DigiMorph.ORG, A VOXEL-BASED DIGITAL LIBRARY OF MORPHOLOGY

The Digital Library of Morphology (DigiMorph.org) resides in the High-Resolution X-ray CT facility (UTCT) at The University of Texas at Austin. On-line since 2002 with initial funding by the NSF Digital Libraries Initiative, DigiMorph serves visualizations derived from high-resolution X-ray computed tomographic (HRXCT) scans for more than 800 specimens representing nearly 600 Recent and fossil taxa. These specimens range in age from Holocene to Silurian, originate from 93 different countries, and reside in 91 separate collections. Accessioned specimens – 30 of which are types – include Archaeopteryx, the oldest-known dinosaurs Eoraptor and Herrerasaurus, the ‘living fossil’ coelacanth, and the recently rediscovered ivory-billed woodpecker, as well as pterosaurs, specimens preserved in amber, and basal mammals. Data associated with specimen entries include species and specimen information, scanning parameters, and relevant literature and links. Visualizations comprise more than 7000 web-sized (<5 Mb) QuickTime slice-by-slice, spin and cutaway animations, STL files, and Java-based interactive slice viewer applets. DigiMorph has worked in close association with several other NSF projects (e.g., Assembling the Tree of Life projects for amphibians and squamates, The Digital Atlas of Catfish Morphology) to make available the imagery acquired in the course of their investigations. DigiMorph also serves supplemental CT imagery for nearly 70 peer-reviewed publications. To date, the library’s content represents the contributions of 160 researchers residing in 83 academic institutions in 15 countries, and more than two million unique visitors have viewed the site and downloaded almost 3 Tb of data. Future directions for DigiMorph include increasing the representation of non-vertebrate taxa, increasing the variety of voxel-based datasets accessioned (to include MRI, confocal microscopy, synchrotron), adapting content for hand-held devices, and adding an FTP site to automate downloads of full-resolution HRXCT data.