Hybrid Technology Hub - Centre of Excellence, Faculty of Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo 0317, Norway.
Department of Informatics, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo 0315, Norway.
Bioinformatics. 2022 Aug 2;38(15):3812-3817. doi: 10.1093/bioinformatics/btac362.
Technical advances have revolutionized the life sciences and researchers commonly face challenges associated with handling large amounts of heterogeneous digital data. The Findable, Accessible, Interoperable and Reusable (FAIR) principles provide a framework to support effective data management. However, implementing this framework is beyond the means of most researchers in terms of resources and expertise, requiring awareness of metadata, policies, community agreements and other factors such as vocabularies and ontologies.
We have developed the Globally Accessible Distributed Data Sharing (GADDS) platform to facilitate FAIR-like data-sharing in cross-disciplinary research collaborations. The platform consists of (i) a blockchain-based metadata quality control system, (ii) a private cloud-like storage system and (iii) a version control system. GADDS is built with containerized technologies, providing minimal hardware standards and easing scalability, and offers decentralized trust via transparency of metadata, facilitating data exchange and collaboration. As a use case, we provide an example implementation in engineered living material technology within the Hybrid Technology Hub at the University of Oslo.
Demo version available at https://github.com/pavelvazquez/GADDS.
Supplementary data are available at Bioinformatics online.
技术进步彻底改变了生命科学领域,研究人员普遍面临着处理大量异构数字数据的相关挑战。可发现性、可访问性、互操作性和可重用性(FAIR)原则为有效数据管理提供了框架。然而,就资源和专业知识而言,大多数研究人员都无法实施这一框架,需要了解元数据、政策、社区协议以及词汇和本体等其他因素。
我们开发了全球可访问分布式数据共享(GADDS)平台,以促进跨学科研究合作中的 FAIR 式数据共享。该平台由(i)基于区块链的元数据质量控制系统、(ii)类似私有云的存储系统和(iii)版本控制系统组成。GADDS 采用了容器化技术,提供了最低的硬件标准和易于扩展的特性,并通过元数据的透明度提供去中心化的信任,从而促进数据交换和协作。作为一个用例,我们在奥斯陆大学的混合技术中心提供了工程化活体材料技术中的一个实现示例。
可在 https://github.com/pavelvazquez/GADDS 上获得演示版本。
补充数据可在生物信息学在线获得。