The H2IOSC project aims to establish a federated cluster of European distributed research infrastructures involved in the humanities and cultural heritage sectors, with operating nodes across Italy. Through four key RIs—DARIAH-IT, CLARIN, OPERAS, and E-RIHS—the project promotes collaboration among researchers with interdisciplinary expertise. Within this framework, DIGILAB functions as the digital access platform for the Italian node of E-RIHS. Conceived as a socio-technical infrastructure for the Heritage Science community, DIGILAB is designed to manage heterogeneous data and metadata through advanced knowledge graph representations. The platform adheres to the FAIR principles and supports the complete data lifecycle, enabling the development and maintenance of Heritage Digital Twins. DIGILAB integrates diverse categories of information related to cultural sites and objects, encompassing historical and artistic datasets, diagnostic analyses, 3D models, and real-time monitoring data. This monitoring capability is achieved through the deployment of cutting-edge Internet of Things (IoT) technologies and large-scale Wireless Sensor Networks (WSNs). As part of DIGILAB, we developed SENNSE (v1.0), a fully open hardware/software platform dedicated to environmental and structural monitoring. SENNSE allows the remote, real-time observation and control of cultural heritage sites (collecting microclimatic parameters such as temperature, humidity, noise levels) and of cultural objects (collecting object-specific data including vibrations, light intensity, and ultraviolet radiation). The visualization and analytical tools integrated within SENNSE transform these datasets into actionable insights, thereby supporting advanced research and conservation strategies within the Cultural Heritage domain. In the following sections, we provide a detailed description of the SENNSE platform, outlining its hardware components and software modules, and discussing its benefits. Furthermore, we illustrate its application through two representative use cases: one conducted in a controlled laboratory environment and another implemented in a real-world heritage context, exemplified by the “Biblioteca Bernardini” in Lecce, Italy.

The H2IOSC project aims to create a federated cluster of research infrastructures (RIs) in the domain of Cultural Heritage at the national level in Italy. Through four key Ris — DARIAH-IT, CLARIN, OPERAS, and E-RIHS — the project enables collaboration among researchers with interdisciplinary expertise. Within this context, DIGILAB emerges as a digital access platform for the Italian node of E-RIHS, providing data management, digital tools, and services to boost cultural heritage preservation, fruition, and study. A significant aspect of DIGILAB architecture is its capability to support geo-localization and real-time monitoring of cultural heritage sites in terms of environmental conditions, structural integrity, and diagnostics, leveraging on novel Internet of Things (IoT) systems and large-scale Wireless Sensor Networks (WSNs). By integrating WSNs into DIGILAB framework, the project enhances remote monitoring and control of cultural sites. These networks facilitate the collection of real-time data on factors such as temperature, humidity, and air quality, providing crucial insights for the Cultural Heritage research community. Moreover, WSNs enable proactive measures to be taken in response to emerging threats, mitigating risks and minimizing damage to cultural assets at a national level.

In this article, we present an approach designed to extend the metadata schema of the Zenodo data management platform to strengthen the FAIRness of the published dataset. We focus on a bottom-up approach starting from a series of datasets ranging from the 3D digitalisation of monuments and sites to the creation of reconstructive records (including the scientific documentation they are based on), to the implementation of digital storytelling and to the development of open source-based web-apps. We propose the simplest possible set of metadata to be included in the Zenodo platform with the possibility, for the community, to adopt and further develop/modify them. This article will describe in detail the formalisation and the digital formats adopted providing the related metadata templates developed within the projects.

The rise of the Internet of Things (IoT) has revolutionised environmental monitoring, enhancing comfort, energy efficiency, and sustainability across indoor and outdoor spaces. However, preventive conservation in cultural heritage still lacks real-time monitoring and predictive capabilities. This paper presents SENNSE, an IoT-driven platform designed to support the monitoring, management, and preservation of cultural heritage sites and artefacts. SENNSE integrates wireless sensor networks with cloud-based analytics to enable real-time data collection, processing, and automated environmental control. The platform’s architecture spans multiple network layers, from sensing hardware to cloud services and dashboard-based data visualisation. We deployed SENNSE in a case study involving three indoor scenarios: semi-confined, closed, and open spaces. Key environmental parameters such as temperature, humidity, and light intensity were monitored to assess microenvironmental conditions. Using machine learning, SENNSE analysed sensor data to extract insights on workspace activity, including office hours, thermal comfort, meeting frequency, and energy use. For office activity detection, the model identified working and non-working periods with 95% training accuracy, 89% test accuracy, 0.99 precision, and 0.86 recall, demonstrating the predictive power of temporal and environmental data. To minimise manual intervention, SENNSE includes features such as over-the-air updates, configurable thresholds, system notifications, and automated email alerts. By integrating IoT technology with preventive conservation strategies, SENNSE offers a robust framework for real-time monitoring and long-term protection of cultural heritage.