This is the NetLogo model described in the paper (file name: DICI .nlog). Sample shape-files have... more This is the NetLogo model described in the paper (file name: DICI .nlog). Sample shape-files have also been provided so that the model can be trialled. Please note that these files have to be saved in the same location as the NetLogo model for them to import.
This article describes in detail how the Dig It, Design It (DIDI) simulation tool operates to des... more This article describes in detail how the Dig It, Design It (DIDI) simulation tool operates to design a subsurface landscape sampling strategy and predict its likely effectiveness. The purpose of the DIDI model is to help archaeologists develop statistically sound subsurface sampling programs that maximise the number of sites found while minimising the number of sampling units used. It has been unusual for archaeological test-pitting programs to be theoretically tested or statistically justified by simulation prior to implementation. Previous research by Kintigh (1988) and Krakker et al. (1983) established the statistical principles underlying the subsurface sampling of a rectangular survey area, and Kintigh pioneered the use of Monte Carlo simulations to test the effectiveness of these sampling strategies. DIDI provides an updated version of this simulation approach that has three key benefits over the original version:1. It allows the user to model a larger range of possible archaeological conditions by providing an additional density distribution function (see below), and making the clustering parameter available with all distribution functions;2. DIDI gives the user the option of filling the previously unavoidable gaps around the edges of the survey area with additional, suitably placed test-units, thereby increasing the detection rate of a sampling strategy; and3. It is free to download and use and is compatible with modern operating systems.
In the southern African archaeological sequence, the Levallois method of core reduction is consid... more In the southern African archaeological sequence, the Levallois method of core reduction is considered to be a distinctive technological feature of the Middle Stone Age (MSA). Similarly, the transition from MSA to Later Stone Age (LSA) has been defined by a decline in the prevalence of Levallois and an increase in prismatic blade production and the use of bipolar percussion to reduce cores. Reanalysis of material recovered from Howiesons Poort Shelter-the eponymous site for the Howiesons Poort phase of the southern African MSA-has revealed that most of the Levallois cores from the site were knapped using a combination of freehand and bipolar percussive techniques. In these cases, freehand percussion was used to prepare and reshape the cores, while bipolar percussion was used as a targeted strategy for detaching Levallois flakes. The discovery of this combination is significant because the accepted definition of the Levallois method prescribes the use of freehand, hard-hammer percussion only. This paper describes the trends in core morphology and reduction processes associated with this bipolar Levallois strategy and evaluates some possible motivations for using bipolar percussion to detach Levallois flakes. Analysis of core dimensions and reduction sequences suggests a gradual strategic transition between freehand Levallois and bipolar bidirectional-opposing reduction strategies as cores become smaller. Contrary to traditional depictions of the technique, bipolar percussion was used by knappers at Howiesons Poort Shelter on cores of a wide range of sizes regardless of material, particularly in situations where control over the force and location of flake removing blows was critical. As well as adding to a growing image of the technological and behavioural complexity of Howiesons Poort (and indeed MSA) hominins, these discoveries have important implications for our understanding of both the Levallois reduction method and the bipolar percussive technique.
This paper presents a new simulation tool, Dig It, Design It, which allows the archaeologist to e... more This paper presents a new simulation tool, Dig It, Design It, which allows the archaeologist to easily design an optimal subsurface sampling program for the detection of buried artefacts. The design of such a program rests upon the relationship between the sampling methodology and the characteristics of the artefact concentrations under study, principally their size, density and density distribution. While the need to consider this relationship has been previously established, a model which automatically performs these calculations had not yet been designed. Dig It, Design It is the first model to be presented which considers artefact site properties and detection probabilities to produce an optimal sampling strategy for the archaeologist, and to provide the detection probabilities for artefact sites with different properties. The model is available online, is very easy to use, and no mathematical knowledge is required. Dig It, Design It thus has the potential to dramatically increase the use of statistically defensible sampling programs within the archaeological community.
Abstract There is a general awareness amongst archaeologists that the intensity of a sampling pro... more Abstract There is a general awareness amongst archaeologists that the intensity of a sampling program, i.e. the number of pits, their size and their spacing, has a strong bearing on discovery rates. However, rarely is the effect of this relationship on specific sampling strategies explicitly assessed due to the difficulty of running the required mathematical models. This paper presents a new simulation tool Dig It, Check It, which allows the archaeologist to easily determine the effectiveness of a sampling program against a variety of artefact site types. This is the first model to be presented which employs simulation to assess the effectiveness of irregular, real-world subsurface sampling programs through the importation of an ArcGis file. This means that a sampling strategy which includes test-pits of varying sizes and intervals can be assessed, as can survey areas of non-rectangular shape. Small artefact concentrations are particularly vulnerable to detection failure, and this model allows the archaeologist to determine whether their absence reflects reality or is a product of the sampling program.
This data article describes how the Dig It Check It (DICI) model operates. The purpose of the DIC... more 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.
This article describes in detail how the Dig It, Design It (DIDI) simulation tool operates to des... more This article describes in detail how the Dig It, Design It (DIDI) simulation tool operates to design a subsurface landscape sampling strategy and predict its likely effectiveness. The purpose of the DIDI model is to help archaeologists develop statistically sound subsurface sampling programs that maximise the number of sites found while minimising the number of sampling units used. It has been unusual for archaeological test-pitting programs to be theoretically tested or statistically justified by simulation prior to implementation. Previous research by Kintigh (1988) and Krakker et al. (1983) established the statistical principles underlying the subsurface sampling of a rectangular survey area, and Kintigh pioneered the use of Monte Carlo simulations to test the effectiveness of these sampling strategies. DIDI provides an updated version of this simulation approach that has three key benefits over the original version:
1. It allows the user to model a larger range of possible archaeological conditions by providing an additional density distribution function (see below), and making the clustering parameter available with all distribution functions; 2. DIDI gives the user the option of filling the previously unavoidable gaps around the edges of the survey area with additional, suitably placed test-units, thereby increasing the detection rate of a sampling strategy; and 3. It is free to download and use and is compatible with modern operating systems.
There is a general awareness amongst archaeologists that the intensity of a sampling program, i.e... more There is a general awareness amongst archaeologists that the intensity of a sampling program, i.e. the number of pits, their size and their spacing, has a strong bearing on discovery rates. However, rarely is the effect of this relationship on specific sampling strategies explicitly assessed due to the difficulty of running the required mathematical models. This paper presents a new simulation tool Dig It, Check It, which allows the archaeologist to easily determine the effectiveness of a sampling program against a variety of artefact site types. This is the first model to be presented which employs simulation to assess the effectiveness of irregular, real-world subsurface sampling programs through the importation of an ArcGis file. This means that a sampling strategy which includes test-pits of varying sizes and intervals can be assessed, as can survey areas of non-rectangular shape. Small artefact concentrations are particularly vulnerable to detection failure, and this model allows the archaeologist to determine whether their absence reflects reality or is a product of the sampling program.
This paper presents a new simulation tool, Dig It, Design It, which allows the archaeologist to e... more This paper presents a new simulation tool, Dig It, Design It, which allows the archaeologist to easily design an optimal subsurface sampling program for the detection of buried artefacts. The design of such a program rests upon the relationship between the sampling methodology and the characteristics of the artefact concentrations under study, principally their size, density and density distribution. While the need to consider this relationship has been previously established, a model which automatically performs these calculations had not yet been designed. Dig It, Design It is the first model to be presented which considers artefact site properties and detection probabilities to produce an optimal sampling strategy for the archaeologist, and to provide the detection probabilities for artefact sites with different properties. The model is available online, is very easy to use, and no mathematical knowledge is required. Dig It, Design It thus has the potential to dramatically increase the use of statistically defensible sampling programs within the archaeological community.
... 13649. Braun, DR, Rogers, MJ, Harris, JWK and Walker, SJ 2008. Landscape-scalevariation in h... more ... 13649. Braun, DR, Rogers, MJ, Harris, JWK and Walker, SJ 2008. Landscape-scalevariation in hominin tool use: evidence from the Developed Oldowan. Journal of Human Evolution, 55: 105363. Burgess, RJ and Kvamme, KL 1978. ...
This is the NetLogo model described in the paper (file name: DICI .nlog). Sample shape-files have... more This is the NetLogo model described in the paper (file name: DICI .nlog). Sample shape-files have also been provided so that the model can be trialled. Please note that these files have to be saved in the same location as the NetLogo model for them to import.
This article describes in detail how the Dig It, Design It (DIDI) simulation tool operates to des... more This article describes in detail how the Dig It, Design It (DIDI) simulation tool operates to design a subsurface landscape sampling strategy and predict its likely effectiveness. The purpose of the DIDI model is to help archaeologists develop statistically sound subsurface sampling programs that maximise the number of sites found while minimising the number of sampling units used. It has been unusual for archaeological test-pitting programs to be theoretically tested or statistically justified by simulation prior to implementation. Previous research by Kintigh (1988) and Krakker et al. (1983) established the statistical principles underlying the subsurface sampling of a rectangular survey area, and Kintigh pioneered the use of Monte Carlo simulations to test the effectiveness of these sampling strategies. DIDI provides an updated version of this simulation approach that has three key benefits over the original version:1. It allows the user to model a larger range of possible archaeological conditions by providing an additional density distribution function (see below), and making the clustering parameter available with all distribution functions;2. DIDI gives the user the option of filling the previously unavoidable gaps around the edges of the survey area with additional, suitably placed test-units, thereby increasing the detection rate of a sampling strategy; and3. It is free to download and use and is compatible with modern operating systems.
In the southern African archaeological sequence, the Levallois method of core reduction is consid... more In the southern African archaeological sequence, the Levallois method of core reduction is considered to be a distinctive technological feature of the Middle Stone Age (MSA). Similarly, the transition from MSA to Later Stone Age (LSA) has been defined by a decline in the prevalence of Levallois and an increase in prismatic blade production and the use of bipolar percussion to reduce cores. Reanalysis of material recovered from Howiesons Poort Shelter-the eponymous site for the Howiesons Poort phase of the southern African MSA-has revealed that most of the Levallois cores from the site were knapped using a combination of freehand and bipolar percussive techniques. In these cases, freehand percussion was used to prepare and reshape the cores, while bipolar percussion was used as a targeted strategy for detaching Levallois flakes. The discovery of this combination is significant because the accepted definition of the Levallois method prescribes the use of freehand, hard-hammer percussion only. This paper describes the trends in core morphology and reduction processes associated with this bipolar Levallois strategy and evaluates some possible motivations for using bipolar percussion to detach Levallois flakes. Analysis of core dimensions and reduction sequences suggests a gradual strategic transition between freehand Levallois and bipolar bidirectional-opposing reduction strategies as cores become smaller. Contrary to traditional depictions of the technique, bipolar percussion was used by knappers at Howiesons Poort Shelter on cores of a wide range of sizes regardless of material, particularly in situations where control over the force and location of flake removing blows was critical. As well as adding to a growing image of the technological and behavioural complexity of Howiesons Poort (and indeed MSA) hominins, these discoveries have important implications for our understanding of both the Levallois reduction method and the bipolar percussive technique.
This paper presents a new simulation tool, Dig It, Design It, which allows the archaeologist to e... more This paper presents a new simulation tool, Dig It, Design It, which allows the archaeologist to easily design an optimal subsurface sampling program for the detection of buried artefacts. The design of such a program rests upon the relationship between the sampling methodology and the characteristics of the artefact concentrations under study, principally their size, density and density distribution. While the need to consider this relationship has been previously established, a model which automatically performs these calculations had not yet been designed. Dig It, Design It is the first model to be presented which considers artefact site properties and detection probabilities to produce an optimal sampling strategy for the archaeologist, and to provide the detection probabilities for artefact sites with different properties. The model is available online, is very easy to use, and no mathematical knowledge is required. Dig It, Design It thus has the potential to dramatically increase the use of statistically defensible sampling programs within the archaeological community.
Abstract There is a general awareness amongst archaeologists that the intensity of a sampling pro... more Abstract There is a general awareness amongst archaeologists that the intensity of a sampling program, i.e. the number of pits, their size and their spacing, has a strong bearing on discovery rates. However, rarely is the effect of this relationship on specific sampling strategies explicitly assessed due to the difficulty of running the required mathematical models. This paper presents a new simulation tool Dig It, Check It, which allows the archaeologist to easily determine the effectiveness of a sampling program against a variety of artefact site types. This is the first model to be presented which employs simulation to assess the effectiveness of irregular, real-world subsurface sampling programs through the importation of an ArcGis file. This means that a sampling strategy which includes test-pits of varying sizes and intervals can be assessed, as can survey areas of non-rectangular shape. Small artefact concentrations are particularly vulnerable to detection failure, and this model allows the archaeologist to determine whether their absence reflects reality or is a product of the sampling program.
This data article describes how the Dig It Check It (DICI) model operates. The purpose of the DIC... more 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.
This article describes in detail how the Dig It, Design It (DIDI) simulation tool operates to des... more This article describes in detail how the Dig It, Design It (DIDI) simulation tool operates to design a subsurface landscape sampling strategy and predict its likely effectiveness. The purpose of the DIDI model is to help archaeologists develop statistically sound subsurface sampling programs that maximise the number of sites found while minimising the number of sampling units used. It has been unusual for archaeological test-pitting programs to be theoretically tested or statistically justified by simulation prior to implementation. Previous research by Kintigh (1988) and Krakker et al. (1983) established the statistical principles underlying the subsurface sampling of a rectangular survey area, and Kintigh pioneered the use of Monte Carlo simulations to test the effectiveness of these sampling strategies. DIDI provides an updated version of this simulation approach that has three key benefits over the original version:
1. It allows the user to model a larger range of possible archaeological conditions by providing an additional density distribution function (see below), and making the clustering parameter available with all distribution functions; 2. DIDI gives the user the option of filling the previously unavoidable gaps around the edges of the survey area with additional, suitably placed test-units, thereby increasing the detection rate of a sampling strategy; and 3. It is free to download and use and is compatible with modern operating systems.
There is a general awareness amongst archaeologists that the intensity of a sampling program, i.e... more There is a general awareness amongst archaeologists that the intensity of a sampling program, i.e. the number of pits, their size and their spacing, has a strong bearing on discovery rates. However, rarely is the effect of this relationship on specific sampling strategies explicitly assessed due to the difficulty of running the required mathematical models. This paper presents a new simulation tool Dig It, Check It, which allows the archaeologist to easily determine the effectiveness of a sampling program against a variety of artefact site types. This is the first model to be presented which employs simulation to assess the effectiveness of irregular, real-world subsurface sampling programs through the importation of an ArcGis file. This means that a sampling strategy which includes test-pits of varying sizes and intervals can be assessed, as can survey areas of non-rectangular shape. Small artefact concentrations are particularly vulnerable to detection failure, and this model allows the archaeologist to determine whether their absence reflects reality or is a product of the sampling program.
This paper presents a new simulation tool, Dig It, Design It, which allows the archaeologist to e... more This paper presents a new simulation tool, Dig It, Design It, which allows the archaeologist to easily design an optimal subsurface sampling program for the detection of buried artefacts. The design of such a program rests upon the relationship between the sampling methodology and the characteristics of the artefact concentrations under study, principally their size, density and density distribution. While the need to consider this relationship has been previously established, a model which automatically performs these calculations had not yet been designed. Dig It, Design It is the first model to be presented which considers artefact site properties and detection probabilities to produce an optimal sampling strategy for the archaeologist, and to provide the detection probabilities for artefact sites with different properties. The model is available online, is very easy to use, and no mathematical knowledge is required. Dig It, Design It thus has the potential to dramatically increase the use of statistically defensible sampling programs within the archaeological community.
... 13649. Braun, DR, Rogers, MJ, Harris, JWK and Walker, SJ 2008. Landscape-scalevariation in h... more ... 13649. Braun, DR, Rogers, MJ, Harris, JWK and Walker, SJ 2008. Landscape-scalevariation in hominin tool use: evidence from the Developed Oldowan. Journal of Human Evolution, 55: 105363. Burgess, RJ and Kvamme, KL 1978. ...
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Papers by Amy Tabrett
1. It allows the user to model a larger range of possible archaeological conditions by providing an additional density distribution function (see below), and making the clustering parameter available with all distribution functions;
2. DIDI gives the user the option of filling the previously unavoidable gaps around the edges of the survey area with additional, suitably placed test-units, thereby increasing the detection rate of a sampling strategy; and
3. It is free to download and use and is compatible with modern operating systems.
1. It allows the user to model a larger range of possible archaeological conditions by providing an additional density distribution function (see below), and making the clustering parameter available with all distribution functions;
2. DIDI gives the user the option of filling the previously unavoidable gaps around the edges of the survey area with additional, suitably placed test-units, thereby increasing the detection rate of a sampling strategy; and
3. It is free to download and use and is compatible with modern operating systems.