On quantifying and visualizing the potter's personal style

Ceramic-sherds analysis has been concerned with categorizing to types according to vessel shape and size for the description of a given material culture. Yet, the characterization of ceramic variations and their meaning receives little attention in the archaeological study. In the present research,...

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Veröffentlicht in:Journal of archaeological science 2019-08, Vol.108, p.104973, Article 104973
Hauptverfasser: Harush, Ortal, Glauber, Naama, Zoran, Amit, Grosman, Leore
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Sprache:eng
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Zusammenfassung:Ceramic-sherds analysis has been concerned with categorizing to types according to vessel shape and size for the description of a given material culture. Yet, the characterization of ceramic variations and their meaning receives little attention in the archaeological study. In the present research, we wished to monitor small-scale variations, searching for the unique signature of the individual potter during production. We thus examined new parameters for distinguishing between trainee potters and monitoring their distinct styles as part of an integrated experimental archaeological study. For the purposes of this research, ceramic students were instructed to produce the same part of a storage jar repeatedly for several days following a strict protocol—with a single prototype and using the same technique in the same workspace. All the produced items were 3-D scanned to extract accurate geometric parameters for classification. Cluster analysis was used to analyze the digital data, in addition to a novel data visualization technique that was developed for detecting ceramic variations. These methods enabled us to distinguish the potters by their individual styles, probably already established in the early stages of learning. Our results show that the novel visualization approach, together with the quantitative method, allows us to efficiently identify the location, on the vessels, of the potters' stylistic fingerprint. •We conducted an experiment with five trainee potters that produced 138 vessels.•All products were 3D scanned and computational analysis was conducted.•A novel data visualization technique was developed.•We found that personal style can be identified in the early stages of learning.•We show that these methods can detect the personal signature of a potter.
ISSN:0305-4403
1095-9238
DOI:10.1016/j.jas.2019.104973