Quantifying the impact of public omics data
Quantifying the impact of public omics data
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DOI：
10.1038/s41467-019-11461-w
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发表时间：
2019-08-05
影响因子：
16.6
通讯作者：
Hermjakob, Henning
中科院分区：
文献类型：
--
作者：
Perez-Riverol, Yasset;Zorin, Andrey;Hermjakob, Henning
公共领域的组学数据量每年都在增加。现代科学已经成为一门数据密集型学科。因此，越来越需要用于数据管理、数据共享和发现新数据集的创新解决方案。2016年，我们发布了第一个版本的组学发现索引（OmicsDI），作为一个轻量级系统，用于聚合多个公共组学数据资源的数据集。OmicsDI汇集了基因组学、转录组学、蛋白质组学、代谢组学和多组学数据集，以及生物过程的计算模型。在这里，我们提出了一组新的指标来量化生物医学数据集的关注和影响。为了提供和评估这些指标，已经实现了一个完整的框架（现在集成到OmicsDI中）。最后，我们为作者、期刊和数据资源提出了一系列建议，以促进数据集影响的最佳量化。
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.