EduceOps: EduceLab Operations for Next-Generation Heritage Science Infrastructure

This award supports the operations of EduceLab, a University of Kentucky facility that helps researchers study and preserve important objects, collections, places, and records from the human past. Heritage science uses imaging, computing, artificial intelligence (AI) and other methods of scientific measurement and analysis, to learn from ancient items while limiting damage to rare or fragile materials, and discovering historically relevant sites. EduceLab has already enabled the identification of previously unknown grave sites, such as those from the US Civil War. It also made it possible to read ancient scrolls that were sealed in volcano ash near Pompeii, enabling first the virtual unrolling of the material and reading of the letter through novel AI methods. Museums, libraries, universities, public agencies, and community organizations often have materials that are too fragile, too rare, too large, or too complex to study with ordinary tools and lack access to advanced instruments, computing resources, and expert guidance. EduceLab will provide a shared place where scientists, scholars, students, and heritage professionals can collaborate to answer questions about artifacts, manuscripts, biological remains, museum collections, buildings, and historic landscapes. The project will advance the national interest by generating access to high quality research infrastructure, strengthening the ability of a range of institutions to study important collections, preserving historical knowledge, training students and researchers in AI and a range of techniques, and creating public materials that help people understand why science matters for preserving our heritage. By making advanced tools and expertise available through a national user facility in Kentucky, the award will promote the progress of science and contribute to education, public understanding, and knowledge of heritage resources. EduceLab will support laboratory-based imaging and materials analysis, mobile and field-based data collection, flexible instrument configurations, and cyberinfrastructure for data movement, computation, artificial-intelligence-assisted analysis, storage, and dissemination. Users will enter the facility through an intake and onboarding process that includes eligibility review, consultation, training, safety and compliance review, and joint project design with expert staff. Projects may combine techniques such as micro computed tomography, X ray fluorescence, electron microscopy, spectral and optical imaging, ground penetrating radar, three dimensional modeling, data science, machine learning, and repository services. The facility will maintain calibration, scheduling, preventive maintenance, data quality control, project reporting, and performance metrics to support reliable access and reproducible results. Expected products include imaging and materials data, computational reconstructions, curated data packages, analytical reports, publications, public case studies, educational materials, and training programs. The project will also develop a cost recovery and partnership model to support long term operation. Together, these activities will create transferable methods for data intensive heritage science and a sustainable model for shared research infrastructure. 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.