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Quantifying the impact of public omics data.

ABSTRACT: The amount of omics data in the public domain is increasing every year. Modern science has become a data-intensive discipline. Innovative solutions for data management, data sharing, and for discovering novel datasets are therefore increasingly required. In 2016, we released the first version of the Omics Discovery Index (OmicsDI) as a light-weight system to aggregate datasets across multiple public omics data resources. OmicsDI aggregates genomics, transcriptomics, proteomics, metabolomics and multiomics datasets, as well as computational models of biological processes. Here, we propose a set of novel metrics to quantify the attention and impact of biomedical datasets. A complete framework (now integrated into OmicsDI) has been implemented in order to provide and evaluate those metrics. Finally, we propose a set of recommendations for authors, journals and data resources to promote an optimal quantification of the impact of datasets.

SUBMITTER: Perez-Riverol Y

PROVIDER: S-EPMC6683138 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Quantifying the impact of public omics data.

Perez-Riverol Yasset Y Zorin Andrey A Dass Gaurhari G Vu Manh-Tu MT Xu Pan P Glont Mihai M Vizcaíno Juan Antonio JA Jarnuczak Andrew F AF Petryszak Robert R Ping Peipei P Hermjakob Henning H

Nature communications 20190805 1

The amount of omics data in the public domain is increasing every year. Modern science has become a data-intensive discipline. Innovative solutions for data management, data sharing, and for discovering novel datasets are therefore increasingly required. In 2016, we released the first version of the Omics Discovery Index (OmicsDI) as a light-weight system to aggregate datasets across multiple public omics data resources. OmicsDI aggregates genomics, transcriptomics, proteomics, metabolomics and ...[more]

PMID: 31383865

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