JSTOR Integrations

JSTOR Seeklight is a cutting-edge, AI-powered tool designed for the streamlined processing of collections, created under the umbrella of JSTOR Digital Stewardship Services. This innovative resource aids archivists and librarians in expediting the management of digital collections while upholding critical professional standards and preserving archival integrity. Seeklight employs sophisticated algorithms to automatically generate descriptive metadata that conforms to a Dublin Core-compatible schema and produces transcripts for various document types, whether typed, handwritten, or a combination of both. Furthermore, it organizes related files into unified archival items when appropriate, all facilitated through an intuitive cloud-based interface. Each piece of AI-generated metadata is paired with confidence scores, enabling users to assess, adjust, or discard the recommendations, and items are tagged with classifications like "AI-Generated," "Reviewed," or "Edited" to ensure transparency and human oversight. In addition, Seeklight provides project-level summaries that follow the conventional structure of finding aids, thereby enhancing the searchability and accessibility of collections and simplifying the research experience for users. This all-encompassing approach not only boosts efficiency but also strengthens the caliber of archival practices in our increasingly digital world, thereby supporting the evolving needs of the research community.