More and more data in various formats are integrated into knowledge graphs. However,
there is no overview of existing approaches for generating knowledge graphs from …

Abstract Knowledge graphs are often constructed from heterogeneous data sources, using
declarative rules that map them to a target ontology and materializing them into RDF. When …

RDF knowledge graphs (KG) are powerful data structures to represent factual statements
created from heterogeneous data sources. KG creation is laborious and demands data …

Data has exponentially grown in the last years, and knowledge graphs constitute powerful
formalisms to integrate a myriad of existing data sources. Transformation functions–specified …

Building and publishing knowledge graphs (KG) as Linked Data, either on the Web or in
private companies, has become a relevant and crucial process in many domains. This …

A large amount of data is available in tabular form. RML is commonly used to declare how
such data can be transformed into RDF. However, RML presents limitations that lead, in …

Abstract Ontology-Based Data Access (OBDA) has traditionally focused on providing a
unified view of heterogeneous datasets (eg, relational databases, CSV and JSON files) …

In this era of information where everything is digital, data tends to be ubiquitous. Data
Analytics is a term that covers all the areas that deal with the logical analysis of raw data …

Purpose A huge amount of diverse data is generated in the Internet of Things (IoT) because
of heterogeneous devices like sensors, actuators, gateways and many more. Due to …

Highly-heterogeneous and fast-arriving large amounts of data, otherwise said Big Data,
induced the development of novel Data Management technologies. In this paper, the …