In archaeology when experts speak about the use of computers in their work, they are not meaning taking a laptop to the excavation site and typing in digging data. It is true that some archaeologists, maybe the site director along with a few field directors, might take their laptop to the dig but when archaeologists express the use of computers in archaeology it is fairly certain that they are referring to a highly specialised and very limited niche, involving computer-based analytical methods to study human behaviour.
Over the last decade archaeologists have become aware that to harvest the full potential of collected data and archaeological research, they will need to be aware of the pitfalls and limitations of the process of field archaeology and enhance their science by incorporating the emerging discipline of information technology and specifically AI.
The method of taking conventional archaeological data and using it in specially designed computer software applications is known as Computational Archaeology (CA). As it is a rather new branch it sometimes carries other names such as archaeological informatics or archaeoinformatics.
The term, ‘computational archaeology’ is usually reserved for the complex mathematical methods that could be calculated in no other manner but by computer. However, CA is not limited to mathematics. In archaeology, computer software can replicate an entire site, stratum by stratum and rebuild the missing architecture into an interactive, three-dimensional, fly-over movie.
CA might include geographical information systems (when applied to spatial analysis), statistical or mathematical modelling, and simulations of possible human behaviour or habitation. All of these operations would be impossible without the aid of computer processing power.
Archaeological problems of great complexity, both theoretical and applied, have been opened up for resolution by the use of a wide range of computer-based information processing software.
CA can be seen developing in two distinct areas: Theoretical and Applied.
Theoretical Computational Archaeology
This area focuses on research about the structure, possibilities, and properties of archaeological data, its inference across multi-disciplines, and building a greater knowledge base. The theoretical approach includes modelling the foggy uncertainties in archaeological data, arriving at the optimal strategies for sampling, scale effects, and spatio-temporal effects.
Applied Computational Archaeology
This area is devoted to the design, development, and writing of specific computer software and algorithms to make the theoretical knowledge perceptible to the researcher.
Mountains of Archaeological Data
CA provides a high-tech tool to the archaeologist who otherwise could not process the voluminous and complex information stores that archaeology continues to stockpile. Despite the enormous usefulness that computation can provide to modern archaeology, it is often misunderstood and poorly represented.
It Requires a Genius
Digital excavation technology requires multi-skilled experts who are proficient in computer software design and algorithms, applied statistics, algebra, geophysics, geoinformation sciences, and not least, be a highly trained archaeologist.
The UK boasts the largest share of the world’s university placements for the study of quantitative archaeology. CA’s most important forum for students and professionals in artificial intelligence science is the Computer Applications and Quantitative Methods in Archaeology (CAA) conference, held annually in a European country.
Many UK universities offer programmes in artificial intelligence including courses in GIS and special analysis in archaeology, archaeological information systems, landscape archaeology and geomatics, and MSc programmes in archaeological computing. However, archaeological expeditions or universities offer insufficient vocational opportunities to graduates of CA science.
The limitless world of computer graphics imaging (CGI) will have to rest on its shovel while it waits for mainstream archaeology to scrape its trowel into the bits and bytes that the new computational science is offering.