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What is JSTOR Seeklight?

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.

What is ArchivEra?

ArchivEra is an excellent choice for managing archival collections, suitable for institutions of all sizes and budgets. With two decades of expertise in assisting archival clients, the platform integrates best practices in collections management tailored to help archivists tackle current issues while also preparing for future demands. Unlike traditional collections management systems, this fully web-based platform allows archives to easily offer public access to their collections, significantly improving the user experience through detailed documentation for each item, artifact, or collection, as well as supplementary multimedia content. Additionally, ArchivEra features specialized workflows that require minimal training and adhere to archival standards like EAD3, thus simplifying processes for users. Its advanced technology and extensive features, such as customized workflows designed specifically for archivists and streamlined finding aid creation, enable institutions to overcome the constraints posed by conventional collections management. This forward-thinking strategy not only boosts operational efficiency but also enriches the archival experience for both professionals and the public, fostering greater engagement and accessibility. Ultimately, ArchivEra stands out as a transformative solution that meets the evolving needs of the archival community.

Media

Media

Integrations Supported

JSTOR

Integrations Supported

Facebook
Microsoft 365
Pinterest
X (Twitter)

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

JSTOR

Date Founded

1995

Company Location

United States

Company Website

info.jstor.org/human-centered-ai-for-stewardship/

Company Facts

Organization Name

Lucidea

Date Founded

2013

Company Location

United States

Company Website

lucidea.com/archivera-archives-collections-management-software/

Categories and Features

Library Management

Not specified

Categories and Features

Archiving

Not specified

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