No abstract

This paper proposes an ontological approach to connect the archaeological topographic evidence for movement in the landscape which can be derived from interpretation and spatial analysis of airborne lidar data with models of movement derived from modeling exercises such as Agent Based Modelling or Cost Path Modelling. This computational ontology enables the investigation of movement and its topographic manifestations in the landscape at various spatio-temporal scales. It creates an explicit framework for accessing meaningful information about movement generated through research using both detection and modelling-led approaches. Developing explicit computational frameworks to provide meaningful context is critical, particularly as remote sensing and modelling projects increase in scale and complexity. The process of developing a computational ontology exposes a deeper underlying issue, and one applicable to many topics we address as archaeologists: if we begin to unpack the concept of 'movement' it is readily apparent that it is a complex phenomenon, like many human habits, and studying it requires drawing together a variety of types of physical evidence and multiple, often competing, theoretical models of human processes and practices. If we wish to make archaeological 'data' on movement available, how do we create appropriate contextual information -really useful metadata -so that this data can be incorporated into the variety of studies for which knowledge of movement is relevant? This is essentially the challenge posed broadly by the FAIR principles, and in particular by the principle of interoperability, which suggests that we "use a formal, accessible, shared, and broadly applicable language for knowledge representation". Rather than simply seeking to fulfill the requirements of an arbitrary standard, attempting to meet the challenge of interoperability provides an impetus and opportunity to attempt to bridge the gap between data and model, and to reconsider how we conceive and represent knowledge in archaeological digital data and modelling projects. This kind of computational ontology, we suggest, can serve as the key for making the data from both these sources actually FAIR.

The amount of information available to archaeologists has grown dramatically during the last ten years. The rapid acquisition of observational data and creation of digital data has played a significant role in this “information explosion”. In this paper, we propose new methods for knowledge creation in studies of movement, designed for the present data-rich research context. Using three case studies, we analyze how researchers have identified, conceptualized, and linked the material traces describing various movement processes in a given region. Then, we explain how we construct ontologies that enable us to explicitly relate material elements, identified in the observed landscape, to the knowledge or theory that explains their role and relationships within the movement process. Combining formal pathway systems and informal movement systems through these three case studies, we argue that these systems are not hierarchically integrated, but rather intertwined. We introduce a new heuristic tool, the “track graph”, to record observed material features in a neutral form which can be employed to reconstruct the trajectories of journeys which follow different movement logics. Finally, we illustrate how the breakdown of implicit conceptual references into explicit, logical chains of reasoning, describing basic entities and their relationships, allows the use of these constituent elements to reconstruct, analyze, and compare movement practices from the bottom up.