Center for Expanded Data Annotation and Retrieval (CEDAR) - Overall

扩展数据注释和检索中心 (CEDAR) - 总体

• 批准号: 8774419
• 负责人: Mark A Musen
• 金额: $ 185.47万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-29 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8774419
• 关键词: Algorithms; Archives; Big Data; Biological Assay; Cataloging; Catalogs; Collection; Communities; Computers; Computing Methodologies; Data; Data Analyses; Data Quality; Data Set; Databases; Development; Ecosystem; Education; Evaluation; Faculty; Future; Growth; Health; Human; Immunology; Instruction; Laboratory Study; Lead; Learning; Light; Literature; Measurable; Metadata; Methods; Mission; National Institute of Allergy and Infectious Disease; Online Systems; Ontology; Paper; Participant; Postdoctoral Fellow; Process; Publications; Research; Research Personnel; Resources; Retrieval; Science; Scientist; Semantics; Site; Structure; Technology; Testing; Training; Universities; Work; base; biomedical scientist; data acquisition; digital; graduate student; innovation; member; public health relevance; repository; research study; tool

DESCRIPTION (provided by applicant): The Big Data revolution requires that biomedical scientists be able to locate, analyze, and integrate the large datasets that now pervade biomedicine. Such work is possible only when experimental datasets are made available online and when they are annotated with metadata that explain how the data are organized, what the data represent, and how the data were collected. The Center for Expanded Data Annotation and Retrieval (CEDAR) will take advantage of the recent growth in community-driven metadata standards to develop innovative computational methods to ease the authoring and use of metadata annotations. Our specific aims focus on working with communities of investigators to standardize descriptions of the data generated through biomedical studies; creating a computational collective for development, evaluation, use, and refinement of metadata templates for describing laboratory studies; developing a comprehensive and open repository of metadata that will inform the learning algorithms that will drive much of our Center's technology; training the biomedical community in the use of metadata and in CEDAR's resources; and evaluating our work in the context of ImmPort, an NIAID-supported multi-assay data repository that will offer end-to-end opportunities to demonstrate and validate our ideas. We anticipate a growing community of users, starting with the Human Immunology Project Consortium, then the BD2K Center Consortium, then the Stanford Digital Repository, growing until we have developed a wide user base leading to measurable changes in the quality of the metadata used to annotate online datasets. The Overall description of our project provides a synopsis of CEDAR's activities and overall specific aims.

描述（由申请人提供）：大数据革命要求生物医学科学家能够定位，分析和整合现在遍布生物医学的大型数据集。只有当实验数据集可以在线获得，并且用元数据解释数据如何组织，数据代表什么以及如何收集数据时，这种工作才有可能。扩展数据注释和检索中心（CEDAR）将利用社区驱动的元数据标准的最新发展，开发创新的计算方法，以简化元数据注释的编写和使用。我们的具体目标侧重于与研究者社区合作，以标准化通过生物医学研究产生的数据的描述;创建一个计算集体，用于开发，评估，使用和改进用于描述实验室研究的元数据模板;开发一个全面和开放的元数据库，该元数据库将为学习算法提供信息，这将推动我们中心的大部分技术;培训生物医学界使用元数据和CEDAR的资源;并在ImmPort的背景下评估我们的工作，ImmPort是NIAID支持的多检测数据库，将提供端到端的机会来展示和验证我们的想法。我们预计用户社区将不断增长，从人类免疫学项目联盟开始，然后是BD 2K中心联盟，然后是斯坦福大学数字知识库，直到我们开发出广泛的用户群，从而导致用于注释在线数据集的元数据质量发生可衡量的变化。 我们项目的总体描述提供了CEDAR活动和总体具体目标的概要。