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Squerall: virtual ontology-based access to heterogeneous and large data sources

, , , , , and . International Semantic Web Conference, page 229--245. Springer, (2019)

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Querying Interlinked Data by Bridging RDF Molecule Templates., , , , , and . T. Large-Scale Data- and Knowledge-Centered Systems, (2018)How to feed the Squerall with RDF and other data nuts?, , , , , and . Proceedings of 18th International Semantic Web Conference - Poster & Demos, (2019)The Query Translation Landscape: a Survey, , , , , and . CoRR, (2019)Semantic Data Integration for the SMT Manufacturing Process Using SANSA Stack., , , , and . ESWC (Satellite Events), volume 12124 of Lecture Notes in Computer Science, page 307-311. Springer, (2020)Strategies for a Semantified Uniform Access to Large and Heterogeneous Data Sources.. University of Bonn, Germany, (2021)How to Feed the Squerall with RDFand Other Data Nuts?, , , , , and . Proceedings of the ISWC 2019 Satellite Tracks (Posters & Demonstrations, Industry, and Outrageous Ideas) co-located with 18th International Semantic Web Conference (ISWC 2019), (2019)STATisfy Me: What are my Stats?, , , and . ISWC 2018 Poster and Demos, (2018)DistLODStats: Distributed Computation of RDF Dataset Statistics., , , and . ISWC (2), volume 11137 of Lecture Notes in Computer Science, page 206-222. Springer, (2018)Querying Data Lakes using Spark and Presto., , , , and . WWW, page 3574-3578. ACM, (2019)Squerall: virtual ontology-based access to heterogeneous and large data sources, , , , , and . International Semantic Web Conference, page 229--245. Springer, (2019)