Human Health Exposure Analysis Resource (HHEAR) Data Center

人类健康暴露分析资源 (HHEAR) 数据中心

• 批准号: 10595949
• 负责人: SUSAN L TEITELBAUM
• 金额: $ 25.16万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-30 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10595949
• 关键词: Administrative Supplement; Characteristics; Communities; Community Health; Custom; Data; Data Set; Development; Environmental Exposure; Environmental Health; Environmental Impact; Epidemiology; Evaluation; Extramural Activities; FAIR principles; Foundations; Goals; Health; Human; Laboratories; Measurement; Metadata; Monitor; Positioning Attribute; Preparation; Process; Readability; Research; Research Personnel; Resources; Science; Self Assessment; Statistical Data Interpretation; Surveys; United States National Institutes of Health; Vocabulary; application programming interface; data centers; data harmonization; data infrastructure; data repository; data resource; data reuse; data science resource; design; next generation; programs; repository

PROJECT SUMMARY The Human Health Exposure Analysis Resource (HHEAR) provides the extramural research community access to laboratory and statistical analyses to add or expand the inclusion of environmental exposures in their research. Through these efforts, the HHEAR-Data Center aims to be a data science resource for the environmental health community, maximizing the potential use, reuse and impact of environmental exposure data. An integral part of this initiative, the HHEAR Data Repository was created to house all data generated within HHEAR labs and provided by HHEAR investigators for epidemiologic and exposure studies within the HHEAR network. Key strengths of this repository are the breadth of high-quality measurements of environmental health data, harmonization of disparate datasets to a common vocabulary and customized downloads that can be saved, stored and shared among users. To augment the Repository’s existing capabilities, we propose two specific aims to enhance the use, utility and impact of the HHEAR Data Repository. First, we will enhance the alignment of the HHEAR Data Repository with the FAIR (Findability, Accessibility, Interoperability and Reusability) Data Principles and the desirable characteristics of data repositories detailed by the National Institutes of Health. We will then develop and implement evaluation metrics designed to align with the FAIR Data Principles. These metrics will monitor use, utility and impact in order to stimulate continuous improvement throughout the lifecycle of the HHEAR Data Repository. To construct our enhancement plan, we conducted self-assessments of the Repository to evaluate its FAIR-ness, desirable characteristics and utility of existing evaluation metrics. These self-assessments revealed gaps in machine-readable metadata to describe the data-generating processes and detailed provenance of datasets from HHEAR studies. Increasing accessibility to metadata, potentially through metadata explorers or application programming interfaces, was identified as another target for enhancement. In addition, self- assessments led to a recognized need for user surveys to augment existing usage metrics generated by monitoring access and downloads within the HHEAR Data Repository. We propose clear milestones to implement these and other planned enhancements during the supplement period. By increasing alignment with the FAIR data principles and expanding evaluation metrics of the HHEAR Repository, we will be able to maximize the benefit of the HHEAR program to the scientific community and provide the data infrastructure for the next generation of exposome science.

项目摘要 人类健康暴露分析资源（HHEAR）提供了校外研究社区 访问实验室和统计分析，以增加或扩展其包含环境暴露 研究。通过这些努力，HHEAR-DATA中心的目标是成为数据科学资源 环境卫生社区，最大程度地利用，再利用和影响环境暴露 数据。该计划不可或缺的一部分，创建了Hear数据存储库来容纳所有生成的数据 在HHEAR实验室中，由HEAR研究人员提供，用于流行病学和暴露研究。 HHEAR网络。该存储库的关键优势是高质量测量的广度 环境健康数据，将不同数据集的协调与常见的词汇和定制 可以在用户中保存，存储和共享的下载。增加存储库的现有 功能，我们提出了两个特定的目标，以增强HHEAR数据的使用，实用性和影响 存储库。首先，我们将增强HEAR数据存储库与公平的对齐（可发现性， 可访问性，互操作性和可重用性）数据原理和数据的理想特征 国立卫生研究院详细介绍的存储库。然后，我们将开发和实施评估 旨在与公平数据原则保持一致的指标。这些指标将监视使用，实用性和影响 为了在HHEAR数据存储库的整个生命周期中刺激持续改进。到 构建我们的增强计划，我们进行了对存储库的自我评估，以评估其公平性， 现有评估指标的理想特征和效用。这些自我评估揭示了 机器可读的元数据来描述数据集的数据生成过程和详细的出处 来自HHEAR研究。增加对元数据的可访问性，可能通过元数据探险家或 应用程序编程界面被确定为增强的另一个目标。另外，自我 评估导致公认的用户调查需要增加现有的用法指标 监视HEAR数据存储库中的访问和下载。我们建议明确的里程碑 在补充期间，实施这些和其他计划的增强功能。通过增加与 公平的数据原则和扩展HHEAR存储库的评估指标，我们将能够 最大化HHEAR计划对科学界的好处，并为数据基础架构提供 下一代的外科科学。