EAGER: Computer-Assisted Redaction and Anonymization of Scholarly Communications and Products (CARASCAP)

EAGER：学术交流和产品的计算机辅助编辑和匿名化 (CARASCAP)

• 批准号: 2135446
• 负责人: Christopher Lee
• 金额: $ 29.99万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2023-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2135446&HistoricalAwards=false
• 关键词: EAGER; Computer; Assisted; Redaction; Anonymization

The Computer-Assisted Redaction and Anonymization of Scholarly Communications and Products (CARASCAP) project will produce a proof-of-concept open-source application stack to assist research teams and individual scholars in identifying, documenting, and redacting sensitive and personally identifying information within their research products. The potential presence of personally identifying information (PII) and other sensitive information is a significant inhibitor to public access to datasets and other products of publicly funded research. Without reliable and cost-effective processes for identifying such information, the default response is most often to indefinitely prevent the public from accessing entire collections of research products. By developing new components and tools for iterative redaction functions incorporated into workflows to prepare datasets for public dissemination, this project will foster a stronger ecosystem of research data publishing efforts. The software will be developed primarily in Python, MIT Licensed, and packaged for distribution on the Python Package Index (PyPI). Independent modules will interpret and modify the source material data structures. For this prototype phase, the project will focus on formats likely to be of interest to a broad range of collections, including open text scraped from web pages at specific URLs, text formats, and modern office formats (e.g., PDF,.odt, .docx, .pst, .ost).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.

学术交流和产品的计算机辅助编辑和分析（CARASCAP）项目将产生一个概念验证的开源应用程序堆栈，以帮助研究团队和个人学者识别，记录和编辑其研究产品中的敏感和个人身份信息。 个人身份信息（PII）和其他敏感信息的潜在存在是公众访问数据集和其他公共资助研究产品的重要抑制因素。 如果没有可靠和具有成本效益的程序来确定这些信息，默认的反应往往是无限期地阻止公众访问整个研究产品集。 通过开发新的组件和工具，将迭代编辑功能纳入工作流程，以准备公开传播的数据集，该项目将促进更强大的研究数据发布工作生态系统。 该软件将主要用Python开发，MIT许可，并打包在Python包索引（PyPI）上分发。 独立模块将解释和修改源材料数据结构。在这个原型阶段，该项目将重点关注可能对广泛的集合感兴趣的格式，包括从特定URL的网页上抓取的开放文本，文本格式和现代办公格式（例如，该奖项反映了NSF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。