archeofrag-gui

This application implemets some features of the archeofrag R package for spatial analysis in archaeology from the study of refitting fragments of objects. It includes methods to evaluate and validate the distinction between archaeological spatial units (e.g. layers), from the distribution and the topology of the refitting relationships between fragments contained in these units.

Input Data

Either upload your data or load the example data set (refitting data from the Liang Abu rock shelter, Borneo). Use the menu on the left to upload your “relations” and “fragments” data as CSV files.

  • The relations table must have a row for each refitting relationship and two columns containing the identifiers of each pair of refitting fragments, respectively;
  • the fragments table must have a row for each fragment, the first column contains its identifier and the second column contains the spatial unit it belongs to (name this column “layer”).

Measurements

In this tab, statistics are reported for all pairs of spatial units defined in the dataset: number of fragments and refitting relationships, etc. The cohesion and admixture values are calculated using the TSAR method. Tables and figures facilitate the exploration of the results

Comparison with simulated data

This tab includes functions for in-depth analysis of a specific pair of spatial units. This pair is compared to similar artificial data, simulated for two different formation hypothesis:

  • H1, the archaeological material studied comes from a single deposition event (although archeaologists might have distinguished two spatial units / depositional events).
  • H2, the material was deposited during two deposition events.

References

The code and more information are available on github and in the following publications:


Stats by pair of spatial units

Admixture between spatial units


Information

Instruction

  • Select the pair of spatial units to compare in the menu
  • The parameters of the simulation are automatically filled with the values measured on the graph corresponding to the two spatial units selected, but can be edited.
  • Set the number of simulated graphs to generate by hypothesis, and click on the “Run” button. Using parallelization speeds up the computation (however, if an error appears, untick the box and be patient).

Procedure

Parameters (number of objects, fragment balance, etc.) are extracted from the input graph for the pair of spatial units under study, and used to generate a series of artificial graphs. Artificial graphs are generated for two deposition hypotheses:

  1. the objects were buried in a single spatial unit and subsequently moved;
  2. the objects were buried in two spatial units and subsequently moved.

Results

The table below summarises the results for each parameter, indicating
  • whether the simulated values for H1 and H2 are significantly different (Wilcoxon test, “H1 != H2?” and “p.value” columns), and
  • whether the observed value is lower / within / higher the interquartile range of values simulated for H1 and H2, respectively (“Obs. value/H1” and “Obs. value/H2” columns).
Charts are generated for the parameters measured on the empirical and artificial fragmentation graphs:
  • the value observed on the empirical graph is represented by a vertical bar,
  • the distribution of values for each hypotheses are represented by dark (H1) and light (H2) grey shades, respectively.

Pair of spatial units

Parameters set up

Computation set up

Results