Functional Requirements for Research Data Repositories

Suntae Kim
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引用次数: 6

Abstract

Article history: Received 12 February 2018 Revised 20 February 2018 Accepted 27 February 2018 Research data must be testable. Science is all about verification and testing. To make data testable, tools used to produce, collect, and examine data during the research must be available. Quite often, however, these data become inaccessible once the work is over and the results being published. Hence, information and the related context must be provided on how research data are preserved and how they can be reproduced. Open Science is the international movement for making scientific research data properly accessible for research community. One of its major goals is building data repositories to foster wide dissemination of open data. The objectives of this research are to examine the features of research data, common repository platforms, and community requests for the purpose of designing functional requirements for research data repositories. To analyze the features of the research data, we use data curation profiles available from the Data Curation Center of the Purdue University, USA. For common repository platforms we examine Fedora Commons, iRODS, DataONE, Dataverse, Open Science Data Cloud (OSDC), and Figshare. We also analyze the requests from research community. To design a technical solution that would meet public needs for data accessibility and sharing, we take the requirements of RDA Repository Interest Group and the requests for the DataNest Community Platform developed by the Korea Institute of Science and Technology Information (KISTI). As a result, we particularize 75 requirement items grouped into 13 categories (metadata; identifiers; authentication and permission management; data access, policy support; publication; submission/ingest/management, data configuration, location; integration, preservation and sustainability, user interface; data and product quality). We hope that functional requirements set down in this study will be of help to organizations that consider deploying or designing data repositories.
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研究数据存储库的功能需求
文章历史:收到2018年2月12日修订2018年2月20日接受2018年2月27日研究数据必须可测试。科学就是验证和测试。为了使数据可测试,在研究过程中用于产生、收集和检查数据的工具必须可用。然而,很多时候,一旦工作结束,结果发表,这些数据就无法访问了。因此,必须提供有关如何保存研究数据以及如何复制研究数据的信息和相关背景。开放科学是一项国际运动,旨在使科学研究数据能够为研究界适当地获取。其主要目标之一是建立数据存储库,以促进开放数据的广泛传播。本研究的目的是研究研究数据的特征、公共存储库平台和社区请求,以设计研究数据存储库的功能需求。为了分析研究数据的特征,我们使用了美国普渡大学数据管理中心提供的数据管理概况。对于公共存储库平台,我们研究了Fedora Commons、iRODS、DataONE、Dataverse、Open Science Data Cloud (OSDC)和Figshare。我们还分析了来自科研团体的需求。为了设计一个能够满足公众对数据访问和共享需求的技术解决方案,我们考虑了RDA知识库兴趣组的要求和韩国科学技术信息研究所(KISTI)开发的DataNest社区平台的要求。作为结果,我们将75个需求项划分为13个类别(元数据;标识符;认证和权限管理;数据获取、政策支持;出版;提交/摄取/管理、数据配置、定位;集成、保存和可持续性、用户界面;数据和产品质量)。我们希望本研究中列出的功能需求将对考虑部署或设计数据存储库的组织有所帮助。
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