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GProM - A Swiss Army Knife for Your Provenance Needs., , , , , and . IEEE Data Eng. Bull., 41 (1): 51-62 (2018)PUG: a framework and practical implementation for why and why-not provenance., , and . VLDB J., 28 (1): 47-71 (2019)Debugging Missing Answers for Spark Queries over Nested Data with Breadcrumb, , , and . Proceedings of the VLDB Endowment (PVLDB), (2021)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)Adaptive Schema Databases., , , , , , , , , and 2 other author(s). CIDR, www.cidrdb.org, (2017)Debugging Transactions and Tracking their Provenance with Reenactment., , , , , , , , and . PVLDB, 10 (12): 1857-1860 (2017)Provenance Summaries for Answers and Non-Answers., , and . PVLDB, 11 (12): 1954-1957 (2018)Query-based Why-not Explanations for Nested Data, , , and . Proceedings of the International Workshop on Theory and Practice of Provenance (TaPP), USENIX Association, (2019)Efficiently Computing Provenance Graphs for Queries with Negation., , , and . CoRR, (2017)PUG: A Framework and Practical Implementation for Why & Why-Not Provenance (extended version)., , and . CoRR, (2018)