Today's post includes two white papers from two different grant programs. Both projects involve strong international partnerships. The first is from our Start-Up Grant program (next deadline: October 5, 2010), and the second highlights results from a project coming from the DFG/NEH Symposia/Workshop program (next deadline: November 16, 2010). Note that the second white paper includes six smaller white papers contributed by workshop participants. Below are summaries of the projects. Click on the title to access the download page if you'd like to read the full white paper.
Digital Documentation and Reconstruction of an Ancient Maya Temple and Prototype Design of Internet GIS Database of Maya Architecture
University of New Mexico
Project Director: Jennifer von Schwerin
Abstract: This is a request to support two planning workshops for an international large-scale project to develop a publicly accessible, online database of Maya architecture for the UNESCO World Heritage Site of Copan, Honduras that curates highly-accurate, 3D models in a virtual environment that is linked to a searchable GIS database of digital records. Art history, anthropology, and museum personnel from the University of New Mexico and the Honduran Institute of Anthropology and History will work with computer technology experts from the ETH Zurich and others to create a tool that makes full-use of the potential for 3D models in research and teaching on ancient architecture.
University of Virginia
Project Director: Erin Mayhood
Abstract: The U.Va. Library requests funding from NEH to collaborate with the University of Paderborn in Detmold, Germany, in conducting two workshops, one to be held in summer 2009 and one in spring 2010, which will promote an international collaboration to create a music notation data model and prototype delivery system. We intend to engage a select group of international scholars and technologists with a broad range of expertise in discussing the features and functions required in a scholarly XML music notation model, critically evaluate the existing data models, discuss optimum solutions for achieving the desired features, and plan for future implementation of the solutions.