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Enhancing Reuse of Data and Biological Material in Medical Research: From FAIR to FAIR-Health
Author(s) -
Petr Holub,
Florian Kohlmayer,
Fabian Praßer,
Michaela Th. Mayrhofer,
Irene Schlünder,
Gillian M. Martin,
Sara Casati,
Lefteris Koumakis,
Andrea Wutte,
Łukasz Kozera,
Dominik Strapagiel,
Gabriele Anton,
Gianluigi Zanetti,
Uğur Sezerman,
Maimuna Mendy,
Dalibor Valík,
Marialuisa Lavitrano,
Georges Dagher,
Kurt Zatloukal,
GertJan B. van Ommen,
JanEric Litton
Publication year - 2018
Publication title -
biopreservation and biobanking
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.545
H-Index - 34
eISSN - 1947-5535
pISSN - 1947-5543
DOI - 10.1089/bio.2017.0110
Subject(s) - biobank , interoperability , reuse , computer science , reusability , data science , process (computing) , data quality , biological data , risk analysis (engineering) , world wide web , business , engineering , bioinformatics , metric (unit) , operating system , software , marketing , biology , programming language , waste management
The known challenge of underutilization of data and biological material from biorepositories as potential resources for medical research has been the focus of discussion for over a decade. Recently developed guidelines for improved data availability and reusability-entitled FAIR Principles (Findability, Accessibility, Interoperability, and Reusability)-are likely to address only parts of the problem. In this article, we argue that biological material and data should be viewed as a unified resource. This approach would facilitate access to complete provenance information, which is a prerequisite for reproducibility and meaningful integration of the data. A unified view also allows for optimization of long-term storage strategies, as demonstrated in the case of biobanks. We propose an extension of the FAIR Principles to include the following additional components: (1) quality aspects related to research reproducibility and meaningful reuse of the data, (2) incentives to stimulate effective enrichment of data sets and biological material collections and its reuse on all levels, and (3) privacy-respecting approaches for working with the human material and data. These FAIR-Health principles should then be applied to both the biological material and data. We also propose the development of common guidelines for cloud architectures, due to the unprecedented growth of volume and breadth of medical data generation, as well as the associated need to process the data efficiently.

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