Promoting data provenance tracking in the archaeological interpretation process

n this paper we propose a model and a set of derivation rules for tracking data provenance during the archaeological interpretation process. The interpretation process is the main task performed by an archaeologist that, starting from ground data about evidences and findings, tries to derive knowledge about an ancient object or event. In particular, in this work we concentrate on the dating process used by archaeologists to assign one or more time intervals to a finding in order to define its lifespan on the temporal axis and we propose a framework to represent such information and infer new knowledge including provenance of data. Archaeological data, and in particular their temporal dimension, are typically vague, since many different interpretations can coexist, thus we will use Fuzzy Logic to assign a degree of confidence to values and Fuzzy Temporal Constraint Networks to model relationships between dating of different findings