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Query-based Why-not Explanations for Nested Data, , , and . Proceedings of the International Workshop on Theory and Practice of Provenance (TaPP), USENIX Association, (2019)Tracing nested data with structural provenance for big data analytics, and . Proceedings of the International Conference on Extending Database Technology (EDBT), page 253-264. (2020)A survey on provenance: What for? What form? What from?, , and . VLDB journal, 26 (6): 881-906 (2017)Distributed Tree-Pattern Matching in Big Data Analytics Systems, and . In Proceedings of the Conference on Advances in Databases and Information Systems (ADBIS), page 171-186. Springer, (2020)Capturing and Querying Structural Provenance in Spark with Pebble, and . Proceedings of the 2019 International Conference on Management of Data, page 1893-1896. New York, Association for Computing Machinery, (2019)Explaining existing and missing results over nested data in big data analytics systems. Universität Stuttgart, Stuttgart, Dissertation, (2021)Research Data Management Project Form. Dataset, (2019)To not miss the forest for the trees - A holistic approach for explaining missing answers over nested data, , , and . In Proceedings of the ACM SIG Conference on the Management of Data (SIGMOD), (2021)Provenance in DISC Systems: Reducing Space Overhead at Runtime, , and . Proceedings of the USENIX Conference on Theory and Practice of Provenance (TAPP), page 1-13. (2017)Debugging Missing Answers for Spark Queries over Nested Data with Breadcrumb, , , and . Proceedings of the VLDB Endowment (PVLDB), (2021)