Addressing Uncertainty according to the Annotator's Expertise in Archaeological Data Collections: an Approach from Fuzzy Logic

Abstract

Archaeological data allow us to synthetically represent the past of individuals and communities over time. This complex representation task requires an amalgamation of variables and makes the intrinsic data vagueness. The study of vagueness as an archaeological data dimension has become a dynamic focus of archaeologists' work in recent years, presenting theoretical and practical approaches for the representation, mainly with fuzzy logic, of archaeological variables. Vagueness in archaeological data can occur due to different reasons: non-existence of evidence, imprecision, errors, subjectivity, etc. Furthermore, the data is usually managed in groups, shared or recovered for subsequent investigations, so the vagueness traceability that is injected due to these management phases is lost. In this paper we present the ongoing work carried out in modeling under fuzzy formal theory the explicit representation of the expertise of the annotator (understood as the professional who introduces archaeological data into a certain system, giving value to the defined variables) in a decoupled way from the value attributed to each variable. The first experiments with chronological and use variables of the sites show how making the annotator's expertise explicit in the fuzzy model allows maintaining the traceability of the uncertainty injected into the archaeological data due to the definition and management of the datasets by different people, as well as establishes a base for implementing archaeological fuzzy decision-based systems.