The amount of multilingual data on the Web proliferates; therefore, develo** ontologies in
various natural languages is attracting considerable attention. In order to achieve semantic …

Processing large-scale and highly interconnected Knowledge Graphs (KG) is becoming
crucial for many applications such as recommender systems, question answering, etc …

Currently, a large amount of spatial and spatiotemporal RDF data has been shared and
exchanged on the Internet and various applications. Resource Description Framework …

Analytical queries are queries with numerical aggregators: computing the average number
of objects per property, identifying the most frequent subjects, etc. Such queries are …

As the availability and the inter-connectivity of RDF datasets grow, so does the necessity to
understand the structure of the data. Understanding the topology of RDF graphs can guide …

Computing dataset statistics is crucial for exploring their structure, however, it becomes
challenging for large-scale datasets. This has several key benefits, such as link target …

Nowadays, ontologies are used in various application areas, involving Artificial Intelligence,
Natural Language Processing, Data Integration, and Knowledge Management. It is essential …

The topological structure of RDF graphs inherently differs from other types of graphs, like
social graphs, due to the pervasive existence of hierarchical relations (TBox), which …

Due to the increasing progress of digitization, immense amounts of data are accumulating,
which can be summarized under the term Big Data and form an exciting basis for data …

Over the past decade, vast amounts of machine-readable structured information have
become available through the automation of research processes as well as the increasing …