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

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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.