Institute of Biostructures and Bioimaging, National Research Council of Italy, Naples, Italy.
Faculty of Industrial Engineering and Technology Management, Holon Institute of Technology, Holon, Israel.
Methods Inf Med. 2022 Dec;61(S 02):e116-e124. doi: 10.1055/a-1938-0533. Epub 2022 Sep 7.
One Digital Health (ODH) aims to propose a framework that merges One Health's and Digital Health's specific features into an innovative landscape. FAIR (Findable, Accessible, Interoperable, and Reusable) principles consider applications and computational agents (or, in other terms, data, metadata, and infrastructures) as stakeholders with the capacity to find, access, interoperate, and reuse data with none or minimal human intervention.
This paper aims to elicit how the ODH framework is compliant with FAIR principles and metrics, providing some thinking guide to investigate and define whether adapted metrics need to be figured out for an effective ODH Intervention setup.
An integrative analysis of the literature was conducted to extract instances of the need-or of the eventual already existing deployment-of FAIR principles, for each of the three layers (keys, perspectives and dimensions) of the ODH framework. The scope was to assess the extent of scatteredness in pursuing the many facets of FAIRness, descending from the lack of a unifying and balanced framework.
A first attempt to interpret the different technological components existing in the different layers of the ODH framework, in the light of the FAIR principles, was conducted. Although the mature and working examples of workflows for data FAIRification processes currently retrievable in the literature provided a robust ground to work on, a nonsuitable capacity to fully assess FAIR aspects for highly interconnected scenarios, which the ODH-based ones are, has emerged. Rooms for improvement are anyway possible to timely deal with all the underlying features of topics like the delivery of health care in a syndemic scenario, the digital transformation of human and animal health data, or the digital nature conservation through digital technology-based intervention.
ODH pillars account for the availability (findability, accessibility) of human, animal, and environmental data allowing a unified understanding of complex interactions (interoperability) over time (reusability). A vision of integration between these two worlds, under the vest of ODH Interventions featuring FAIRness characteristics, toward the development of a systemic lookup of health and ecology in a digitalized way, is therefore auspicable.
一个数字健康（ODH）旨在提出一个框架，将一个健康和数字健康的具体特点融合到一个创新的领域。FAIR（可发现、可访问、可互操作和可重用）原则将应用程序和计算代理（或者，换句话说，数据、元数据和基础设施）视为具有发现、访问、互操作和重用数据的能力的利益相关者，而无需或只需最小的人工干预。
本文旨在探讨 ODH 框架如何符合 FAIR 原则和指标，为研究和定义是否需要制定适应的指标以实现有效的 ODH 干预提供一些思路。
对文献进行综合分析，以提取 ODH 框架的三个层次（关键、视角和维度）中每个层次对 FAIR 原则的需求或已经存在的部署实例。范围是评估从缺乏统一和平衡的框架出发，追求 FAIR 性的许多方面的分散程度。
尝试根据 FAIR 原则解释 ODH 框架不同层中的不同技术组件。尽管文献中可检索到的数据 FAIR 化流程工作流程的成熟和可行示例为我们提供了坚实的基础，但对于高度互联的场景（如基于 ODH 的场景），我们还需要更好的能力来全面评估 FAIR 方面。不过，仍然有可能及时处理医疗保健交付在综合征场景、人类和动物健康数据的数字化转型，或通过基于数字技术的干预进行数字自然保护等主题的所有潜在特征。
ODH 支柱考虑了人类、动物和环境数据的可用性（可发现性、可访问性），从而允许对复杂交互（互操作性）进行统一理解，随着时间的推移（可重用性）。因此，可以预见，这两个世界之间的整合愿景，在具有 FAIR 特征的 ODH 干预的掩护下，朝着以数字化方式发展健康和生态的系统查找发展。
