The Dig It Check It model

Abstract

This data article describes how the Dig It Check It (DICI) model operates. The purpose of the DICI model is to assess the effectiveness of a specified subsurface sampling program in the detection of archaeological sites (Way and Tabrett, in press) [1]. Specifically, the aim of the model is to determine the inherent biases of the specified sampling program, i.e. what is the probability that sites of a certain size, density and density-distribution will be, or were, missed by the sampling program. A simulation is run which randomly places sites, the characteristics of which can be varied between runs, in a sampling area with the specified test-pit layout to determine the probability of overlap between the test-pits and sites with the selected characteristics. When overlap does occur, the site is recorded as intersected. The model then calculates the site density at that point and compares it with the test-pit size to determine whether the density is great enough for detection to also occur.

(DIGSS) Determination of Intervals using Georeferenced Survey Simulation: An R package for subsurface survey

“…While every archaeologist who has sunk a spade in the earth has implicitly considered their approach in these terms, they often get confused or conflated when field methods are being discussed or proscribed. Indeed, the disambiguation of these measures is not fundamental to other survey software, including DICI/DIDI [ 12 – 14 ]. In contrast, the DIGSS program offers multiple means by which these two independent measures of the performance of a survey can be assessed, thus opening the door to far more informed considerations of the trade-offs involved in digging more or fewer units, in changing spacing or grid types, or moving from smaller post holes to 50 x 50 cm units.…”

“…The most recent forays into this field have been made by Mosig Way and Tabrett [ 12 – 14 ], who have developed and made available two open-source NetLogo tools ( Dig It , Check It and Dig It , Design It ), which offer the ability to evaluate (retrospectively) and design, by means of simulation, the effectiveness and efficiency of survey testing programs. Dig It , Check It (DICI), “allows the archaeologist to determine what types of sites are probably being missed by a specific program” [ 14 :71], by retrospectively stipulating the area surveyed, test pit configuration (as excavated), and site type (average density, site diameter, and density distribution), to establish the rate at which sites of the type specified were intersected and detected.…”

“…Second, and in contrast with some other available programs (e.g., DICI/DIDI [ 12 – 14 ], which share aspects of DIGSS’ simulation-based approach), DIGSS permits the user to specify ranges for a number of key variables rather than stipulating a single mean value for each variable. Thus, for site density (sites/km 2 ), site area, artifact density, the user is able to input ranges (either min-max or min, max, mean, sd) of values, thereby recognizing that a given survey area may contain few or many sites, which may be small or large, and which may have variable artifact densities.…”

“…Finally, and again unlike DICI/DIDI [ 12 – 14 ], DIGSS’ looping function, which outputs data on effectiveness and efficiency across a user-stipulated range of value, represents a clear advantage of the package. Instead of iteratively performing a series of simulations manually, changing a given variable one step at a time, it is possible to automate this process and track the results so as to identify points of peak performance or moments of inflection as a given variable moves between stipulated end points.…”

A new Monte Carlo simulation tool for designing an archaeological landscape sampling strategy

“…The general concepts and method for how to estimate a detection rate were developed in the 1980s [1 , 2] but the software developed by Kintigh has for many years been impossible to use with modern computer operating systems. In response to this problem, Way and Tabrett [3] , [4] , [5] recently developed two free simulation tools to help archaeologists design an optimal subsurface sampling strategy for their survey area and check the effectiveness (in terms of detection rate) of any such strategy employed by themselves or others. While the statistical and geometric principles governing the creation of an optimally spaced test-pit grid have been discussed elsewhere [1 , 2 , 4] , here we describe in depth the how the simulation tool Dig It, Design It (DIDI) operates, point the reader to additional user resources available, and explain how several key improvements were incorporated into the programming.…”