Digital Archaeology and
Crowdsourcing Research

Worldwide

Cyberarchaeology—the marriage of computer science, engineering, and archaeology—is the future of the past. For UC San Diego archaeologist Thomas E. Levy and research scientist Albert Yu-Min Lin, the tools of the trade include crowdsourcing, multispectral imaging, and data-sharing workflows. At the Qualcomm Institute’s Center of Interdisciplinary Science for Art, Architecture and Archaeology (CISA3), they are exploring methodologies for art conservation and cultural heritage research, while training a new generation of interdisciplinary experts to work in the emerging cyberarchaeology field.

In academic year 2012–13, Levy took his research style on the road, generating worldwide interest in digital cyberarchaeology. His whirlwind research season included a trip to Petra in Jordan, where he and his team deployed a helium balloon platform to create high-definition imagery of the ancient Temple of Winged Lions. The American Center of Oriental Research (ACOR) recruited Levy for the conservation project, or what he refers to as “rescue archaeology.” The massive data the team collected in a short amount of time will be available through ACOR at no charge to researchers from multiple nations.

Qualcomm Institute research scientist Albert Yu-Min Lin; Archaeology professor Tom Levy, middle, with graduate students and a Total station used to survey an area of southern Jordan prior to excavation

Lin is a three-time alumnus of UC San Diego’s Jacob School of Engineering in electrical engineering (BS ’04, MS ’05) and materials science (PhD ’08). He used crowdsourcing that involved local people in an effort to solve an eight hundred-year-old mystery—the whereabouts of Genghis Khan’s lost tomb. By logging onto a customized Internet portal, users could join Lin’s expedition in real time. The National Geographic-supported project, launched in 2010, emphasized searching for cultural-heritage sites while maintaining respect for local customs and beliefs.

In 2013, Lin, the National Aeronautics and Space Administration (NASA), and TopCoder, the world’s largest platform for digital open innovation, a competitive community of digital creators, challenged programmers worldwide to develop a machine-learning algorithm that would match human perception when picking out interesting features in satellite imagery used in Lin's search for the lost burial site. Once developed, the algorithm could integrate machines and crowds to accelerate discovery in a wide array of big data problems, ranging from planetary to medical imaging exploration.