Student > Ph. D. Student 14 14%
Student > Bachelor 7 7%
Student > Master 6 6%
Student > Doctoral Student 6 6%
Other 19 19%
Unknown 34 33%
Readers by discipline Count As %
Social Sciences 15 15%
Medicine and Dentistry 12 12%
Computer Science 11 11%
Agricultural and Biological Sciences 5 5%
Business, Management and Accounting 3 3%
Other 20 20%
Unknown 36 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 July 2023.
All research outputs
#2,060,528
of 25,382,440 outputs
Outputs from Human Genomics
#48
of 564 outputs
Outputs of similar age
#42,735
of 339,863 outputs
Outputs of similar age from Human Genomics
#2
of 12 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 564 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 339,863 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.