| Literature DB >> 29695297 |
Madeleine J Murtagh1, Mwenza T Blell2, Olly W Butters3, Lorraine Cowley3, Edward S Dove4, Alissa Goodman5, Rebecca L Griggs6, Alison Hall7, Nina Hallowell8, Meena Kumari9, Massimo Mangino10, Barbara Maughan10, Melinda C Mills8, Joel T Minion3, Tom Murphy5, Gillian Prior11, Matthew Suderman6, Susan M Ring6, Nina T Rogers12, Stephanie J Roberts3, Catherine Van der Straeten13,14, Will Viney15, Deborah Wiltshire16, Andrew Wong12, Neil Walker17, Paul R Burton3.
Abstract
BACKGROUND: 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.Entities:
Keywords: Data Access Committee (DAC); Data access; Data ethics; Data governance; Ethnography; Governance; Interdisciplinarity; Participant involvement; Qualitative research
Mesh:
Year: 2018 PMID: 29695297 PMCID: PMC5918902 DOI: 10.1186/s40246-018-0154-6
Source DB: PubMed Journal: Hum Genomics ISSN: 1473-9542 Impact factor: 4.639
Classes of data and their access regulation
| Data type and sensitivity | Data available from | Governance | Data distribution | |
|---|---|---|---|---|
| Class 1 | Low risk survey/phenotype-only data, e.g. social, economic, psychological and health data. | UK Data Archive | Requires registered access—online (clickable) end-user licences. | Data is distributed by the UK Data Archive. |
| Class 2 | Low sensitivity genetic-only data, e.g. genome-wide single nucleotide polymorphism [SNP] data generated from a standard chip with no phenotype information except gender and a coarse measure of area of residence. | European Genome-phenome Archive (EGA) | Requires application to the Sanger DAC, administrative decision based on algorithm of criteria for access. | Data are distributed by the EGA. |
| Class 3 | Potentially disclosive survey/phenotype-only data, e.g. small geographic area. Requires application to a study-based Data Access Committee made up of study investigators and study technical staff. | Study DAC | Data may be issued on special licence or may be accessible only in on or off-site data safe havens. | Data is distributed, or the data safe haven hosted, by the study. |
| Class 4 | New forms of genetic-only data, e.g. exome sequence and epigenetic data, are reviewed by METADAC until their ethical implication/sensitivity is established. | METADAC | Application requires review and approval from the METADAC Access Committee. Application includes signed agreement to conditions of use. Data use is monitored annually. | Data are distributed by the EGA. |
| Class 5 | Genetic-only data with known ethical issues, e.g. incidental findings risk in exome data. | METADAC | Application requires review and approval from the METADAC Access Committee. Application includes signed agreement to conditions of use. Data use is monitored annually. | Data are distributed by the EGA. |
| Class 6 | Biological samples. Use of biological samples will always require additional oversight for ethical and scientific reasons. | METADAC | Application requires independent scientific review and approval from the METADAC Access Committee. | Samples are issued by the relevant study under Material Transfer Agreements. |
| Class 7 | Any combination of Classes 1 to 6, e.g. individual-level phenotype data linked to genotype data or samples, is potentially more disclosive than any one class of data alone. | METADAC | Application requires review and approval from the METADAC Access Committee. Application includes signed agreement to conditions of use. Data use is monitored annually. | Combined datasets are issued on unique IDs and distributed by the study and EGA. |
| Class 8 | Non-research data. High risk when multiple variables are combined. | Various | Certain administrative datasets, e.g. education and criminal records, are available for research via the Administrative Data Research Network. Individual-level health data is available for research via NHS Digital). | Various |
METADAC assessment criteria
| 1. The application has been submitted by bona fide researchers (using the MRC definition [ |