Center for Public Health Genomics, School of Medicine, University of Virginia, 22908, Charlottesville, VA, USA.
School of Data Science, University of Virginia, Charlottesville VA 22904, Charlottesville, VA, USA.
Sci Data. 2022 Sep 8;9(1):553. doi: 10.1038/s41597-022-01619-5.
The biomedical research community is investing heavily in biomedical cloud platforms. Cloud computing holds great promise for addressing challenges with big data and ensuring reproducibility in biology. However, despite their advantages, cloud platforms in and of themselves do not automatically support FAIRness. The global push to develop biomedical cloud platforms has led to new challenges, including platform lock-in, difficulty integrating across platforms, and duplicated effort for both users and developers. Here, we argue that these difficulties are systemic and emerge from incentives that encourage development effort on self-sufficient platforms and data repositories instead of interoperable microservices. We argue that many of these issues would be alleviated by prioritizing microservices and access to modular data in smaller chunks or summarized form. We propose that emphasizing modularity and interoperability would lead to a more powerful Unix-like ecosystem of web services for biomedical analysis and data retrieval. We challenge funders, developers, and researchers to support a vision to improve interoperability through microservices as the next generation of cloud-based bioinformatics.
生物医学研究界正在大力投资生物医学云平台。云计算在解决大数据挑战和确保生物学可重复性方面具有巨大的潜力。然而，尽管它们具有优势，但云平台本身并不能自动支持 FAIRness。全球开发生物医学云平台的努力带来了新的挑战，包括平台锁定、跨平台集成困难以及用户和开发人员的重复工作。在这里，我们认为这些困难是系统性的，源于鼓励在自给自足的平台和数据存储库上进行开发工作而不是可互操作的微服务的激励措施。我们认为，通过优先考虑微服务以及以较小的块或摘要形式访问模块化数据，可以缓解许多这些问题。我们提出，强调模块化和互操作性将导致更强大的类似 Unix 的生物医学分析和数据检索网络服务生态系统。我们挑战资助者、开发人员和研究人员支持通过微服务提高互操作性的愿景，将其作为下一代基于云的生物信息学。
