When should archeoViz be Used?

For What Sort of Archaeological Research?

  • Old and new research: recently produced datasets (Cassenade in France, excavated in 2013–2014) and old datasets (Le Poeymaü, excavated in 1948–1956);
  • Site size: small sites (Erb Tanks in Namibia, 4 m²) and large sites (Mas de Vignoles X in France, ≈2400 m²);
  • Site composition: sites made of only one sector (Moulin-Neuf in France) or two sectors, for which two archeoViz instances were created (Roc de Marcamps 1 and 2 in France, Marathousa 1a and 1b in Greece);
  • Assemblage size: small assemblages (Combe-Grèze in France, ≈100 objects) and large assemblages (Le Flageolet in France, ≈65,000 objects);
  • Refittings: dataset including or not information about refitting objects (Chauzey in France, 1846 refits, Le Bout des Vergnes in France, 3740 refits);
  • Location methods: objects accurately located as points (Combe Cullier in France) or approximately located within volumes (Těšetice in Czech Republic);
  • Chronology: Palaeolithic data (Les Jambes, Amalda in the Basque Country), Neolithic (Le Petit Paulmy in France), Medieval (Altenerding in Germany), and ethno-archaeological datasets (the Mask site in Alaska, 20th c.);
  • Publication status: published datasets (the Taï, Grotte XVI, La Roche-à-Pierrot, Bilzingsleben in Germany, Barger Gulch in the US) and unpublished datasets (Roquemissou in France, Bastos in Brazil).

For What Sort of Data?

archeoViz deals with individual objects located by sets of coordinates (x, y, z) and represented as points, i.e. the output of total stations in contemporary excavations. The data structure is kept as simple as possible, with (few) mandatory and some optional variables.

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Example of an input CSV file. Mandatory variables are in italics type. ‘max’ coordinates are for objects inaccurately located within a range. An unlimited number of variables named using the “object_” prefix can be added.

Special Features and Use Cases

Beyond its initial vocation for point clouds, archeoViz can be adapted to other needs and display:


Displaying refittings: archeoViz instance of the Chez Thuilet Palaeolithic site

Spatial uncertainty

Representing location uncertainty: artificial data.

Fabrics measurements

Displaying fabrics measurements: archeoViz instance for the Shuidonggou site


Displaying shapes: elephant bones in the archeoViz instance for the Marathousa 1A site

Reusing the Visualisations and Outputs in the archeoViz web application for Spatial Archaeological Data

In archeoViz, the plots in the “3D plot”, “Map”, “Section X”, and “Section Y” tabs can be exported into two formats:

  • in a vector image format (SVG), for edition with applications as Inskcape or Illustrator.
  • as standalone interactive plots in HTML format.

In addition, the small map in the “Section X” and “Section Y” tabs and the plan of the excavation “Timeline” tab can also be exported in SVG.

Exporting and Editing Figures

The archeoViz visualisation (left) was exported as a SVG file and edited in the Inkscape application (left).

Embedding a standalone HTML visualisation into a Web Page

archeoViz makes it possible to export the 2D and 3D visualisations as interactive HTML standalone files. These files can be sent through email or embedded within other web page. Below, an example with a 3D visualisation exported from the Poeymaü archeoViz instance:

Embedding an archeoViz instance into a Web Page

In the same way, an archeoViz instance can also be embedded in an other web page. For example, Taï site archeoViz instance:

Statistical Analysis and Third-party Applications in the archeoViz Application for Spatial Archaeological Data

Spatial Statistics in archeoViz

archeoViz includes some spatial analysis functionalities for basic and exploratory use:

  • computation of 3D regression surfaces (summarising the distribution of the objects by layer),
  • computation of 3D convex hulls (showing the maximal extension of the objects by layer),
  • computation of 2D contour lines (in the “Map” tab), summarising the horizontal distribution of the objects, in general or by layer.

Analysis with Third-party Applications

Data can be export from the “Statistics” tab to third-party applications for other analysis. If applicable to the dataset at hand, links to the following applications are displayed in the archeoViz “Statistics” tab:

  • archeofrag, for refitting analysis
  • seriograph, for seriation
  • explor, for correspondence analysis
  • amado online, for seriation and classification
  • shinyHeatmaply for classification and heatmaps

See for example the Shuidonggou 2 archeoViz instance, where data can be exported to these applications.

Export to archeofrag

The TSAR method (“Topological Study of Archaeological Refitting”) was published as a new approach in refitting analysis. This method is implemented in the archeofrag R package, and partially demonstrated in the archeofrag R Shiny web application. If a dataset with refitting data is loaded in archeoViz it can be transmitted to the online archeofrag application. See, for example, the Grotte XVI or Flageolet archeoViz instances.

Export to the Seriograph

The Seriograph is a web application (part of the SPARTAAS collection) to visualise changes in the quantitative distribution of artefacts types in ordered or unordered series of spatial units. See, for example, the Poeymaü and Flageolet archeoViz instances.

Export to explor (correspondence analysis)

Data can be exported to the explor R package / shiny application, which has been adapted and deployed for archeoViz. Explor performs a correspondence analysis and allows to interactively explore the results. See, for example, the Taï, Poeymaü or Pirro Nord archeoViz instances.

Export to AMADO online (seriation and classification)

AMADO online is an application for seriation and classification of count data. The application interface is multilingual (9 languages). See, for example, the Taï, Poeymaü or Pirro Nord archeoViz instances.

Export to shinyHeatmaply

Heatmaply is an R package to generate interactive heatmaps. shinyHeatmaply is a Shiny web application to use heatmaply’s functionalities online, namely to compute a clustering using various distances and clustering methods, and to display the result as an heatmap. See, for example, the Grande Rivoire or Poeymaü archeoViz instances.

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