Presenting multivariate statistical protocols in R using Roman wine amphorae productions in Catalonia, Spain

Angourakis, Andreas; Ferreras, Verònica Martínez; Torrano, Alexis; Esparraguera, Josep María Gurt i

doi:10.1016/j.jas.2018.03.007

Cited by 7 publications

(3 citation statements)

References 35 publications

(51 reference statements)

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“…Unsupervised methods are widely used in provenance studies of pottery and particularly PCA is routinely applied [43] to define geochemical and/or petrographic groups within sampled materials from archaeological workshops and consumption centers. However, the presented results show that these methods would have failed to detect and distinguish a mixed ensemble containing pottery from the six studied production centers.…”

Section: Discussionmentioning

confidence: 99%

Application of Supervised Machine-Learning Methods for Attesting Provenance in Catalan Traditional Pottery Industry

Anglisano

Casas

Anglisano³

et al. 2019

Minerals

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The traditional pottery industry was an important activity in Catalonia (NE Spain) up to the 20th century. However, nowadays only few workshops persist in small villages were the activity is promoted as a touristic attraction. The preservation and promotion of traditional pottery in Catalonia is part of an ongoing strategy of tourism diversification that is revitalizing the sector. The production of authenticable local pottery handicrafts aims at attracting cultivated and high-purchasing power tourists. The present paper inspects several approaches to set up a scientific protocol based on the chemical composition of both raw materials and pottery. These could be used to develop a seal of quality and provenance to regulate the sector. Six Catalan villages with a renowned tradition of local pottery production have been selected. The chemical composition of their clays and the corresponding fired products has been obtained by Energy dispersive X-ray fluorescence (EDXRF). Using the obtained geochemical dataset, a number of unsupervised and supervised machine learning methods have been applied to test their applicability to define geochemical fingerprints that could allow inter-site discrimination. The unsupervised approach fails to distinguish samples from different provenances. These methods are only roughly able to divide the different provenances in two large groups defined by their different SiO 2 and CaCO 3 concentrations. In contrast, almost all the tested supervised methods allow inter-site discrimination with accuracy levels above 80%, and accuracies above 85% were obtained using a meta-model combining all the predictive supervised methods. The obtained results can be taken as encouraging and demonstrative of the potential of the supervised approach as a way to define geochemical fingerprints to track or attest the provenance of samples.

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Section: Discussionmentioning

confidence: 99%

Application of Supervised Machine-Learning Methods for Attesting Provenance in Catalan Traditional Pottery Industry

Anglisano

Casas

Anglisano³

et al. 2019

Minerals

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“…MCA is a descriptive and exploratory statistical treatment designed to analyse large data sets that include different types of information (e.g. Baxter et al 2008;Baxter 2009;Montana et al 2009 andAngourakis et al 2018;Montana et al 2018). The variables and conversion values of the different qualifiers are shown in full in Supplementary Material Table S1, which has 21 columns and 77 rows.…”

Section: Archaeological Potterymentioning

confidence: 99%

The indigenous settlement of Monte Iato (western Sicily): an ethnoarchaeometric approach for outlining local Archaic ceramic productions

Montana

Polito

Kistler

et al. 2021

Archaeol Anthropol Sci

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An ethnoarchaeometric approach has been followed to identify the textural and compositional characteristics of the ceramic pastes produced in ancient Iaitas/Ietas, an indigenous site located in western Sicily on Monte Iato, a few tens of kilometres from Palermo. This approach was primarily motivated by the lack of discovered Archaic kilns or production sites/workshops and the inability to identify reference groups. Raw clays were sampled in the territory of San Cipirello and San Giuseppe Iato (today’s municipalities both sited on the northern slopes of Monte Iato), together with representative historic tiles and bricks locally produced until fairly recently. Grain-size analysis and experimental firings were performed on the clay samples. A significant number of archaeological ceramic samples (incised and painted indigenous pottery dating back to the seventh–fifth centuries BCE) from stratigraphic excavations on Monte Iato, and hypothesized as local productions on a stylistic-morphological basis, was carefully selected for archaeometric analysis. This set of samples (90 in total, comprising raw clays, historic tiles/bricks and archaeological ceramics) underwent a combined chemical and mineralogical-petrographic analysis to identify any possible compositional matching. This approach enabled the identification of minero-petrographic and chemical markers pertinent to the indigenous Archaic pottery produced at Monte Iato, although no evidence of coeval ceramic kilns has been found so far. Local raw clay sources have been documented and some significant points of the chaîne opératoire adopted in antiquity have been noted (clay mixing and tempering practices). Attesting Monte Iato as a centre of ceramic production and defining both the microscopic fabric and the average composition of local pastes open up new perspectives in the complex issue concerning the production and regional circulation of incised and painted indigenous ceramics in Archaic Sicily.

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“…Successive generations of ceramic packaging containers have significant characteristics of the era in terms of shape, decoration, glaze color, etc., reflecting the cultural characteristics and aesthetic trends of different historical periods [4][5][6]. Multivariate statistical analysis is a method for processing and analyzing multivariate data and is suitable for exploring and interpreting patterns and relationships in complex data sets [7][8][9]. When studying the development history of Chinese ceramic packaging containers, multivariate statistical analysis methods, such as principal component analysis, cluster analysis, etc., can be used to analyze a large amount of sample data and reveal the development patterns and characteristics of ceramic packaging containers in different historical periods [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Analyzing the Development History of Chinese Ceramic Packaging Containers and Their Modern Design Innovation Based on Multivariate Statistics

Wu,

Tao

2024

Applied Mathematics and Nonlinear Sciences

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This paper explores the development history and modern design innovation of Chinese ceramic packaging containers through multivariate statistical analysis, revealing their essential role in the market and cultural heritage. The development history and contemporary design innovation of Chinese ceramic packaging containers are studied in depth. The study finds that ceramic packaging containers have evolved from prehistoric hand-kneaded small pieces to the present, constantly incorporating new crafts and cultural elements. Regarding formal aesthetics, the use of rhythm and rhyme in ceramic packaging containers grew at 81.13% between 2015 and 2020, suggesting that designs tend to be more dynamic and expressive. Data analysis shows that the key factors influencing the design of ceramic packaging containers include process technology, trade development, cultural concepts and religious beliefs. Regression analysis indicates that these factors significantly positively impact the design quality of ceramic packaging containers, with a model fit of 63.52%, revealing that these factors jointly promote the improvement of design quality. Innovative combination of traditional elements and modern technology is the key to fostering innovation of ceramic packaging container design and cultural heritage. The market competitiveness and cultural value of ceramic packaging containers can be effectively promoted by emphasizing the development of craft technology and the integration of cultural elements.

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Presenting multivariate statistical protocols in R using Roman wine amphorae productions in Catalonia, Spain

Cited by 7 publications

References 35 publications

Application of Supervised Machine-Learning Methods for Attesting Provenance in Catalan Traditional Pottery Industry

Application of Supervised Machine-Learning Methods for Attesting Provenance in Catalan Traditional Pottery Industry

The indigenous settlement of Monte Iato (western Sicily): an ethnoarchaeometric approach for outlining local Archaic ceramic productions

Analyzing the Development History of Chinese Ceramic Packaging Containers and Their Modern Design Innovation Based on Multivariate Statistics

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