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Detecting Linked Data Quality Issues via Crowdsourcing: A DBpedia Study, , , , , и . Semantic Web Journal, (2016)PLANET: Query Plan Visualizer for Shipping Policies against Single SPARQL Endpoints., , , , и . ISWC (Posters & Demos), том 1272 из CEUR Workshop Proceedings, стр. 189-192. CEUR-WS.org, (2014)HARE: An Engine for Enhancing Answer Completeness of SPARQL Queries via Crowdsourcing., , , и . WWW (Companion Volume), стр. 501-505. ACM, (2018)whoVIS: Visualizing Editor Interactions and Dynamics in Collaborative Writing Over Time., и . WWW (Companion Volume), стр. 191-194. ACM, (2015)WikiWho: precise and efficient attribution of authorship of revisioned content., и . WWW, стр. 843-854. ACM, (2014)Triple Pattern Join Cardinality Estimations over HDT with Enhanced Metadata., , , и . SEMANTiCS (Posters & Demos), том 2451 из CEUR Workshop Proceedings, CEUR-WS.org, (2019)teepee - A Triple Pattern Fragment Profiler Visualization Tool., и . ISWC (P&D/Industry/BlueSky), том 2180 из CEUR Workshop Proceedings, CEUR-WS.org, (2018)Networks of Linked Data Eddies: An Adaptive Web Query Processing Engine for RDF Data., и . ISWC (1), том 9366 из Lecture Notes in Computer Science, стр. 111-127. Springer, (2015)Diefficiency Metrics: Measuring the Continuous Efficiency of Query Processing Approaches., , и . ISWC (2), том 10588 из Lecture Notes in Computer Science, стр. 3-19. Springer, (2017)A Hybrid Approach to Perform Efficient and Effective Query Execution Against Public SPARQL Endpoints.. WWW (Companion Volume), стр. 469-473. ACM, (2015)