Geographical Network Analysis

The original data for this model stems from: Ciolek, T. Matthew, 2005. Georeferenced data set (Series 1 - Routes): Trade routes in the Ottoman Empire 1300-1600 CE. OWTRAD Dromographic Digital Data Archives (ODDDA). Old World Trade Routes (OWTRAD) Project. Canberra: www.ciolek.com - Asia Pacific Research Online. (www.ciolek.com/OWTRAD/DATA/tmcTRm1300.html)
This dataset was significantly enlarged and modified by me in order to map the most important maritime and terrestrial routes across the Eastern Mediterranean in the period 1300-1500 AD, with a focus on the Balkans and Asia Minor, the core regions of the Byzantine as well as of the Ottoman Empire.
This dataset was then turned into a topological network model, in which localities serve a nodes and the routes between them as links.
In order to integrate “real space” into the model, the strength of links between nodes was weighted according to their geographical distance (the larger the distance the bigger the cost of interaction and the weaker the connection - for terrestrial routes, a cost factor of five has been applied in comparison with maritime routes).
On this basis, several measurements of network centrality have been calculated in order to quantify the relative significance of sites and routes within the model for the Eastern Mediterranean. In addition, two analyses for diffusion and expansion related to historical developments (the spread of the Black Death from the Crimea and the expansion of the Ottoman state from Northwestern Asia Minor) have been executed.
This study, which is work in progress, was made possible on the basis of a fellowship of the Alexander S. Onassis Public Benefit Foundation for research at the Institute for Historical Research of the National Hellenic Research Foundation in Athens.

In the past numerous concepts of urbanity have been discussed and a variety of criteria for towns have been developed. They include size, population, legal aspects, way of life, structural and functional approaches. However, since the mentioned criteria cover only a part of the phenomenon and partly use fixed and arbitrary thresholds, they are not sufficient for analysis. We turn to an understanding of urbanity as a process that creates and shapes the scenery of the buildings and people and that is mainly driven by complexity. In this sense, we understand urbanity as a process of adaptation to changing conditions or contexts in a complex settlement system, which is triggered by size, attracted by exemplary solutions and characterized by the emergence of new structures. In this paper we address the issue of relative centrality as proposed by Christaller in the urbanity process as well as centrality within a network sciences approach. Our aim is to interweave different concepts of urbanity, centrality, interaction and connectivity, combining different concepts and research traditions as well as expanding them, resulting in a collection of different terminological frameworks. In the context of adaptation, urbanity is relative in the sense that different places may have gained better or worse adaptation under different conditions. The urbanity process is always shaped by the threat of too much complexity and too little connectivity. Above all, it is a certain surplus of connectivity that characterizes urbanity. This surplus is mapped by the variant of centrality proposed by Christaller. While Christaller's models can be transferred into network sciences frameworks, Christaller does not offer an adequate centrality measure. Therefore, his concept of centrality cannot be transferred correctly without being translated carefully into the network research context. In this article, we argue why this is necessary and explain how it can be done. In this paper the above concept will be applied to the Early Iron Age Princely Seats with a special focus on the Heuneburg. In order to represent similarities and interaction between different nodes a very limited part of the material culture can be used. For this purpose we use fibulae which allow for fairly accurate dating and hence ensure a narrow time slice for the network analysis. Using Fibulae the research will be limited to a certain social segment, which we refer to as "middle class." This paper is intended to deal with the rather complex issue of urbanity using more simple approaches such as network analysis. In this context, we pursue a tight integration of theory and methodology and we consider certain conceptual Nakoinz et al. Iron Age Urbanity issues. This paper has two main results. Firstly, we develop a consistent approach in order to apply social network centrality measures on geographical networks. Secondly, we will analyse which role the above mentioned middle class played in the course of urbanity processes.