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Not only ecosystems are particularly sensitive to extreme weather as a result of climate change. Historical buildings, museum’s collections and historical gardens can also be affected by extreme weather conditions. Assessing the extent to which cultural assets are endangered by such weather and climate events is an interdisciplinary task that requires the collaboration of climate scientists together with cultural heritage managers, monument conservators, restorers and engineers. However, this discussion is currently hardly taking place in Germany, both on a scientific and on policy levels.Therefore, the BMBF-funded project KERES addresses the following questions:What safety risks of our cultural heritage are caused by extreme weather events? Which practical solutions need to be addressed and managed the current and emerging impacts of climate change on cultural assets in Germany? In close cooperation with the relevant stakeholders and potential users, such as the Prussian Palaces and Gardens Foundation (SPSG), Fraunhofer IOSB is building a web-based knowledge platform that combines the research results and best practices for adaptation and mitigation measures of the historical buildings and historical parks property. This aims to create the greatest possible degree of user orientation so that the knowledge platform can be used sustainably in the long term. This platform is able to collect and integrate multisource information in order to effectively provide complete and updated situational awareness and decision support for innovative measurements improving cultural heritage resilience, in particular new solutions for maintenance and conservation. It is based on the open source; easily configurable and extendable. It can be accessed by the wide range of users via the web interface.Several levels of data integration, aggregation and linking are aggregated:integration of expert knowledge, connection of sensors for comprehensive monitoring and reporting,data analysis of complex processes with an open interface for easy integration of new algorithms,semantic and geographic linking of analysis data and multiple domain information. The backbone of this information network is an ontology, which connects the data of the different domains, like cultural heritage, climate change, environmental data, crisis management, regulations, sensor data management, buildings, materials and many more. The platform is flanked by two other applications, such as a planning tool for the evacuation of art objects:This is a tool for creating route maps for the fire brigade to evacuate cultural objects. The decision-maker supports finding individual measures against damage caused by climate change. The applications for preventive and reactive measures to deal with potential or acute damage situations are examined as well. The designed methods are tested for five case studies including historical buildings and historical gardens in Germany.

The intensity and frequency of extreme weather events in Europe are one of the most dangerous consequences of a warming climate. Some regions suffer more under heat waves and droughts, while others are experiencing extreme rainfalls. Thus, for example, a severe flood in July 2021 in several European countries caused widespread damages particularly in Belgium and Germany.Which extreme weather events are to be expected in the future? How can the damage of irretrievable historical sites be avoided or, at least, limited or dealt with? All these questions are addressed in the three-year research project KERES, which is funded by the German Federal Ministry of Education and Research (BMBF) and is coordinated by the Fraunhofer ISC together with the Fraunhofer EU Office in Brussels.As first step the regional relevance of future extreme weather events in Germany will be investigated. This information will be further used to estimate the potential damages to buildings and outdoor facilities. The precautionary and responsive measures to manage potential or acute damage situations will be investigated as well. The designed methodologies will be tested for five case studies including World Heritage Sites (historical buildings and historical gardens) in Germany.The major tools of KERES include building component and indoor climate simulations and high-resolution urban climate models. The necessary input will be taken from the most recent ensemble of regional climate change projections of the EURO-CORDEX Initiative (www.euro-cordex.net). As a result, an ontology-based information system will be designed for managing the expected damage situations.We will present first results from the KERES project. The discussion will be focused on how to access and visualize the robustness of projected changes of extreme weather events in a way oriented to individual cultural heritage sites.

Industrial Internet of Things (IIoT) applications are being used more and more frequently. Data collected by various sensors can be used to provide innovative digital services supporting increasing efficiency or cost reduction. The implementation of such applications requires the integration and analysis of heterogeneous data coming from a broad variety of sensors. To support these steps, this paper introduces OPAL, a software toolbox consolidating several software components for the semantically annotated integration and analysis of IoT-data. Data storage is realized in a standardized and INSPIRE-compliant way utilizing the SensorThings API. Supporting a broad variety of use cases, OPAL provides several import adapters to access data sources with various protocols (e.g., the OPC UA protocol, which is often used in industrial environments). In addition, a unified management and execution environment, called PERMA, is introduced to allow the programming language independent integration of algorithms.

Climate change (CC) will morph the environmental landscape, thus leading to climate stress imposed on Cultural Heritage (CH). Especially, tangible CH, like castles, palaces, monuments and churches as well as gardens are exposed to CH effects. Such effects are heat waves, flooding, higher sea level, just to name a few.The management and preservation of such CH buildings and whole sites, particularly in the context of CC, is a complex task in which authorities and decision makers need to aggregate and oversee information from diverse sources and domains. Yet, only by considering all relevant and available information, stakeholders can make well-grounded decisions. This imposes a complex task upon the authorities, not only due to the diversity and heterogeneity, but also to the quantity of available data.Only if the current and future situation of the CH in focus is understood, strategies for protecting them can be developed.The first challenge is to apply different kind of sensors to the buildings and gardens to collect data about the weather (temperature, precipitation, etc.), the situation of walls incl. cracks and the state of plants. After that, this data needs to be managed and made accessible in homogeneous way for further processing and analysis.The domain of smart city research faces the exact same problems. Sensors are applied all over the city for example about traffic, infrastructure, air and water quality and weather data. In contrast to CH the community is much larger and the industry is involved as well.Therefore, it is beneficial to look into technologies developed for smart cities and analyze how they can be applied to the monitoring of CH sites. For retrieving, managing and processing sensor data there are open standards evolving, for example the SensorThings API standard by the Open Geospatial Consortium (OGC). Currently, many tools evolve around such standards from which some are available as open source.First results of successfully applying these technologies from different CH and smart city projects will be presented.

Understanding the current situation is critical in every natural disaster or crisis. Therefore, there is a need for accurate and up-to-date information about the scope, extent and impact of a disaster. The basis for this information is data that is available through a variety of sensors. Decision Support Systems (DSSs) support decision makers in disaster management, response, and recovery by providing early warnings, insights into the current situation and recommendations for mitigation actions. For this purpose, raw sensor data needs to be collected, analyzed, integrated, and its semantics need to be automatically understood by the system. This series of processes forms a generic sensor to decision chain. In this paper, we present solutions and technologies to integrate those steps seamlessly, also demonstrating how each step of the pipeline can be visualized.