The documentation, dissemination, and enhancement of Cultural Heritage is of great relevance. To that end, technological tools and interactive solutions (e.g., 3D models) have become increasingly popular. Historical silk fabrics are nearly flat objects, very fragile and with complex internal geometries, related to different weaving techniques and types of yarns. These characteristics make it difficult to properly document them, at the yarn level, with current technologies. In this paper, we bring a new methodology to virtually represent such heritage and produce 3D printouts, also making it highly interactive through the tool Virtual Loom. Our work involves sustainability from different perspectives: (1) The traditional production of silk fabrics respects the environment; (2) Virtual Loom allows the studying of silk heritage while avoiding their degradation; (3) Virtual Loom allows creative industries to save money and materials; (4) current research on bioplastics for 3D printing contributes to environmental sustainability; (5) edutainment and gaming can also benefit from Virtual Loom, avoiding the need to acquire the original objects and enhancing creativity. The presented work has been carried out within the scope of the SILKNOW project to show some results and discuss the sustainability issues, from the production of traditional silk fabrics, to their dissemination by means of Virtual Loom and 3D printed shapes.

This paper presents an Artificial Intelligence approach to mining context and emotions related to olfactory cultural heritage narratives, particularly to fairy tales. We provide an overview of the role of smell and emotions in literature, as well as highlight the importance of olfactory experience and emotions from psychology and linguistic perspectives. We introduce a methodology for extracting smells and emotions from text, as well as demonstrate the context-based visualizations related to smells and emotions implemented in a novel smell tracker tool. The evaluation is performed using a collection of fairy tales from Grimm and Andersen. We find out that fairy tales often connect smell with the emotional charge of situations. The experimental results show that we can detect smells and emotions in fairy tales with an F1 score of 91.62 and 79.2, respectively.

The global health situation due to the SARS-COV-2 pandemic motivated an unprecedented contribution of science and technology from companies and communities all over the world to fight COVID-19. In this paper, we present the impactful role of text mining and data analytics, exposed publicly through IRCAI's Coronavirus Watch portal. We will discuss the available technology and methodology, as well as the ongoing research based on the collected data.Povzetek: Opisana je vloga rudarjenja besedil in podatkovne analitike na primeru portala IRCAI's Coronavirus Watch.

Using the Internet and wealth of data and knowledge available on the Web, so-called web observatories have been developed in the last decade—in very different fields of use. The article discusses the use of such observatories to support the implementation of sustainable development at different scales. The focus is on landslides as risk to society, and since they are related to water and soil, a web-based observatory on natural hazards, including landslides, can draw upon water- and soil-related observatories that are used worldwide as a sustainable development tool. A new landslide observatory may support major global initiatives to adapt to climate change. The Observatory’s vision, structure and use can be built upon the experiences gathered by developing a global water observatory for smart water management, using Artificial Intelligence tools. UNESCO Chair on Water-related Disaster Risk Reduction of the University of Ljubljana, Slovenia, and the UNESCO International Research Institute on Artificial Intelligence at the Institute Jožef Stefan, Slovenia, have joined efforts and knowledge to develop a new global web observatory (tentatively first as the Landslide Observatory) to be used by different stakeholders when implementing global climate adaptation policies and relevant European Union strategies. The information gathered on the internet is structured, and shown using geolocators for different regions and/or countries. For interpretation of world-wide web data, landslide expert knowledge is used.