Institute for Interdisciplinary Data Science, Research Computing and Data Services, University of Idaho, Moscow, ID, 83844-2358, USA.
Department of Biological Sciences, Boise State University, Boise, ID, 83725-1515, USA.
BMC Res Notes. 2022 Mar 18;15(1):106. doi: 10.1186/s13104-022-05996-3.
Open science and open data within scholarly research programs are growing both in popularity and by requirement from grant funding agencies and journal publishers. A central component of open data management, especially on collaborative, multidisciplinary, and multi-institutional science projects, is documentation of complete and accurate metadata, workflow, and source code in addition to access to raw data and data products to uphold FAIR (Findable, Accessible, Interoperable, Reusable) principles. Although best practice in data/metadata management is to use established internationally accepted metadata schemata, many of these standards are discipline-specific making it difficult to catalog multidisciplinary data and data products in a way that is easily findable and accessible. Consequently, scattered and incompatible metadata records create a barrier to scientific innovation, as researchers are burdened to find and link multidisciplinary datasets. One possible solution to increase data findability, accessibility, interoperability, reproducibility, and integrity within multi-institutional and interdisciplinary projects is a centralized and integrated data management platform. Overall, this type of interoperable framework supports reproducible open science and its dissemination to various stakeholders and the public in a FAIR manner by providing direct access to raw data and linking protocols, metadata and supporting workflow materials.
在学术研究计划中,开放科学和开放数据越来越受到欢迎,并且受到资助机构和期刊出版商的要求。开放数据管理的一个核心组成部分,特别是在协作的、多学科的和多机构的科学项目中,除了提供原始数据和数据产品以维护 FAIR(可发现、可访问、可互操作、可重复使用)原则之外,还需要记录完整和准确的元数据、工作流程和源代码。虽然数据/元数据管理的最佳实践是使用既定的国际公认的元数据模式,但其中许多标准是特定于学科的,这使得难以以易于发现和访问的方式对多学科数据和数据产品进行编目。因此,分散和不兼容的元数据记录阻碍了科学创新,因为研究人员需要找到并链接多学科数据集。增加多机构和跨学科项目中数据可发现性、可访问性、互操作性、可重复性和完整性的一个可能解决方案是集中式和集成的数据管理平台。总的来说,这种互操作框架通过提供对原始数据的直接访问并链接协议、元数据和支持工作流程材料,以 FAIR 的方式支持可重复的开放科学及其向各种利益相关者和公众的传播。