HEPData: the unique publication-related data repository in particle physics

HEPData：粒子物理学领域唯一的与出版物相关的数据存储库

• 批准号: ST/S000720/1
• 负责人: Richard Keith Ellis
• 金额: $ 25.19万
• 依托单位: Durham University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ST%2FS000720%2F1
• 关键词: HEPData; unique; publication; related; data

HEPData is the primary repository for publication-related data from particle physics experiments. It responds to a community need to share, manage and preserve data in a form that it can be easily re-used. It is also one of the major elements in fulfilling the STFC and RCUK policies for the management and sharing of scientific data, applied to the particular instance of particle physics. If HEPData did not exist, modern concerns about data management would require the project to be undertaken. The Durham High-Energy Physics Database (HEPData) has been built up over the past four decades as a unique open-access repository for publication-related high-level data. It contains results from more than 8500 experimental particle physics papers, typically the numbers behind the plots or tables that appear in publications. High energy physics data is either `raw',`derived' or `published', depending on the amount of analysis which has been performed. HEPData is nowpart of the INSPIRE collaboration, a global consortium which aims to preserve, manage and share `derived' and `published' data produced by High-Energy Physics experiments, both to ensure that publically funded data is openly available, and to maximise the scientific value obtained from the aggregation of related data.

HEPData 是粒子物理实验中与出版相关的数据的主要存储库。它满足了社区以易于重复使用的形式共享、管理和保存数据的需求。它也是履行 STFC 和 RCUK 科学数据管理和共享政策的主要要素之一，适用于粒子物理的特定实例。如果 HEPData 不存在，现代对数据管理的关注将需要开展该项目。达勒姆高能物理数据库 (HEPData) 在过去四十年中建立起来，作为与出版相关的高级数据的独特的开放访问存储库。它包含 8500 多篇实验粒子物理论文的结果，通常是出版物中出现的图表或表格后面的数字。高能物理数据可以是“原始”、“导出”或“发布”，具体取决于已执行的分析量。 HEPData 现在是 INSPIRE 合作的一部分，这是一个全球联盟，旨在保存、管理和共享高能物理实验产生的“衍生”和“发布”数据，既确保公共资助的数据公开可用，又最大限度地提高从相关数据汇总中获得的科学价值。