(SOAS University of London, London, UK)

Keywords: Data mining mortuary analysis Turfan

This research analyses mortuary variability in the Turfan Basin (Xinjiang, P.R. China) to understand the motivation for using niche graves in this area. The strength of the methodology is the bottom-up approach to data mining. The data are collected and fed into a mySQL database at the lowest possible level, so that these basic analytical units can be aggregated at any moment to the level needed. This will make it possible to look at the data from multiple perspectives, views or paradigms. Ultimately, this case study illustrates how quantitative or statistical approaches can be used to enhance a critical attitude towards data collection, data mining and data analysis.
This methodology will allow a combination of deductive and (true) inductive reasoning: pre-defined questions can be addressed and new ones can be generated. Three main pre-defined questions are: 1) Do the early niche graves in the Turfan Basin represent an innovation introduced by immigrants, or are they rather the result of a local development in tomb architecture? 2) What motivated the use of niche graves in the Turfan Basin? 3) If the niche graves in the Turfan Basin represent a type introduced from outside, how can they be linked to similar practices in other regions? The ultimate question is whether the research category ‘niche grave’ is significant at all?
It is my ambition that this research will serve as a data mining model for future research in this area that will make it possible to 1) standardise the collection of ‘big data’; 2) simplify comparative intrasite and intersite analysis, and finally 3) generate new research questions while maintaining a critical attitude towards the data.