TY - JOUR
T1 - FAIR Data Cube, a FAIR data infrastructure for integrated multi-omics data analysis
AU - Liao, Xiaofeng
AU - Ederveen, Thomas H A.
AU - Niehues, Anna
AU - de Visser, Casper
AU - Huang, Junda
AU - Badmus, Firdaws
AU - Doornbos, Cenna
AU - Orlova, Yuliia
AU - Kulkarni, Purva
AU - van der Velde, K. Joeri
AU - Swertz, Morris A.
AU - Brandt, Martin
AU - van Gool, Alain J.
AU - ’t Hoen, Peter A.C.
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/12
Y1 - 2024/12
N2 - Motivation: We are witnessing an enormous growth in the amount of molecular profiling (-omics) data. The integration of multi-omics data is challenging. Moreover, human multi-omics data may be privacy-sensitive and can be misused to de-anonymize and (re-)identify individuals. Hence, most biomedical data is kept in secure and protected silos. Therefore, it remains a challenge to re-use these data without infringing the privacy of the individuals from which the data were derived. Federated analysis of Findable, Accessible, Interoperable, and Reusable (FAIR) data is a privacy-preserving solution to make optimal use of these multi-omics data and transform them into actionable knowledge.Results: The Netherlands X-omics Initiative is a National Roadmap Large-Scale Research Infrastructure aiming for efficient integration of data generated within X-omics and external datasets. To facilitate this, we developed the FAIR Data Cube (FDCube), which adopts and applies the FAIR principles and helps researchers to create FAIR data and metadata, to facilitate re-use of their data, and to make their data analysis workflows transparent, and in the meantime ensure data security and privacy.
AB - Motivation: We are witnessing an enormous growth in the amount of molecular profiling (-omics) data. The integration of multi-omics data is challenging. Moreover, human multi-omics data may be privacy-sensitive and can be misused to de-anonymize and (re-)identify individuals. Hence, most biomedical data is kept in secure and protected silos. Therefore, it remains a challenge to re-use these data without infringing the privacy of the individuals from which the data were derived. Federated analysis of Findable, Accessible, Interoperable, and Reusable (FAIR) data is a privacy-preserving solution to make optimal use of these multi-omics data and transform them into actionable knowledge.Results: The Netherlands X-omics Initiative is a National Roadmap Large-Scale Research Infrastructure aiming for efficient integration of data generated within X-omics and external datasets. To facilitate this, we developed the FAIR Data Cube (FDCube), which adopts and applies the FAIR principles and helps researchers to create FAIR data and metadata, to facilitate re-use of their data, and to make their data analysis workflows transparent, and in the meantime ensure data security and privacy.
KW - Data sovereignty
KW - FAIR
KW - FAIR Data Cube
KW - Federated analysis
KW - Metadata
KW - Multi-omics
UR - http://www.scopus.com/inward/record.url?scp=85213703884&partnerID=8YFLogxK
U2 - 10.1186/s13326-024-00321-2
DO - 10.1186/s13326-024-00321-2
M3 - Article
C2 - 39732721
AN - SCOPUS:85213703884
SN - 2041-1480
VL - 15
JO - Journal of Biomedical Semantics
JF - Journal of Biomedical Semantics
M1 - 20
ER -