Abstract
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 limited, available storage options, today there is a wide array of options to choose from to best meet an application’s 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.
Software Framework. https://eis-bonn.github.io/Squerall.
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Notes
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We used queue data structure simply to be able to dynamically pull (unqueue) elements from it iteratively till it has no more elements.
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Available at https://github.com/EIS-Bonn/Squerall (Apache-2.0 license).
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URL: http://purl.org/db/nosql, details are out of the scope of this article.
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The 1.5M scale factor generates 500M RDF triples, and the 5M factor 1,75B triples.
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Acknowledgment
This work is partly supported by the EU H2020 projects BETTER (GA 776280) and QualiChain (GA 822404); and by the ADAPT Centre for Digital Content Technology funded under the SFI Research Centres Programme (Grant 13/RC/2106) and co-funded under the European Regional Development Fund.
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Mami, M.N., Graux, D., Scerri, S., Jabeen, H., Auer, S., Lehmann, J. (2019). Squerall: Virtual Ontology-Based Access to Heterogeneous and Large Data Sources. In: Ghidini, C., et al. The Semantic Web – ISWC 2019. ISWC 2019. Lecture Notes in Computer Science(), vol 11779. Springer, Cham. https://doi.org/10.1007/978-3-030-30796-7_15
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