Data Science Resource

数据科学资源

• 批准号: 10684796
• 负责人: Deborah L McGuinness
• 金额: $ 16.97万
• 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 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10684796
• 关键词: Acceleration; Address; Area; Bioinformatics; Cataloging; Catalogs; Collaborations; Collection; Communication; Communities; Community Health; Community Outreach; Data; Data Collection; Data Science; Databases; Development; Environmental Exposure; Environmental Health; Epidemiology; Evaluation; Evolution; FAIR principles; Feedback; Future; Goals; Guidelines; Health; Human; Infrastructure; Ingestion; Laboratories; Language; Lead; Leadership; Life Cycle Stages; Link; Maps; Metadata; Methodology; Mission; Modeling; Ontology; Outcome; Participant; Process; Published Comment; Research; Research Personnel; Research Support; Resources; Science; Semantics; Services; Terminology; Time; Update; Vocabulary; community engagement; computer based Semantic Analysis; crosslink; data access; data centers; data dictionary; data harmonization; data interoperability; data management; data portal; data repository; data resource; data science resource; data standards; design; experience; flexibility; health data; implementation process; interoperability; medical schools; meetings; metadata standards; 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.

数据科学资源总结 HHEAR数据科学资源（DSR）将加速环境健康科学的研究， 创建一个经过社区审查的HHEAR本体，用于为HHEAR数据门户提供动力， 促进各种环境健康数据之间的联系。DSR提供了本体 专业知识、本体识别和映射标准、社区外展和参与，以及整体 语义指导，以支持HHEAR数据中心的数据门户，提供可查找、可访问 可互操作和可重复使用的暴露和健康数据。DSR侧重于互操作术语 连接到并利用一流的词汇表，包括我们当前CHEMICAL本体的演变 HHEAR本体论，以获得更广泛的范围和新的研究支持。事实上，我们在 建立CHEMICAL本体通知并指导我们的HHEAR计划。我们还致力于积极引导和 继续建立一个致力于最佳实践数据和元数据的麻烦和健康社区 词汇表和标准，并在适当时进行重用和链接。该资源有助于语义领导， 流程、工具、语义设计和基础架构演进咨询，以支持查找、优先排序 分析差距/覆盖范围，并有效地使用适当的词汇和用例。由专家指导， 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 目的是创建开源、社区驱动的数据和元数据注释集 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 暴露科学的语言。此外，正在设计的方法的目标是超越这一点 计划，为未来的参与者和社区提供指导。本体和过程有助于 HHEAR计划的目标是加快与疾病相关的研究、分析和 协作，最显著的是明确使用术语和更新流程。 DSR的具体目标是为程序范围的HHEAR本体沿着评估标准 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 现有的基础设施和专业知识将克服充满挑战的漫长实施过程的需要 挑战--我们在实施《儿童权利公约》的过程中已经遇到并克服了许多这样的挑战 DC，并将能够灵活地响应HHEAR网络的需求。