BioCADDIE: Biomedical and healthCAre Data Discovery and Indexing Engine center

BioCADDIE:生物医学和 healthCare 数据发现和索引引擎中心

基本信息

项目摘要

DESCRIPTION (provided by applicant): Biomedical and healthcare data sharing efforts are currently impaired by lack of (1) proper incentives and sharing tools for data producers, (2) practical frameworks for data standardization and indexing of data, and (3) effective data discovery mechanisms. BioCADDIE is a consortium of data producers, curators, publishers, and consumers who will work together to develop practical, sustainable solutions to the problem of biomedical and healthcare data discovery. Through task forces and corresponding pilot projects addressing the barriers enumerated above, we will promote open discussion of why millions of dollars are currently spent in the generation of data that remain captive at their origin or are shared in a sub-optimal way just to comply with mandates from funding agencies and scientific journals. We will promote the development of incentives, policies, and tools for data sharing and data discovery. We will engage researchers, clinicians, patients, and the community in general in an open dialogue focused on pros and cons of biomedical and clinical data sharing. BioCADDIE's specific aims are to: (1) Organize task forces with representatives from communities who have interest in data production, dissemination, and utilization. We will organize an annual symposium, workshops, Internet-based discussions among biomedical and clinical researchers, professional societies, journal publishers, funding agencies, clinicians, patients, and information scientists on best, sustainable practices for making data easily discoverable by different types of users. (2) Promote the development of realistic, minimal, friendly meta-data specifications and annotations for biomedical and healthcare data collections, and corresponding tools for automated indexing so that users will be able to locate data that are relevant to their specific free text searches. (3) Incubate new technologies by funding highly innovative, high-risk pilot research projects that enable the development of novel data discovery and indexing engines and have them tested by our diverse community of stakeholders. We only describe a small number of seed pilot projects in this proposal because BioCADDIE will solicit proposals for new pilot projects every year and select them through a review process involving the various stakeholder communities.
描述(由申请人提供):目前缺乏(1)数据生产者的适当激励措施和共享工具,(2)数据标准化和数据索引的实用框架,以及(3)有效的数据发现机制。 BiocAddie是一个数据生产者,策展人,出版商和消费者的财团,他们将共同努力,为生物医学和医疗保健数据发现问题开发实用,可持续的解决方案。通过工作队和相应的飞行员项目,解决了上述列出的障碍,我们将宣传为什么目前将数百万美元用于生成数据的生成,这些数据仍被俘虏,或以次优的方式共享,以遵守资助机构和科学期刊的授权。我们将促进用于数据共享和数据发现的激励措施,政策和工具的开发。我们将与研究人员,临床医生,患者和社区与一般的公开对话进行,重点介绍了生物医学和临床数据共享的利弊。 BiocAddie的具体目的是:(1)与对数据生产,传播和利用感兴趣的代表组织工作队。我们将在生物医学和临床研究人员,专业社会,期刊出版商,资助机构,临床医生,患者和信息科学家有关最佳,可持续性实践方面,以使不同类型的用户可轻松发现数据的最佳可持续性实践中,在生物医学和临床研究人员,专业社会,期刊出版商,资助机构,临床医生,患者和信息科学家中组织年度研讨会,基于互联网的讨论。 (2)促进针对生物医学和医疗保健数据收集的现实,最小,友好的元数据规格和注释,以及用于自动索引的相应工具,以便用户能够找到与其特定免费文本搜索相关的数据。 (3)通过资助具有高度创新的高风险试点研究项目来孵化新技术,从而使新的数据发现和索引引擎能够开发,并由我们多样化的利益相关者社区对其进行测试。我们仅在此提案中描述了少量的种子试点项目,因为BiocAddie每年都会为新的试点项目征求建议,并通过涉及各种利益相关者社区的审查过程选择它们。

项目成果

期刊论文数量(14)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
DataMed - an open source discovery index for finding biomedical datasets.
  • DOI:
    10.1093/jamia/ocx121
  • 发表时间:
    2018-03-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chen X;Gururaj AE;Ozyurt B;Liu R;Soysal E;Cohen T;Tiryaki F;Li Y;Zong N;Jiang M;Rogith D;Salimi M;Kim HE;Rocca-Serra P;Gonzalez-Beltran A;Farcas C;Johnson T;Margolis R;Alter G;Sansone SA;Fore IM;Ohno-Machado L;Grethe JS;Xu H
  • 通讯作者:
    Xu H
Elsevier's approach to the bioCADDIE 2016 Dataset Retrieval Challenge.
A publicly available benchmark for biomedical dataset retrieval: the reference standard for the 2016 bioCADDIE dataset retrieval challenge.
Supporting inter-topic entity search for biomedical Linked Data based on heterogeneous relationships.
  • DOI:
    10.1016/j.compbiomed.2017.05.026
  • 发表时间:
    2017-08-01
  • 期刊:
  • 影响因子:
    7.7
  • 作者:
    Zong N;Lee S;Ahn J;Kim HG
  • 通讯作者:
    Kim HG
Feasibility of Representing Data from Published Nursing Research Using the OMOP Common Data Model.
使用 OMOP 通用数据模型表示已发表的护理研究数据的可行性。
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LUCILA OHNO-MACHADO其他文献

LUCILA OHNO-MACHADO的其他文献

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{{ truncateString('LUCILA OHNO-MACHADO', 18)}}的其他基金

Admin Core (FABRIC)
管理核心 (FABRIC)
  • 批准号:
    10662369
  • 财政年份:
    2023
  • 资助金额:
    $ 81.07万
  • 项目类别:
A FAIR Bridge2AI Center (FABRIC)
公平的 Bridge2AI 中心 (FABRIC)
  • 批准号:
    10745613
  • 财政年份:
    2023
  • 资助金额:
    $ 81.07万
  • 项目类别:
A FAIR Bridge2AI Center (FABRIC)
公平的 Bridge2AI 中心 (FABRIC)
  • 批准号:
    10662351
  • 财政年份:
    2023
  • 资助金额:
    $ 81.07万
  • 项目类别:
A FAIR Bridge2AI Center (FABRIC)
公平的 Bridge2AI 中心 (FABRIC)
  • 批准号:
    10895014
  • 财政年份:
    2023
  • 资助金额:
    $ 81.07万
  • 项目类别:
Admin Core (FABRIC)
管理核心 (FABRIC)
  • 批准号:
    10897496
  • 财政年份:
    2023
  • 资助金额:
    $ 81.07万
  • 项目类别:
iAGREE: A Multi- Center, Networked Patient Consent Study
iAGREE:一项多中心、网络化患者同意研究
  • 批准号:
    10748211
  • 财政年份:
    2023
  • 资助金额:
    $ 81.07万
  • 项目类别:
Admin Core (FABRIC)
管理核心 (FABRIC)
  • 批准号:
    10473060
  • 财政年份:
    2022
  • 资助金额:
    $ 81.07万
  • 项目类别:
A FAIR Bridge2AI Center (FABRIC)
公平的 Bridge2AI 中心 (FABRIC)
  • 批准号:
    10473059
  • 财政年份:
    2022
  • 资助金额:
    $ 81.07万
  • 项目类别:
iAGREE: A Multi-Center, Networked Patient Consent Study
iAGREE:一项多中心、网络化的患者同意研究
  • 批准号:
    10356887
  • 财政年份:
    2020
  • 资助金额:
    $ 81.07万
  • 项目类别:
iAGREE: A Multi-Center, Networked Patient Consent Study
iAGREE:一项多中心、网络化的患者同意研究
  • 批准号:
    10594207
  • 财政年份:
    2020
  • 资助金额:
    $ 81.07万
  • 项目类别:

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  • 批准号:
    8819270
  • 财政年份:
    2014
  • 资助金额:
    $ 81.07万
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