RDF has seen increased adoption in recent years, prompting the standardization of the
SPARQL query language for RDF, and the development of local and distributed engines for …

We present SemOpenAlex, an extensive RDF knowledge graph that contains over 26 billion
triples about scientific publications and their associated entities, such as authors, institutions …

Abstract Resource Description Framework (RDF) is increasingly being used to model data
on the web. RDF model was designed to support easy representation and exchange of …

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

The proliferation of semantic data in the form of Resource Description Framework (RDF)
triples demands an efficient, scalable, and distributed storage along with a highly available …

Leveraging Big Data (BD) processing frameworks to process large-scale Resource
Description Framework (RDF) datasets holds a great interest in optimizing query …

We present Strabo 2, a distributed geospatial RDF store able to process GeoSPARQL
queries over massive RDF datasets. Strabo 2 is based on robust technologies, able to scale …

This paper discusses one of the most significant challenges of large-scale RDF data
processing over Apache Spark, the relational schema optimization. The choice of RDF …

The explosion of the web and the abundance of linked data demand effective and efficient
methods for storage, management, and querying. Apache Spark is one of the most widely …

The recent advancements of the Semantic Web and Linked Data have changed the working
of the traditional web. There is a huge adoption of the Resource Description Framework …