Data-Driven Chronology in Archaeology (original) (raw)

Data-driven chronology is one of the most exciting and fast-moving developments in archaeological science in recent years. As the logistics of doing fieldwork for primary research becomes ever more problematic, and in many countries the database of results from developer-funded fieldwork grows to an unprecedented size, many workers are 'digging' through 'grey literature' and legacy data in order to uncover new insight about the past. In doing so, new methods have been developed, particularly in statistics, GIS and modelling. Some of these, such as the use of summed radiocarbon, have provoked debate about how much we can read into the patterns of change suggested by the data at face value. Can these methods be used for case studies with short chronological frameworks, and if so, how short? In this session, we explore case studies where new data-driven methods have been applied to archaeological problems, especially in chronology. We invite papers exploring aspects of large radiocarbon databases, papers exploring the value of 'traditional' chronological (e.g. pottery seriation) approaches in today's data-driven world, or other data-rich chronological studies, including methodological advances in statistics, Bayesian modelling and GIS. We seek to open a forum where regional studies especially can be presented, allowing the cross-fertilization of ideas and lively debate. We welcome proposals of papers (of up to 15 minutes) to our session. Please include a paper title and an abstract of between 200 and 300 words, your institutional affiliation and contact details. All submissions to be made online by 15 th February 2018. For further information or enquiries on the session, please contact Rowan McLaughlin (r.mclaughlin@qub.ac.uk) To submit an abstract, or for further information on the EAA Annual Meeting 2018, please visit: www.e-a-a.org/EAA2018/