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 …

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 …

Purpose Massive amounts of data, manifesting in various forms, are being produced on the
Web every minute and becoming the new standard. Exploring these information sources …

With the advancement of Semantic Technologies, large geospatial data sources have been
increasingly published as Linked data on the Web. The LinkedGeoData project is one of the …

In designing a distributed RDF system, it is quite common to divide an RDF graph into
subgraphs, called partitions, which are then distributed. Graph partitioning in general and …

The last decades have witnessed significant advancements in terms of data generation,
management, and maintenance. This has resulted in vast amounts of data becoming …

Abstract Knowledge Graphs (KGs) integrate heterogeneous data, but one challenge is the
development of efficient tools for allowing end users to extract useful insights from these …

This paper presents DistRDF2ML, the generic, scalable, and distributed framework for
creating in-memory data preprocessing pipelines for Spark-based machine learning on RDF …

With the high proportion of electrical and electronic devices in China's power grids, massive
graph data of power distribution equipment has been accumulated to share the knowledge …

Scaling-out RDF processing to deal with graph size usually requires partitioning the RDF
graph. Typical partitioning approaches minimize edge-cuts or vertex-cuts. In this paper we …