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EAGER: Crowdsourcing Metadata Enhancements to Improve the Discoverability and Reusability of Scientific Data: Experimental Evaluations

EAGER：众包元数据增强功能以提高科学数据的可发现性和可重用性：实验评估

基本信息

批准号：
1838994
负责人：
Margaret Levenstein
金额：
$ 29.82万
依托单位：
Regents of the University of Michigan - Ann Arbor
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-10-01 至 2022-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1838994&HistoricalAwards=false
关键词：
EAGER Crowdsourcing Metadata Enhancements Improve

项目摘要

This exploratory pilot project will undertake two experiments to determine what motivates people to contribute metadata enhancements to data that have been archived, but that are not sufficiently findable, accessible, interoperable, and reusable. Current practice in data curation relies on the efforts of data producers and professional data curators to produce and provide metadata, including variable level data descriptors, study key words, and bibliographic citations to data-related publications. These efforts are expensive and, as a result, are often undersupplied, leaving data that has been archived and shared with the scientific community of limited value for reuse. The experiments in this project will directly inform potentially transformative efforts to engage the broader community in crowdsourcing enhancements to metadata so that tools and interfaces can be designed that will induce others to participate in this valuable activity, tapping into their knowledge of and interest in data in particular domains to increase data FAIRness. This project is supported by the National Science Foundation Public Access Initiative which is managed by the NSF Office of Advanced Cyberinfrastructure on behalf of the Foundation.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.

这个探索性的试点项目将进行两个实验，以确定是什么激励人们为已存档的数据贡献元数据增强功能，但这些数据不足以找到，访问，互操作和可重用。目前的数据管理实践依赖于数据生产者和专业数据管理者的努力，以生产和提供元数据，包括可变水平的数据描述符，研究关键词，以及与数据相关的出版物的书目引用。这些工作费用昂贵，因此往往供应不足，使已存档并与科学界共享的数据的再利用价值有限。该项目的实验将直接为潜在的变革性努力提供信息，以使更广泛的社区参与众包增强元数据，从而可以设计工具和界面，吸引其他人参与这一有价值的活动，利用他们对特定领域数据的知识和兴趣，以提高数据的公平性。该项目由美国国家科学基金会公共访问计划支持，该计划由美国国家科学基金会高级网络基础设施办公室代表基金会管理。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。