Long Term Interoperability of Distributed Research Data Infrastructures

Marius Politze, Yusra Shakeel, Siream Hunke, Philipp Ost, Rossella Aversa, Benedikt Heinrichs, Ilona Lang
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Abstract

Research institutions have established a variety of research data infrastructures that orient towards discipline or methodology specific needs of their respective research community. Technically, these infrastructures ultimately are based on “off-the-shelf” hardware and software building blocks – both commercial and open-source. While such “enterprise ready” infrastructures can scale well, they apt to data silos and typically do not adhere to scientific standards like the FAIR (Findability, Accessibility, Interoperability, Reusability) principles out of the box. Using common architecture concepts such as the FAIR Digital Object (FAIR DO) allows interconnection of these silos by adding a long term interoperability layer on top of the existing infrastructure components. The presented approach provides a practical solution for interconnecting distributed research data infrastructures to national (like NFDI) and international (like EOSC and Gaia-X) infrastructures and preventing the creation of data silos. By allowing existing data infrastructures to make data FAIR, we enable researchers to access and reuse data from different domains, facilitating cross-disciplinary research and advancing new methods for scientific discoveries.
分布式研究数据基础设施的长期互操作性
研究机构已经建立了各种研究数据基础设施,这些基础设施面向各自研究社区的学科或方法特定需求。从技术上讲,这些基础设施最终都是基于“现成的”硬件和软件构建块——既有商业的,也有开源的。虽然这样的“企业就绪”基础设施可以很好地扩展,但它们倾向于数据孤岛,通常不遵循开箱即用的科学标准,如FAIR(可查找性、可访问性、互操作性、可重用性)原则。使用诸如FAIR Digital Object (FAIR DO)之类的公共体系结构概念,通过在现有基础设施组件之上添加长期互操作性层,可以实现这些竖井的互连。所提出的方法为将分布式研究数据基础设施与国家(如NFDI)和国际(如EOSC和gia - x)基础设施互连提供了一种实用的解决方案,并防止了数据孤岛的产生。通过允许现有的数据基础设施使数据公平,我们使研究人员能够访问和重用来自不同领域的数据,促进跨学科研究和推进科学发现的新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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