Computational approaches have become commonplace during the last decades and are now routinely employed in most areas of archaeological research and practice. They permeate most archaeological research and not just that for which computer-based analytical methods are a necessity. Field data collection for example, which includes both archaeological survey and excavation, have been implementing important improvements based on new digital technologies and slowly move from an application focused on recording methods to an analytical use of computational approaches.
Despite its enormous contribution to archaeological research and practice computational archaeology is still difficult to pin down with a definition given its wide application and the multiplicity of approaches it encompasses. From statistics to simulation and modelling passing through network analysis, remote sensing and GIS computational archaeology includes a wide diversity of fields. Many of these fields are still poorly represented in archaeology undergraduate degrees and only a handful of universities offer postgraduate degrees providing training on several of these approaches.
At GIAP we focus on geosciences (remote sensing and GIS), the application of machine and deep learning to archaeological questions, geostatistics and 3D reconstruction and modelling but some of our members are experienced with network analysis and simulation.