Graph databases capture richly linked domain knowledge by integrating heterogeneous
data and metadata into a unified representation. Here, we present the use of bespoke …

In the last years, virtual exhibitions have been widely adopted to enhance traditional
museums and enable active interaction with culture without posing any physical constraints …

With the rapid development of artificial intelligence, knowledge graphs have been widely
recognized as a critical component in many AI techniques and systems. A complex …

Abstract Ontology and Knowledge Graph (KG) are two hotspot topics in Semantic Web and
Artificial Intelligence (AI) fields. They have gained their importance due to the thriving …

Last years witnessed a shift from the potential utility in digitisation to a crucial need to enjoy
activities virtually. In fact, before 2019, data curators recognised the utility of performing data …

Biomedical knowledge graphs (BKGs) have emerged as powerful tools for organizing and
leveraging the vast and complex data found across the biomedical field. Yet, current reviews …

Abstract Knowledge graphs denote structured data which represent entities and
relationships between them in a form of a graph, often expressed in the RDF data model. It …

The integration of external knowledge graphs has emerged as a powerful approach to
enrich conversational AI systems with coherent and knowledge-rich conversations. This …

Abstract Knowledge Graphs are a critical source for Question Answering, but their potential
may be threatened due to the complexity of their query languages, such as SPARQL. On the …

The growing availability of (linked) open data requires lay users to master how to deal with
data effectively, yet SPARQL presents a barrier to leveraging data represented as …