Data lakes are becoming increasingly prevalent for Big Data management and data
analytics. In contrast to traditional 'schema-on-write'approaches such as data warehouses …

Data federation addresses the problem of uniformly accessing multiple, possibly
heterogeneous data sources, by map** them into a unified schema, such as an RDF …

A large number of datasets are being made available on the Web using a variety of formats
and according to diverse data models. Ontology Based Data Integration (OBDI) has been …

In recent years, data lakes emerged as a way to manage large amounts of heterogeneous
data for modern data analytics. One way to prevent data lakes from turning into inoperable …

The last two decades witnessed a remarkable evolution in terms of data formats, modalities,
and storage capabilities. Instead of having to adapt one's application needs to the, earlier …

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 …

ABSTRACT A data lake (DL), abbreviated as DL, denotes a vast reservoir or repository of
data. It accumulates substantial volumes of data and employs advanced analytics to …

Data lakes have emerged as a pivotal solution for managing vast amounts of unstructured
and structured data, offering unparalleled scalability and flexibility. This article delves into …

Increasing data volumes have extensively increased application possibilities. However,
accessing this data in an ad hoc manner remains an unsolved problem due to the diversity …

Data lakes are storage repositories that contain large amounts of data in its native format;
either structured ssemi-structured or unstructured, to be used when needed. Data lakes are …