INVESTIGATING MATERIAL DECAY OF HISTORIC BUILDINGS USING VISUAL ANALYTICS WITH MULTI‐TEMPORAL INFRARED THERMOGRAPHIC DATA

This paper shows how visual analytics methodology can be used to facilitate interpretation of multi‐temporal thermographic imagery for the purpose of restoration of cultural heritage. We explore thermographic data in a visual environment from the unifying spatio‐temporal perspective in an attempt to identify spatial and spatio‐temporal patterns that could provide information about the structure and the level of decay of the material, and the presence of other physical phenomena in the wall. The approach is tested on a thermographic dataset captured on the façade of a Romanesque building from the 13th century—the Cathedral in Matera (Italy).     

NON‐DESTRUCTIVE INVESTIGATION OF BRONZE ARTEFACTS FROM THE MARCHES NATIONAL MUSEUM OF ARCHAEOLOGY USING NEUTRON DIFFRACTION*

Non‐destructive neutron diffraction techniques were applied to determine composition and microstructure data, and hence to derive information on manufacturing techniques of Picenum bronze artefacts. Furthermore, texture analyses were carried out on standards and suitable ancient artefacts to investigate their potential role in archaeometallurgical studies. This is a first step towards an overall characterization of the bronze collection of the Marches National Museum of Archaeology, Italy, and the analytical demonstration of relations with and differences compared to Etruscan metallurgy. The work is also an example application of the powerful non‐destructive archaeometrical approaches provided by time‐of‐flight neutron diffraction.     

STATISTICAL ASPECTS OF POTTERY QUANTIFICATION FOR THE DATING OF SOME ARCHAEOLOGICAL CONTEXTS*

This paper describes some statistical analyses of a particular archaeological material (pottery) originating at some sites in the city of Tours. An important part of the archaeological study of pottery is the comparison of ceramic assemblages to establish the absolute dates of contexts. In this paper, a statistical model is built to assess this comparison. The statistical procedure uses classical tools (correspondence analysis, linear regression and resampling methods) in an iterative scheme. Archaeologists may find in the paper a useful set of known statistical methods, while statisticians can learn a method of ‘arranging’ well‐known techniques. No method is new, but their combination is characteristic of this application.     

COMPARING GLASS COMPOSITIONAL ANALYSES*

In a recently published study of Romano‐British colourless glass compositions, using inductively coupled plasma spectroscopy, 28 glasses from Colchester sampled in a previous study were resampled. This was done deliberately, with a view to examining the repeatability of results from sampling on different occasions. We report on our results here, developing in the process some simple statistical methodology that could be applied in similar situations. The potential for combining analyses undertaken at different times is discussed and illustrated.     

AMPHORAE FROM LYONS: PETROGRAPHIC AND CHEMICAL ARGUMENTS*

This paper briefly presents a method for the interpretation of quantitative petrographic data and chemical composition data from amphorae found in Lyons with the aim of determining whether or not the amphorae are of local production. We will try to define the exact place of each argument in our reasoning about the attribution of the origin of these ceramics, while insisting on the zones of uncertainty for each method. It is important to emphasize here that in assigning the origin of the Lyons amphorae all the arguments must be used conjointly. The presence of rhyolite in the temper is not enough to determine the Lyons origin of an amphora, and the geochemical arguments are often insufficient to make a decision. It is a reasoned application of petrographic, geochemical and archaeological arguments which enables us to pronounce an attribution.     

TRACE ELEMENT GEOCHEMISTRY OF NATIVE COPPER FROM THE WHITE PINE MINE,MICHIGAN (USA): IMPLICATIONS FOR SOURCING ARTEFACTS*

Eighty-five samples of native copper from the White Pine mine in upper Michigan were analysed by neutron activation to document geochemical variability within a single locality. Silver, sodium, antimony and scandium contents vary by two orders of magnitude, whereas arsenic values vary by three orders of magnitude. This variability reinforces the need for provenance studies of artefacts to examine sufficient samples to test for heterogeneity within the source area. The White Pine suite contains some of the most impure native copper that has been analysed to date. Arsenic and silver values of these impure samples overlap with those of European coppers, but consideration of several elements can still distinguish native copper from European copper.     

MULTIVARIATE ANALYSIS OF COMPOSITIONAL DATA: APPLIED COMPARISONS FAVOUR STANDARD PRINCIPAL COMPONENTS ANALYSIS OVER AITCHISON'S LOGLINEAR CONTRAST METHOD

There has been debate about whether standard principal components analysis is appropriate for the multivariate analysis of compositional data (e.g. oxide composition of glass), Loglinear transformation has been recommended by Aitchison as a prerequisite. This paper argues that previous comparisons of methodological merits have tended to circularity of argument by making assumptions about the form of a good multivariate result. To break the circularity of argument the authors have introduced randomized variables into five data sets. A good result must recognize these randomized variables as noise and place them near the centroid of the principal components scattergram of variable loadings. Standard principal components analysis is found to perform better than loglinear transformation in its ability to recognize the randomized variables. It is concluded that loglinear transformation tends to introduce spurious structure into a table of compositional data. This paper is followed by a comment by M. J. Baxter.     

MODIFIED MAHALANOBIS FILTERS FOR GROUPING POTTERY BY CHEMICAL COMPOSITION*

A statistical procedure for grouping pottery in provenance studies by chemical data is presented, which now is routinely in use in our laboratory. It is based on the Mahalanobis filter method and X² -statistics, and can be used for both establishing groups and assigning single sherds to already known groups, thus replacing principal components analysis or cluster analysis and avoiding their problems in grouping pottery. The new method is able to consider correlations, uncertainties of measurement and constant shifts of the data in case of dilution. In particular, considering dilution effects results in both a better assignment to and separation of reference groups and is also equivalent to the compositional data approach, if log-transformed data are used. Other distortions of data (e.g., mixing of clays) can also be considered.     

THE EFFICIENT COMPUTATION OF UNBIASED MAHALANOBIS DISTANCES AND THEIR INTERPRETATION IN ARCHAEOMETRY*

This paper argues for cross-validation to reduce bias in estimating Mahalanobis distances of individuals to groups, a particular problem with small sample sizes. Formulae for the efficient computation of cross-validated distances, which avoid excessive matrix inversion, are given. The use of Mahalanobis distances as measures of consistency, or as indications of outlying values, is described. The little-known technique of gamma plotting is outlined and discussed as an aid to interpreting distances in these terms. Both cross-validation and gamma plotting are illustrated in an example on marble composition.