Experiential Observations: an Ontology Pattern-based Study on Capturing the Potential Content within Evidences of Experiences

Modelling the knowledge behind human experiences is a complex process: it should take into account, among others, the activities performed, human observations, and the documentation of the evidence. To represent this knowledge in a declarative way means to support data interoperability in the context of cultural heritage artefacts, as linked datasets on experience documentation have started to appear. With this objective in mind, we describe a study based on an Ontology Design Pattern for modelling experiences through observations, which are considered indirect evidence of a mental process (i.e., the experience). This pattern highlights the structural differences between types of experiential documentation, such as diaries and social media, providing a guideline for the comparability between different domains and for supporting the construction of heterogeneous datasets based on an epistemic compatibility. We have performed not only a formal evaluation over the pattern, but also an assessment through a series of case studies. This approach includes a) the analysis of interoperability among two case studies (reading through social media and historical sources); b) the development of an ontology for collecting evidences of reading, which reuses the proposed pattern; and c) the inspection of experience in humanities datasets

Integration strategy and tool between formal ontology and graph database technology

Ontologies, and especially formal ones, have traditionally been investigated as a means to formalize an application domain so as to carry out automated reasoning on it. The union of the terminological part of an ontology and the corresponding assertional part is known as a Knowledge Graph. On the other hand, database technology has often focused on the optimal organization of data so as to boost efficiency in their storage, management and retrieval. Graph databases are a recent technology specifically focusing on element-driven data browsing rather than on batch processing. While the complementarity and connections between these technologies are patent and intuitive, little exists to bring them to full integration and cooperation. This paper aims at bridging this gap, by proposing an intermediate format that can be easily mapped onto the formal ontology on one hand, so as to allow complex reasoning, and onto the graph database on the other, so as to benefit from efficient data handling

How to access ancient landscapes? Field survey and legacy data integration for research on Greek and Roman settlement patterns in Eastern Sicily

The integration of field survey data from Eastern Sicily (the Plain of Catania) with legacy data avai- lable for the region will expand our knowledge on Mediterranean ancient rural landscapes. With an extent of 430 km2, the area is a perfect case study due to its geographical unity and the number of archaeological projects (both excavations and surveys) carried out within it in recent decades. Indeed, combining data from earlier research projects with new archaeological survey data allows us to conduct a settlement pattern analysis of the project’s study area. Heterogenous datasets have been integrated throu- gh their implementation into a geo-database, featuring the management and integration of topographical units and archaeological entities through semantic relations. Through geospatial data analysis based on the complete gazetteer of archaeological sites (whether sherd scatters, ruins, caves dwellings, tombs or tracks), a new image of rural landscapes for this area of Eastern Sicily from the Greek Archaic to the Late Roman Age can be visualized, beyond the traditional Sicilia frumentaria narrative

Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020

On behalf of the Program Committee, a very warm welcome to the Seventh Italian Conference on Computational Linguistics (CLiC-it 2020). This edition of the conference is held in Bologna and organised by the University of Bologna. The CLiC-it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after six years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges