Data Science Resource

数据科学资源

• 批准号: 10006829
• 负责人: Deborah L McGuinness
• 金额: $ 25.69万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10006829
• 关键词: Address; Area; Bioinformatics; Cataloging; Catalogs; Collaborations; Collection; Communication; Communities; Community Health; Community Outreach; Consult; Data; Data Collection; Data Science; Databases; Development; Environmental Exposure; Environmental Health; Epidemiology; Evaluation; Evolution; FAIR principles; Feedback; Future; Goals; Guidelines; Health; Human; Infrastructure; Ingestion; Institutes; Laboratories; Language; Lead; Leadership; Life Cycle Stages; Link; Metadata; Methodology; Mission; Modeling; Ontology; Outcome; Participant; Process; Published Comment; Research; Research Personnel; Research Support; Resources; Science; Semantics; Services; Terminology; Time; Update; Vocabulary; computer based Semantic Analysis; crosslink; data access; data centers; data dictionary; data harmonization; data interoperability; data management; data portal; data resource; data science resource; data standards; data warehouse; design; experience; flexibility; health data; interoperability; medical schools; meetings; ontology development; open source; outreach; programs; prototype; tool; virtual; working group

DATA SCIENCE RESOURCE SUMMARY The HHEAR Data Science Resource (DSR) will accelerate research in environmental health sciences by creating a community-vetted HHEAR ontology that is used to power the HHEAR data portal, and more broadly to facilitate connections between a wide range of environmental health data. The DSR provides ontology expertise, ontology identification and mapping criteria, community outreach and engagement, and overall semantic guidance to support the HHEAR Data Center's data portal that provides findable, accessible, interoperable, and reusable exposure and health data. The DSR focuses on interoperable terminology connecting to and leveraging best-in-class vocabularies, including the evolution of our current CHEAR ontology into an HHEAR ontology as needed for the broader scope and new study support. Indeed, our experiences in building the CHEAR ontology inform and guide our plans for HHEAR. We also aim to actively lead and continue to build an exposome and health community striving toward best practice data and metadata vocabularies and standards, with reuse and link as appropriate. The resource contributes semantic leadership, processes, tools, and semantic design and infrastructure evolution consulting to support finding, prioritizing, analysis for gaps/coverage, and effectively using appropriate vocabulary and use cases. Guided by experts in data science, bioinformatics, and domains, we will actively co-lead and participate in community working group(s) with the aim of creating open-source, community-driven annotated collections of data and metadata standards. Ultimately, these goals have the potential to provide a community-driven and community-accepted language for exposure science. Further, the methodologies are being designed with a goal of living beyond this program, providing guidance for future participants and communities. The ontology and the process facilitates the goals of the HHEAR Program in expediting progress in exposome-related research, analyses, and collaborations, most notably by having unambiguous use of terminology and processes for updates. The DSR's specific aims are to provide the program-wide HHEAR ontology along with criteria for evaluating and cataloging relevant standards. We will co-lead community engagement and outreach, and support the DRMC in ontology usage of the Data Center's robust data harmonization and access portal. Leveraging our existing infrastructure and expertise will overcome the need for a long implementation process fraught with challenges—we have already encountered and overcome many such challenges in implementing the CHEAR DC, and will be able to flexibly respond to the needs of the HHEAR Network.

数据科学资源摘要 HHEAR数据科学资源(DSR)将通过以下方式加快环境健康科学的研究 创建社区审查的HHEAR本体，用于支持HHEAR数据门户，更广泛地说 以促进广泛的环境健康数据之间的连接。DSR提供了本体 专门知识、本体识别和绘图标准、社区外联和参与，以及总体 支持HHEAR数据中心数据门户的语义指导，该数据门户提供可查找、可访问、 可互操作、可重复使用的暴露和健康数据。DSR侧重于可互操作的术语 连接并利用一流的词汇表，包括我们当前CHEAR本体的演变 为更广泛的范围和新的研究支持提供所需的HHEAR本体。事实上，我们在这方面的经验 构建CHEAR本体，为我们的HHEAR计划提供信息和指导。我们的目标也是积极领导和 继续建立一个宣传组和健康社区，努力实现最佳实践数据和元数据 词汇表和标准，以及适当的重用和链接。该资源有助于语义领导力， 流程、工具以及语义设计和基础设施演进咨询，以支持查找、确定优先顺序、 分析差距/覆盖面，并有效地使用适当的词汇和用例。在专家的指导下 数据科学、生物信息学和领域，我们将积极共同领导和参与社区工作 集团(S)，目标是创建开源的、社区驱动的带注释的数据和元数据集合 标准。最终，这些目标有可能提供一个社区驱动和社区接受的 曝光科学的语言。此外，方法论的设计目标是超越这一点 计划，为未来的参与者和社区提供指导。本体论和过程便于 HHEAR计划的目标是加快与曝光组相关的研究、分析和 协作，最显著的是明确使用术语和更新流程。 DSR的具体目标是提供项目范围的HHEAR本体以及评估标准 并对相关标准进行编目。我们将共同领导社区参与和外展，并支持 DRMC在数据中心强大的数据协调和访问门户的本体使用中。利用我们的 现有的基础设施和专业知识将克服长期实施过程的需要 挑战-我们在实施CHEAR时已经遇到并克服了许多这样的挑战 并将能够灵活地响应HHEAR网络的需求。