Benjamin Serbe

In recent years, R has silently become the workhorse for many quantitative archaeologists. It’s open source, platform-independent and can be linked very well with other programming languages. [...] Nevertheless, there are still many colleagues who have not yet realised the potential of the language and how easy it is today to conduct high quality research with the available tools. [...]
Within this session we would like to explore the state of the art and the potential application of R in archaeology. We invite presentations for this session that explore questions like (but not limited to):
* What are the specific benefits of this statistical framework in the eyes of its users?
* What are the possibilities? What are the limits?
* What future directions might the usage of R in archaeology have?
* Which archaeological package has been developed, and which package still has to be developed to improve the usability of the sofware for archaeologists?
* What has to be considered to optimise the workflow with R?
We especially would like to attract colleagues who might present archaeological R packages that are ready or in the making and demonstrate their relevance for archaeological analysis. Also we would like to encourage potential presenters to demonstrate their research approaches via live coding, for which we would support them in ensuring that their presentations will work offline and on foreign hardware. [...] We
hope to foster a productive and inclusive exchange between both young and experienced users from all backgrounds.

Location modeling, both inductive and deductive, is widely used in archaeology to predict or investigate the spatial distribution of sites. The commonality among these approaches is their consideration of only spatial effects of the first order (i.e., the interaction of the locations with the site characteristics). Second-order effects (i.e., the interaction of locations with each other) are rarely considered. We introduce a deductive approach to investigating such second-order effects using linguistic hypotheses about settling behavior in the Final Palaeolithic. A Poisson process was used to simulate a point distribution using expert knowledge of two distinct hunter-gatherer groups, namely, reindeer hunters and elk hunters. The modeled points and point densities were compared with the actual finds. The G-, F-, and K-function, which allow for the identification of second-order effects of varying intensity for different periods, were applied. The results reveal differences between the two investigated groups, with the reindeer hunters showing location-related interaction patterns, indicating a spatial memory of the preferred locations over an extended period of time. Overall, this paper shows that second-order effects occur in the geographical modeling of archaeological finds and should be taken into account by using approaches such as the one presented in this paper.

Dec 02, 2021 to Dec 04, 2021
Hybrid: Audimax CAP2 – Hörsaal C at Kiel University and on ZOOM

Exchange networks structure and development are essential for explaining social and economic inequalities. The conference aims to detect those inequalities within the distribution of sourced raw materials over time and space. It centres on large-scale exchange networks from the Neolithic to the Iron Age.

For access to the zoom conference please contact:
Linda Seifert stu227208@mail.uni-kiel.de

The Big Exchange project investigates large-scale exchange systems in Eurasia and Africa (8000-1 BC). We concentrate on raw materials of known origin ('sourced finds'). Network analysis of tools and artificial intelligence methods are used to analyse the combined data sets. We invite broad collaboration on bimodal exchange networks.