PlatformTM, a standards-based data custodianship platform for translational medicine research.


Journal

Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192

Informations de publication

Date de publication:
13 08 2019
Historique:
received: 23 10 2018
accepted: 25 07 2019
entrez: 15 8 2019
pubmed: 15 8 2019
medline: 21 8 2020
Statut: epublish

Résumé

Biomedical informatics has traditionally adopted a linear view of the informatics process (collect, store and analyse) in translational medicine (TM) studies; focusing primarily on the challenges in data integration and analysis. However, a data management challenge presents itself with the new lifecycle view of data emphasized by the recent calls for data re-use, long term data preservation, and data sharing. There is currently a lack of dedicated infrastructure focused on the 'manageability' of the data lifecycle in TM research between data collection and analysis. Current community efforts towards establishing a culture for open science prompt the creation of a data custodianship environment for management of TM data assets to support data reuse and reproducibility of research results. Here we present the development of a lifecycle-based methodology to create a metadata management framework based on community driven standards for standardisation, consolidation and integration of TM research data. Based on this framework, we also present the development of a new platform (PlatformTM) focused on managing the lifecycle for translational research data assets.

Identifiants

pubmed: 31409798
doi: 10.1038/s41597-019-0156-9
pii: 10.1038/s41597-019-0156-9
pmc: PMC6692384
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

149

Subventions

Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/I000771/1
Pays : United Kingdom
Organisme : Innovative Medicines Initiative (IMI)
ID : 115446 & 115308
Pays : International
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/E025080/1
Pays : United Kingdom
Organisme : Innovative Medicines Initiative (IMI)
ID : 115446
Pays : International
Organisme : Innovative Medicines Initiative (IMI)
ID : 115308
Pays : International

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Auteurs

Ibrahim Emam (I)

Data Science Institute, Imperial College London, London, UK. i.emam@imperial.ac.uk.

Vahid Elyasigomari (V)

Data Science Institute, Imperial College London, London, UK.

Alex Matthews (A)

Clinical Research Centre, University of Surrey, Guildford, UK.

Stelios Pavlidis (S)

Data Science Institute, Imperial College London, London, UK.

Philippe Rocca-Serra (P)

Oxford e-Research Centre, University of Oxford, Oxford, UK.

Florian Guitton (F)

Data Science Institute, Imperial College London, London, UK.

Denny Verbeeck (D)

Janssen Pharmaceutica NV, Beerse, Belgium.

Lucinda Grainger (L)

Clinical Research Centre, University of Surrey, Guildford, UK.

Erica Borgogni (E)

GSK Vaccines Srl, Siena, Italy.

Giuseppe Del Giudice (G)

GSK Vaccines Srl, Siena, Italy.

Mansoor Saqi (M)

Data Science Institute, Imperial College London, London, UK.

Paul Houston (P)

CDISC, Clinical Data Interchange Standards Consortium and CDISC EU Foundation, London, UK.

Yike Guo (Y)

Data Science Institute, Imperial College London, London, UK.

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Classifications MeSH