Interpretable Visual Exploration of Archaeological Signs

The study of archaeological signs and non-verbal markings requires navigating complex relationships between artefacts, symbolic forms, and contextual metadata. While digital heritage platforms increasingly provide cataloguing and metadata services, they still offer limited support for visual exploration and comparison, particularly when signs are small, spatially unconstrained, and embedded within deteriorated artefacts. This paper presents the International Etruscan Sigla Project (IESP), an integrated visual heritage system that combines structured cataloguing, intelligent document-based knowledge extraction, and AI-assisted visual similarity retrieval within a unified archaeological exploration environment. Rather than introducing these capabilities as independent tools, IESP supports the complete archaeological workflow, from knowledge acquisition and catalogue navigation to image-based exploration and comparative analysis. The system stores and models artefacts and sign elements, automatically extracts structured information from publicly available archaeological documents, and enables similarity-driven exploration through a dual-encoder architecture specifically designed for fine-grained comparison of archaeological signs. The proposed retrieval strategy aligns global sign representations with spatial feature maps extracted from artefact images, enabling similarity-based retrieval while preserving the local visual evidence required for archaeological interpretation. Users can interact with the system through multiple retrieval modalities, including sketch-based queries, image-based sign retrieval, and support-based exploration. The paper also presents the system's software architecture and reports the results of an expert-centred user study conducted through realistic archaeological tasks. The evaluation combines task performance, usability, cognitive workload, technology acceptance, and qualitative observations, demonstrating that the proposed interaction paradigm effectively supports archaeological exploration while preserving human interpretation and scholarly transparency. Overall, IESP demonstrates how integrating structured knowledge management, document understanding, and interpretable AI can transform digital heritage repositories into interactive environments that actively support archaeological research and visual analysis.