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Squerall: Virtual Ontology-Based Access to Heterogeneous and Large Data Sources

: Mami, Mohamed Nadjib; Graux, Damien; Scerri, Simon; Jabeen, Hajira; Auer, Soeren; Lehmann, Jens


Ghidini, C.:
The Semantic Web - ISWC 2019. 18th International Semantic Web Conference. Proceedings. Pt.II : Auckland, New Zealand, October 26-30, 2019
Cham: Springer Nature, 2019 (Lecture Notes in Computer Science 11799)
ISBN: 978-3-030-30795-0 (Print)
ISBN: 978-3-030-30796-7 (Online)
International Semantic Web Conference (ISWC) <18, 2019, Auckland>
European Commission EC
H2020; 776280; BETTER
European Commission EC
H2020; 822404; QualiChain
Fraunhofer IAIS ()

The last two decades witnessed a remarkable evolution in terms of data formats, modalities, and storage capabilities. Instead of having to adapt ones application needs to the, earlier limited, available storage options, today there is a wide array of options to choose from to best meet an applications needs. This has resulted in vast amounts of data available in a variety of forms and formats which, if interlinked and jointly queried, can generate valuable knowledge and insights. In this article, we describe Squerall: a framework that builds on the principles of Ontology-Based Data Access (OBDA) to enable the querying of disparate heterogeneous sources using a unique query language, SPARQL. In Squerall, original data is queried on-the-fly without prior data materialization or transformation. In particular, Squerall allows the aggregation and joining of large data in a distributed manner. Squerall supports out of-the-box five data sources and moreover, it can be programmatically extended to cover more sources and incorporate new query engines. The framework provides user interfaces for the creation of necessary inputs, as well as guiding non-SPARQL experts to write SPARQL queries. Squerall is integrated into the popular SANSA stack and available as open-source software via GitHub and as a Docker image.