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

The digital transformation of companies has led to the evolution of databases towards Big
Data. Our work is part of this context and concerns more particularly the mechanisms to …

Ontology-based data access (OBDA) is a well-established approach to information
management which facilitates the access to a (single) relational data source through the …

In recent years, topics like (advanced) data analytics and data science have been constantly
gaining popularity in research and business domains (Cerquitelli et al. 2020; Romero et al …

With the diverse applications to industry and domain-specific context, multi-source
information extraction on semi-structured and unstructured data, as well as across data …

With data's evolution in terms of volume, variety, and velocity, Information Systems (IS)
administrators have to steadily adapt their data model and choose the best solution (s) to …

Data science applications increasingly rely on heterogeneous data sources and analytics.
This has led to growing interest in polystore systems, especially analytical polystores. In this …

The adoption of document stores, such as MongoDB or CouchDB, has increased drastically
in recent years. Part of this popularity can certainly be explained by their flexibility in loading …

Hybrid complex analytics workloads typically include (i) data management tasks (joins,
selections, etc.), easily expressed using relational algebra (RA)-based languages, and (ii) …

Data analytics applications today often require processing heterogeneous data from
different data models, including relational, graph, and text data, for more holistic analytics …