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This paper explores the link between archaeology and the digital humanities, especially the adoption of 3D modeling technology, which is becoming an integral part of archaeological practice. Here we present a case study, a sample of 3D models from a large collection of well-preserved medieval ceramics from the excavations of the Sanctuary of Zeus at Nemea, Greece. This growing digital collection can illustrate the advantages, potential, and challenges presented by the incorporation of 3D technology into archaeological practice. 3D modeling technology can facilitate documentation, interpretation, and publication of archaeological datasets. However, the longevity of these datasets remains uncertain and require extensive dialogue and collaboration, as storage space requirements, support of current digital infrastructure, and long-term data accessibility and preservation are matters that do not have standardized solutions. More effort needs to be invested in preserving these large datasets before 3D modeling can become fully incorporated into archaeological practice.

For decades, dating of Roman Terra Sigillata pottery was assessed by visual inspection. Since the ornaments and indentations on the ceramic surface are characteristic for the manufacturing workshop in the Roman Empire, archeologists have used chronological catalogues to assign the sherds to its time period. This paper should underpin the application of image-based nondestructive testing (NDT) methods as a powerful instrument for obtaining data, which allows to extract predominant features for later classification. At first, an overview ist given to a variety of non-invasive inspection technique with particular focus on digital photography and infrared (IR) thermography. To receive enhanced spectral information, IR thermography is proposed complementary to visible light photography in an experimental study. Furthermore, different image processing techniques are applied to reveal their potential for enhanced feature extraction. Finally, the paper should give rise for the identification of the manufacturing period and the constructor's fingerprint of Terra Sigillata pottery at a later stage.

Emerging modern technologies including Mixed Reality (MR) are gradually becoming an inherent component of higher education. Studies concerning the effectiveness of their use as a didactic tool have been conducted in several fields of research. While the benefits of spatial representation through MR have already been employed in the fields of cultural heritage and museums, hardly any research is dedicated to higher archaeological education. In this paper, we present the first results of the ongoing development of the MARBLE-App of the research programme »Mixed and Augmented Reality in Blended Learning Environments« on the integration of MR into everyday archaeological higher education. The results are presented on the basis of learners' feedback from a focus group study carried out with archaeology students on understanding the spatial complexity of an archaeological structure. They show an increase in the students' impression, their self-reflected learning gains and their engagement towards spatial-related topics in the field of archaeology.That said, we perceive a high potential yet to be explored for the use of this technology in archaeological spatial education.

An editorial of the second issue of the journal "Research in Film and History" that explores current research, debates, and projects at the intersection between the disciplines of film studies and history. Issue 2

Im Jahr 2021 lädt die Initiative "Forschungsdatenmanagement" alle Mitarbeitenden der BBAW zu einer Veranstaltungsreihe mit dem Titel "Forschungsdatenmanagement kompakt" ein. Die Präsentationsfolien der ersten Online-Veranstaltung am 11.02.2021 führen in die Grundlagen und Grundbegriffe des Forschungsdatenmanagements ein und stellen die Ziele der Initiative vor.

The magnitude of destruction on cultural heritage worldwide creates unprecedented challenges for its rehabilitation since conservation activities must be integrated into the context of larger rehabilitation efforts. It is argued that an authentic remodelling of the Eastern 38 m Buddha establishing the previous spatial configuration of the figure has to integrate the original fragments, combining scientific analysis of the figure's original physical remains with the careful interpretation of the existing documented sources. The authors propose a phased approach using a composite material matrix based on silt-clay close to the original cliff conglomerate embedding also the original fragments. The presented community-based rebuilding intervention executed by local artisans and artists conceptualizes on the evolution of the figurative meaning of the monument over time with the overall objective to use traditional building techniques to retain tangible and intangible values that maintain the authenticity and the specific significance and spirit of this place. The result has the potential to contribute to a necessary reconciliation process. It may serve as an exemplary case in World Heritage context able to bridge different cultural approaches to heritage among regional, national, and international bodies and stakeholders while respecting diverse values, meanings and the Buddha figure's original physical remains alike.

Non-destructive testing of objects and structures is a valuable tool. Specially in cultural heritage where the preservation of the inspected sample is of vital importance. In this paper, a decorative marquetry sample is inspected with three NDT techniques: air-couple ultrasound, computed-tomography scan and infrared thermography. Results from the three techniques were compared.

Cultural heritage preservation using photometric approaches received increasing significance in the past years. Capturing of these datasets is usually done with high-end cameras at maximum image resolution enabling high quality reconstruction results while leading to immense storage consumptions. In order to maintain archives of these datasets, compression is mandatory for storing them at reasonable cost. In this paper, we make use of the mostly static background of the capturing environment that does not directly contribute information to 3d reconstruction algorithms and therefore may be approximated using lossy techniques. We use a superpixel and figure-ground segmentation based near-lossless image compression algorithm that transparently decides if regions are relevant for later photometric reconstructions. This makes sure that the actual artifact or structured background parts are compressed with lossless techniques. Our algorithm achieves compression rates compared to the PNG image compression standard ranging from 1:2 to 1:4 depending on the artifact size.

Verifying the identity of a person (sitter) portrayed in a historical painting is often a challenging but critical task in art historian research. In many cases, this information has been lost due to time or other circumstances and today there are only speculations of art historians about which person it could be. Art historians often use subjective factors for this purpose and then infer from the identity information about the person depicted in terms of his or her life, status, and era. On the other hand, automated face recognition has achieved a high level of accuracy, especially on photographs, and considers objective factors to determine the identity or verify a suspected identity. The limited amount of data, as well as the domain-specific challenges, make the use of automated face recognition methods in the domain of historic paintings difficult. We propose a specialized, likelihood-based fusion method to enable deep learning-based face recognition on historic portrait paintings. We additionally propose a method to accurately determine the confidence of the made decision to assist art historians in their research. For this purpose, we used a model trained on common photographs and adapted it to the domain of historical paintings through transfer learning. By using an underlying challenge dataset, we compute the likelihood for the assumed identity against reference images of the identity and fuse them to utilize as much information as possible. From these results of the likelihoods fusion, we then derive decision confidence to make statements to determine the certainty of the model’s decision. The experiments were carried out in a leave-one-out evaluation scenario on our created database, the largest authentic database of historic portrait paintings to date, consisting of over 760 portrait paintings of 210 different sitters by over 250 different artists. The experiments demonstrated, that a) the proposed approach outperforms pure face recognition solutions, b) the fusion approach effectively combines the sitter information towards a higher verification accuracy, and c) the proposed confidence estimation approach is highly successful in capturing the estimated accuracy of the decision. The meta-information of the used historic face images can be found at https://github.com/marcohuber/HistoricalFaces.

Eine Präsentation der erreichten und anvisierten Ziele der Initiative „Forschungsdatenmanagement“ der Berlin-Brandenburgischen Akademie der Wissenschaften von Reinhold Kliegl, Katja Marciniak und Alexander Czmiel (Stand: 24.02.2022).