@inproceedings{e4433008fdef4c82a98d30f02a980a1a,
title = "A UML-Style Visual Query Environment Over DBPedia",
abstract = "We describe and demonstrate a prototype of a UML-style visual query environment over DBPedia that allows query seeding with any class or property present in the data endpoint and provides for context-sensitive query growing based on class-to-property and property-to-property mappings. To handle mappings that connect more than 480 thousand classes and more than 50 thousand properties, a hybrid approach of mapping pre-computation and storage is proposed, where the property information for “large” classes is stored in a database, while for “small” classes and for individuals the matching property information is retrieved from the data endpoint on-the-fly. The created schema information is used to back the query seeding and growing in the ViziQuer tool. The schema server and the schema database contents can be re-used also in other applications that require DBPedia class and property linking information.",
keywords = "DBPedia, RDF data schema, SPARQL, Visual queries, ViziQuer",
author = "Kārlis {\v C}erāns and Lelde Lāce and Mikus Grasmanis and Jūlija Ov{\v c}iņņikova",
note = "Publisher Copyright: {\textcopyright} 2022, Springer Nature Switzerland AG.",
year = "2022",
doi = "10.1007/978-3-030-98876-0\_2",
language = "English",
isbn = "9783030988753",
volume = "1537 CCIS",
series = "Communications in Computer and Information Science",
publisher = "Springer",
pages = "16--27",
editor = "Emmanouel Garoufallou and Mar{\'i}a-Antonia Ovalle-Perandones and Andreas Vlachidis",
booktitle = "Metadata and Semantic Research - 15th International Conference, MTSR 2021, Revised Selected Papers",
address = "Germany",
}