The TRIQUETRA project seeks to establish an evidence-based assessment platform for precise risk assessment. Functioning as a Decision Support Tool, this platform aims to enhance efficiency in risk mitigation and site remediation. The TRIQUETRA project's overall approach is structured around three key elements: (i) Risk Identification, (ii) Risk Quantification, and (iii) Risk Mitigation. Within this framework, a novel Knowledge Base Platform (KBP) has been created, serving as an electronic repository equipped with advanced search tools and capabilities. It encompasses information on Climate Change (CC), geological, historical, and site-specific data, along with risks and mitigation measures for Cultural Heritage (CH) sites based on the verified data, geographical identification and results obtained from the outputs of the project. The primary goal of the KBP is to comprehensively integrate and visualize all shared project data, utilizing both a searchable literature database and a sophisticated WebGIS platform that adheres to the standards set by the Open Geospatial Consortium (OGC) and INSPIRE. It also incorporates various features for the deployment, cataloguing and categorisation of the data produced and shared within the project, to enhance the discoverability of the data. The KBP is structured based on two distinct key components, namely the Bibliography inventory and the WebGIS. These distinct sections of the platform gather all the data and information related to the pilot CH sites of the project. The combination of available datasets for each pilot site leads to the creation of a data cube - a multidimensional structure facilitating the efficient representation and analysis of data across various dimensions, including time and location. It is imperative to point out that the platform will keep evolving throughout the course of the project in order to align with upcoming project outputs, enabling the fusion of different data types and efficient research on each pilot CH site. This, in turn, contributes to advancing knowledge in CH monitoring and facilitating optimal preservation and risk mitigation actions.
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Kontopoulos et al. (2024) studied this question.
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