ABSTRACT
Within archaeology, datasets that could be truly classed as ‘Big Data’ in the sense used by most of the hard sciences do not yet exist. However, our datasets are becoming increasingly large and complex as more and more data is generated (primarily) by commercial projects. If we define ‘Big Data’ in this context as datasets that are too large to be collated and analysed without automated methods (within budget constraints), then we are beginning to see archaeological spatial analysis brush up against the shores of Big Data analytics. Within archaeology, these datasets fall broadly within two camps: (a) those with immense numbers of records but with simple numeric attributes (e.g. point clouds generated by LiDAR); and (b) those with lower numbers of records but complex numeric and textual attributes (e.g. catalogues of discoveries at national or international scales). This chapter is primarily concerned with the latter and will discuss methods which can be used to study these complex large datasets in their spatial context, using examples taken from the English Landscapes and Identities project which ended in 2016.
