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Qualitative Data Repository

Qualitative Data Repository
定性数据存储库
批准号:
1061292
负责人:
Colin Elman
金额:
$59.98万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-08-01 至 2015-07-31

项目摘要

项目成果

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中文摘要
翻译
该项目建立了一个专门的存储库,用于存储和共享通过社会科学的定性和多方法研究产生或收集的数据。该资源库将促进社会科学家更大程度的数据共享,在制定和宣传对管理、共享和重用定性数据至关重要的标准和实践方面发挥主导作用,并为世界各地的学者提供大量的教学和研究利益。社会科学家广泛使用定性数据来推进一系列分析目标,包括解释、描述性概括和因果推论。不幸的是,定性数据通常只被使用一次:它们被收集用于特定的研究目的,然后被丢弃。定性研究人员之间缺乏数据共享的传统,部分原因是由于基础设施的差距——缺乏存储和共享定性数据的合适场所。为定性和多方法研究产生的数据提供一个专门的储存库将填补这一空白,并将促进定性政治科学家存档做法的标准化。定性数据存储库有四个主要目的。首先,存储库将以数字形式存储数据,为访问提供适当的搜索工具和索引。这些数字化数据将包括采访记录和笔记、焦点小组、口述历史、参与者观察和人种学研究、档案文件扫描、报纸文章和报告,以及定性数据分析软件的输出。其次,该存储库将成为其自身馆藏之外的材料的门户,允许用户从不同的数据库和档案中识别相关数据。它将与美国和其他存放定性数据的国家的档案馆建立联系,寻求从资料库“点击”访问的协议。第三,储存库将通过为定性和多方法研究人员提供必要的场所和工具来鼓励他们共享数据。最后,资源库将有助于促进发布定性研究数据的通用标准和实践,以及引用其他学者产生的数据和数据集,以及为发表数据集的学者授予应有的荣誉。促进和规范从定性和多方法研究中产生的数据的存储和共享将为社会科学和更广泛的学术界带来几个重要的好处。通过鼓励数据共享并提供这样做的场所,该知识库将极大地扩大美国和国外学者(包括那些缺乏原始数据收集资源的学者)对丰富的社会科学数据的访问。反过来,这将使否则无法进行的重要研究成为可能。该资源库将显著降低评估基于经验的定性分析的成本,并增加定性研究过程的透明度,从而增强对定性研究结果的信心。通过提高研究人员的可见度,知识库将促进知识交流,促进知识社区的形成,并作为研究网络和伙伴关系的平台。总体而言,该资源库将帮助美国国家科学基金会实现其促进社会科学中更系统的定性研究的目标,从而促进发现和加强科学理解。这个项目的社会效益与其对教育的影响息息相关。该数据库将通过共享数据提供的教学机会,有效地将研究和教育结合起来。该项目还通过存储库提供的培训来加强教育。
英文摘要
This project establishes a dedicated repository for storing and sharing data generated or collected through qualitative and multi-method research in the social sciences. The repository will promote greater data sharing by social scientists, play a leading role in developing and publicizing the standards and practices which are crucial for managing, sharing, and reusing qualitative data, and provide substantial pedagogical and research benefits to scholars around the world. Qualitative data are widely used by social scientists to advance a range of analytical goals, including interpretations, descriptive generalizations, and causal inferences. Unfortunately, qualitative data are typically used only once: they are collected for a particular research purpose, and then discarded. The absence of a data sharing tradition among qualitative researchers is in part due to an infrastructure gap--the absence of a suitable venue for storing and sharing qualitative data. Providing a dedicated repository for data generated by qualitative and multi-method research will fill this gap and will facilitate the standardization of archiving practices among qualitative political scientists. The Qualitative Data Repository has four main purposes. First, the repository will store data in digital form, providing access with appropriate search tools and indexes. This digitized data will include transcripts and notes from interviews, focus groups, oral histories, participant observations, and ethnographic studies, scans of archival documents, newspaper articles, and reports, and outputs from qualitative data analysis software. Second, the repository will be a portal to material beyond its own holdings, allowing users to identify relevant data from diverse databases and archives. It will establish linkages with archives in the U.S. and other countries that house qualitative data, seeking agreements for "click through" access from the repository. Third, the repository will encourage the sharing of data by qualitative and multi-method researchers by providing them a venue and the tools necessary to do so. Finally, the repository will help to promote common standards and practices for publishing qualitative research data, and for citing data and data sets produced by another scholar--as well as for granting due credit to scholars for the publication of data sets.Facilitating and regularizing the storing and sharing of data arising from qualitative and multi-method research will deliver several important benefits for the social sciences and broader academic community. By encouraging data sharing and providing a venue to do so, the repository will greatly expand the access of scholars in the United States and abroad--including those who lack the resources to engage in original data collection--to a wealth of social science data. In turn, this will make possible important research that otherwise would not be conducted. The repository will dramatically reduce the costs of assessing empirically based qualitative analysis and increase the transparency of the qualitative research process, thus bolstering confidence in the findings of qualitative studies. By increasing researcher visibility, the repository will induce intellectual exchange, promoting the formation of epistemic communities, and serving as a platform for research networks and partnerships. Overall, the repository will be poised to help NSF realize its goal of promoting more systematic qualitative research in the social sciences, thereby advancing discovery and enhancing scientific understanding.The societal benefits of this project are tied to its impact on education. The repository will effectively integrate research and education through the instructional opportunities offered by sharing data offers. The project also enhances education through the training the repository will provide.
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会议论文
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:
Qualitative Data Repository 2021-2024
  • 批准号:
    2116935
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $129.97万
  • 财政年份:
    2021
  • 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:
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: