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Qualitative Data Repository 2021-2024

Qualitative Data Repository 2021-2024
定性数据存储库 2021-2024
批准号:
2116935
负责人:
Colin Elman
金额:
$129.97万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-08-15 至 2024-07-31

项目摘要

项目成果

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中文摘要
翻译
该奖项资助定性数据存储库(QDR),这是一个开放的存储库,致力于通过定性和多方法研究生成的数据的管理、保存和出版。QDR是一个由社会科学家和信息科学家领导的合作项目,活跃于社会、行为、卫生和教育科学的许多学科。通过鼓励和授权研究人员分享他们的定性数据,该数据库促进了科学的进步;建立基础设施,支持定性研究的开放性;鼓励制度变革以提高研究透明度,并允许在道德和法律上共享定性数据(即,在不伤害人类参与者或侵犯专利限制的情况下)。数据共享和重用是科学不可缺少的组成部分,有助于使其更加严谨、累积和高效,同时降低成本。定性数据存储库(QDR)是一个由社会科学家和信息科学家领导的合作项目,活跃于社会、行为、健康和教育科学的许多学科。QDR被CoreTrustSeal认证为“可信数据存储库”,是支持美国开放科学的基础设施的关键部分。通过QDR共享的数据可用于多个目标:根据数据验证出版物中的结果和声明;进行二次分析以回答新问题,从而促进知识的发现和生产;通过主动学习来改进教学方法。该奖项使QDR能够为研究人员和数据图书馆员组织关于定性数据管理的定制讲习班和培训课程。通过进一步将QDR整合到学术生态系统中,并促进与机构审查委员会和社会科学出版基础设施的互动,该知识库将继续开发新的方法,使学者能够随时获取支撑其科学出版物的数据和材料。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This award funds the Qualitative Data Repository (QDR), an open repository dedicated to the curation, preservation, and publication of data generated through qualitative and multi-method research. QDR, a collaborative project led by social scientists and information scientists, is active in many disciplines in the social, behavioral, health, and education sciences. The repository promotes the progress of science by encouraging and empowering researchers to share their qualitative data; building infrastructure to support the openness of qualitative research; and encouraging institutional change to advance research transparency and allow qualitative data to be shared ethically and legally (i.e., without harming human participants or infringing proprietary constraints). Data sharing and reuse are indispensable components of science that help to make it more rigorous, cumulative, and efficient, as well as less expensive. The Qualitative Data Repository (QDR), a collaborative project led by social scientists and information scientists, is active in many disciplines in the social, behavioral, health, and education sciences. Certified as a “trusted data repository” by CoreTrustSeal, QDR is a key part of the infrastructure supporting open science in the US. Data shared via QDR can be used for multiple goals: to verify results and claims in publications based on the data; for secondary analysis to answer new questions, thus facilitating discovery and the production of knowledge; and to improve pedagogy through empowering active learning. This award enables QDR to organize customized workshops and training sessions for researchers and data librarians on qualitative data-management. By further integrating QDR into the academic ecosystem and facilitating interaction with Institutional Review Boards and the social science publication infrastructure, the repository continues to develop new ways for scholars to provide ready access to the data and materials that underpin their scientific publications.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(1)
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会议论文
Curating for Accessibility
策划无障碍
DOI: 10.2218/ijdc.v17i1.837
发表时间: 2022
期刊: International Journal of Digital Curation
影响因子: --
作者: [Anderson, Theresa, Colón, Randy D., Goben, Abigail, Karcher, Sebastian]
通讯作者: Karcher, Sebastian
Support for Institutes and Research Groups on Qualitative and Multi-Method Research: 2024-2026
  • 批准号:
    2343087
  • 项目类别:
    Standard Grant
  • 资助金额:
    $35.0万
  • 财政年份:
    2024
  • 负责人:
    Colin Elman
  • 依托单位:
EAGER: Mapping Open Science through the Journal Editors Discussion Interface
  • 批准号:
    2332061
  • 项目类别:
    Standard Grant
  • 资助金额:
    $27.5万
  • 财政年份:
    2023
  • 负责人:
    Colin Elman
  • 依托单位:
Support for Institutes and Research Groups on Qualitative and Multi-Method Research: 2021-2023
  • 批准号:
    1948724
  • 项目类别:
    Standard Grant
  • 资助金额:
    $23.69万
  • 财政年份:
    2020
  • 负责人:
    Colin Elman
  • 依托单位:
EAGER: Sharing Knowledge, Building Community: Introducing a Journal Editors' Discussion Interface (JEDI)
  • 批准号:
    2032661
  • 项目类别:
    Standard Grant
  • 资助金额:
    $29.97万
  • 财政年份:
    2020
  • 负责人:
    Colin Elman
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位:
基于Linked Open Data的Web服务语义互操作关键技术
  • 批准号:
    61373035
  • 项目类别:
    面上项目
  • 资助金额:
    77.0万元
  • 批准年份:
    2013
  • 负责人:
    冯志勇
  • 依托单位: