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Department of Archaeology

 
Read more at: Marianna Emilia Sofia Negro

Marianna Emilia Sofia Negro

Fri, 10/29/2021 - 11:53


Read more at: Lucia Martina Scalise

Lucia Martina Scalise

Fri, 10/29/2021 - 11:30


Read more at: Isavella Voulgareli

Isavella Voulgareli

Fri, 10/29/2021 - 10:47


Read more at: Andriana-Maria Xenaki

Andriana-Maria Xenaki

Fri, 10/22/2021 - 14:22


Read more at: Predicting the Past with Supervised Learning: Applications and Challenges in Archaeology

Predicting the Past with Supervised Learning: Applications and Challenges in Archaeology

Mon, 10/11/2021 - 14:06

Until the recent proliferation of the supervised machine learning approach in archaeology, quantitative analyses were made using unsupervised learning tools that are restricted to analyze and cluster unlabeled datasets. Conversely, supervised tools are applied in labelled data which, using specific algorithms to train this data, enable to classify and predict potential outcomes accurately. With supervised methods, the researcher plays an active role in the entire process by labelling input and output data and supervising the training procedure.


Read more at: TSAR: Topological Study of Archaeological Refitting. Evaluating the reliability of archaeological spatial units with the “archeofrag” R package

TSAR: Topological Study of Archaeological Refitting. Evaluating the reliability of archaeological spatial units with the “archeofrag” R package

Mon, 10/11/2021 - 13:15

Theoretical issues raised by the dialectical relationship between the quality of archaeological data and the quality of their modelling will be addressed from a methodological standpoint. I argue that 1) archaeological science needs to ensure the highest standards regarding each of these two aspects, and 2) that the theoretical problems must be addressed with regards to their consequences for operational methods.


Read more at: Petrus (Piet) J. Gerrits

Petrus (Piet) J. Gerrits

Fri, 09/17/2021 - 09:27


Read more at: ArchBiMod – Agent-Based Modelling to assess the quality and bias of the archaeological record

ArchBiMod – Agent-Based Modelling to assess the quality and bias of the archaeological record

Archaeological data is often biased and incomplete. This is a well-known issue for most archaeologists. Although studies of specific sites and small regions can have this into account, the effect of this problem increases exponentially as archaeologists expand their chronological and geographic frame, and try to answer questions related to general dynamics and broad human processes.


Read more at: Training the next generation of archaeological scientists: Interdisciplinary studies of pre-modern Plasters and Ceramics from the eastern Mediterranean (PlaCe)

Training the next generation of archaeological scientists: Interdisciplinary studies of pre-modern Plasters and Ceramics from the eastern Mediterranean (PlaCe)

The PlaCe network is a high-profile partnership focused on the interdisciplinary study of pre-modern ceramics and plasters. This Innovative Training Network aims at training Early-Stage Researchers to conduct state-of-the-art, science-based research on the technology, use, and provenance of ceramics and plaster, integrating archaeological materials science with biomolecular archaeology. The geographic focus is the Eastern Mediterranean, but we are hoping to push methodological developments of significance in other regions.


Read more at: The Cambridge Heritage Science Hub Initiative (CHERISH)

The Cambridge Heritage Science Hub Initiative (CHERISH)

Cambridge is home to world-leading researchers across archaeological science, technical art history and heritage science, based at Department of Archaeology, the Fitzwilliam Museum, and the Hamilton Kerr Institute, among others. There are multiple synergies across these institutions in terms of research methodologies, goals and ambitions in the field of technical and scientific investigation of works of art and archaeological objects.