five

RDARI International Survey of Institutional Research Data Services 2019

收藏
rdr.ucl.ac.uk2020-01-21 更新2025-01-22 收录
下载链接:
https://rdr.ucl.ac.uk/articles/dataset/RDARI_International_Survey_of_Institutional_Research_Data_Services_2019/10283540/1
下载链接
链接失效反馈
官方服务:
资源简介:
This is the complete set of results from the survey of institutional research data management services conducted by the Research Data Architectures for Research Institutions (RDARI) Interest Group of the Research Data Alliance (RDA). The survey was conducted between July and November 2019. The dataset consists of 82 responses, deduplicated and with email addresses redacted where explicit consent to publish was not granted.The survey results are provided in two formats: as an Excel file, and as comma-separated values. The survey questions and answer formats are provided both in the Excel file and the accompanying readme.txt file.The RDARI International Survey of Institutional Research Data Services (2019) was intended to capture the contemporary state of research data management service provision in research institutions and in so doing establish grounds for benchmarking between institutions. In addition, it was intended to facilitate and encourage the exchange of useful information between institutions to help RDM service providers learn from each other's experiences. Besides questions relating to the scale and nature of each institution, the survey gathered data relating to technologies, governance, resourcing, costs models, uptake, and the perceived success (or otherwise) of a range of research data management services.

本数据集系由研究数据联盟(RDA)研究数据架构研究机构兴趣小组(RDARI)开展的机构研究数据管理服务调查的完整结果。该调查于2019年7月至11月间进行。数据集包含82份有效回复,已进行去重处理,并在未获得明确发布同意的情况下对电子邮件地址进行了匿名处理。调查结果以两种格式提供:Excel文件格式以及逗号分隔值格式。调查问题及其答案格式既包含在Excel文件中,也包含在附带的readme.txt文件中。2019年RDARI国际机构研究数据服务调查旨在捕捉研究机构中研究数据管理服务提供的当代状态,并在此基础上为机构间的基准测试奠定基础。此外,该调查旨在促进并鼓励机构间有用信息的交流,以帮助研究数据管理服务提供商相互借鉴经验。除了与每个机构的规模和性质相关的问题外,调查还收集了有关技术、治理、资源配置、成本模型、采纳情况以及研究数据管理服务感知成功(或失败)等方面的数据。
提供机构:
University College London
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作