As mentioned above, the Human Jigsaw greatly enhanced the Fellow’s research profile and career potential. This is evident in a) her invited participation in the Conference in Translational Forensics, b) the increased number of invitations she has received to review papers by leading journals, c) her invitation to assume an advisory role on digitization and geometric morphometrics in a project exploring the evolution of the Ovis skeleton, led by Dr. K. Papagianni, and d) her collaboration with a PhD Student from the University of La Laguna in Tenerife to study calcaneus morphology using geometric morphometrics. Very importantly, the fellow has managed to secure a highly competitive grant to continue her research in forensic anthropology for three more years (see information above). Furthermore, the fellow had the opportunity to expand her teaching/mentoring experience by contributing to the module ‘Palaeoanthropology’ taught to undergraduate students at the Democritus University of Thrace, and supervising the dissertation of one undergraduate student from the National University at Athens.
The Human Jigsaw scientific results are expected to have important implications in bioarchaeology and forensic anthropology since multiple/mass disturbed burials are very common in both disciplines and pose distinct interpretational challenges. In bioarchaeological contexts, the Human Jigsaw methodology will allow the identification of the number of individuals, which often employs robust elements such as parts of the femur, but also estimation of the age and sex of these individuals, which is principally based on the os coxae. Hence, this novel methodology will allow much more accurate palaeodemographic reconstructions and a better understanding of mortuary rituals and how they may have been differentiated across different age and sex groups. In forensic anthropological contexts, the Human Jigsaw methodology will facilitate the identification of the unknown subjects by allowing a very important initial sorting of the remains before destructive analyses, such as ancient DNA, are applied. In addition, the methodology developed by the Human Jigsaw is anticipated to pave the way for similar studies in zooarchaeology, where almost all assemblages are commingled and fragmentary, and the epiphyses are often the only well-preserved part of the bones. By adapting the machine learning algorithms to be used in ovicaprids, swine and cows, key archaeological information pertaining to animal management and consumption practices may be obtained. Finally, a highly accurate surface analysis method for matching adjoining bone surfaces can be of great value to prosthetic implants manufacturers. In order to facilitate further research applications, all algorithms produced by this project will be made openly available at GitHub, as already done with the CSG Toolkit and the pairing algorithms.
