With regard to spatial and surface data (points, curves and surfaces) methods derived from geo-statistics, geo-informatics, machine learning and pattern recognition and knowledge discovery are commonly applied. This allows the regionalisation of a variety of archaeological data about landscapes, as for example soil quality, workability, and availability of nutrients.
Besides the regionalisation of punctual and small-regional data, these methods provide relevant information for the analysis of observed processes, such as the changing of soils. This analysis of cause-and-effect complexes within their temporal and spatial frame is a central issue of current archaeological research in general and especially of SFB 1070. During its second phase the research centre explores different kinds of materiality and temporality as resource assemblages. Algorithms are not only used in order to identify relevant cultural and environmental variables and their significant links, but also as a support for the exploration of dynamic processes, for example whether the development of settlement patterns is determined rather by socio-cultural or by natural and environmental conditions, a question of central importance in the work of SFB 1070.
