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This paper presents the Story Map Building and Visualizing Tool (SMBVT), a sofware that allows users to create and visualise semantic story maps using a user-friendly web interface. The tool uses Wikidata as external reference knowledge base and exploits Semantic Web technologies in the back-end system to represent stories modelled on the Narrative ontology, a CRM-based vocabulary for representing narratives. SMBVT is entirely open-source and accessible afer free registration.

Digital Libraries (DLs) are full of narratives. Besides its richness, DLs services often retrieve narrative components, but not the narratives as a whole. To formally represent this knowledge and to create and visualize narratives the Digital Humanities group of ISTI-CNR has developed the Narrative Ontology (NOnt) and the Narrative Building and Visualising Tool (NBVT). In this context, my research aims to investigate the possibility to introduce the geospatial dimension of narratives in NOnt. Moreover, my research aims to extend the functionalities of NBVT to enrich the narratives with geospatial information. As a case study, I have chosen to create narratives about mountain ecosystems and economic value chains produced within the Mountain Valorization through Interconnectedness and Green Growth (MOVING) European project (2020-2023). Currently, my research is still at an early stage and I have started to conduct a state-of-the-art study of the geospatial and spatiotemporal RDF/S representation techniques. Eventually, I will evaluate the extension of NOnt.

Maps have always stimulated people's imagination and spatiotemporally supported storytelling; however, they cannot alone represent the life and emotions associated with the territories they describe. Story maps are an IT solution to enrich maps with such information. They are online applications enriched with multimedia and textual information that tell map-based stories. Current software for story map building is either commercial or requires advanced IT skills that make it hardly used by environmental experts. This deliverable describes the Story Map Building and Visualizing Tool (SBVMT), an open-source and free-to-use tool to build and publish story maps, which overcomes common drawbacks of other software by operating within the open-science e-Infrastructure (D4Science) used in the MOVING Project. SBVMT includes new features such as an ontology to represent story maps, Semantic Web technologies for data representation, automatic connection to Wikidata, secure multi-user collaboration in story building, and visualisation of the narrative either as a story map or a timeline. This deliverable shows how SBVMT can overcome the perceptual gap between territory and map. We evaluated its usability and effectiveness from both the point of view of experts building the story map and users interacting with it. Using SMBVT we created the story maps related to the MOVING selected regions. Furthermore, exploiting the semantic web technologies, we implemented several SPARQL queries that allow linking different stories and discovering new knowledge.

The Artificial Intelligence for Media and Humanities laboratory (AIMH) has the mission to investigate and advance the state of the art in the Artificial Intelligence field, specifically addressing applications to digital media and digital humanities, and taking also into account issues related to scalability. This report summarize the 2022 activities of the research group.

The image of the world created by the Medieval and Renaissance culture was crucial to the development of Western thought in European history. To the best of our knowledge Medieval and Renaissance geographical works have not been studied using digital methods. The three years (2020-2023) Italian National research project IMAGO - Index Medii Aevi Geographiae Operum - aims at providing a systematic overview of this literature using Semantic Web technologies. As the first step to develop tools to support scholars in creating, evolving and consulting a knowledge base (KB) of the geographical works, we created an OWL 2 DL ontology. Following the re-use logic and to maximize the interoperability, we developed the ontology as an extension of two reference ontologies, that is the CIDOC CRM vocabulary and its extension FRBRoo, including its in-progress reformulation, LRMoo. In this paper, we present the project, the ontology and the tool to populate it that we developed. Furthermore, we present a preliminary study to map the works collected in the IMAGO KB and the manuscripts stored in the KB of the Mapping Manuscript Migrations project.

The Artificial Intelligence for Media and Humanities laboratory (AIMH) has the mission to investigate and advance the state of the art in the Artificial Intelligence field, specifically addressing applications to digital media and digital humanities, and taking also into account issues related to scalability. This report summarize the 2021 activities of the research group.

In this paper, we present the Hypermedia Dante Network (HDN) project. First, we briefly introduce the relevant state of the art on Dante's commentaries and their digital representation, and we outline the project goals. In the main section, we present the core features of the HDN ontology, an evolution of the DanteSources ontology that aims at representing knowledge about Dante's primary sources as they are identified by a vast range of commentaries. Then, we describe the tool that has been developed to process Dante's commentaries and populate the HDN ontology. Finally, we comment on the project's usability and possible outcomes for both scholars and common users.

Annual Report of the Artificial Intelligence for Media and Humanities laboratory (AIMH) research activities in 2020.