Why-Not Provenance

Our work on Why-Not provenance focuses on theory and algorithms to explain why some tuples are not part of a query result, even though developers or users expected them to be. For flat relational data, we have developed various algorithms producing instance-based explanations, query-based explanations, and hybrid explanations. We are currently researching why-not provenance for nested data. 

Acknowledgements. Prior to joining the University of Stuttgart, work related to Why-Not provenance has been partly funded by IBM Research, the Eliteprogramm für Postdoktorandinnen und Postdoktoranden der Baden-Würrtemberg Stiftung, and an AAP Grant of Université Paris Sud.

Publications

  1. Diestelkamper, R., Lee, S., Glavic, B., & Herschel, M. (2021). Debugging Missing Answers for Spark Queries over Nested Data with Breadcrumb. Proceedings of the VLDB Endowment (PVLDB). http://www.vldb.org/pvldb/vol14/p2731-diestelkamper.pdf
  2. Diestelkämper, R., Lee, S., Herschel, M., & Glavic, B. (2021). To not miss the forest for the trees - A holistic approach for explaining missing answers over nested data. In Proceedins of the ACM SIG Conference on the Management of Data (SIGMOD). https://dl.acm.org/doi/pdf/10.1145/3448016.3457249
  3. Diestelkämper, R., Glavic, B., Herschel, M., & Lee, S. (2019). Query-based Why-not Explanations for Nested Data. Proceedings of the International Workshop on Theory and Practice of Provenance (TaPP). https://www.usenix.org/conference/tapp2019/presentation/diestelkamper
  4. Bidoit, N., Herschel, M., & Tzompanaki, K. (2016). Refining SQL Queries based on Why-Not Polynomials. 8th USENIX Workshop on the Theory and Practice of Provenance, TaPP 2016, Washington, D.C., USA, June 8-9, 2016. https://www.usenix.org/conference/tapp16/workshop-program/presentation/bidoit
  5. Bidoit, N., Herschel, M., & Tzompanaki, K. (2015). EFQ: why-not answer polynomials in action. Proceedings of the VLDB Endowment (PVLDB), 8(12), Article 12. http://dblp.uni-trier.de/db/journals/pvldb/pvldb8.html#BidoitHT15
  6. Bidoit, N., Herschel, M., & Tzompanaki, K. (2015). Immutably answering Why-Not questions for equivalent conjunctive queries. Ingénierie Des Systèmes d’information, 20(5), Article 5. https://doi.org/10.3166/isi.20.5.27-52
  7. Herschel, M. (2015). A hybrid approach to answering why-not questions on relational query results. Journal of Data and Information Quality, 5(3), Article 3. http://dblp.uni-trier.de/db/journals/jdiq/jdiq5.html#Herschel15
  8. Bidoit, N., Herschel, M., & Tzompanaki, A. (2015). Efficient computation of polynomial explanations of why-not questions. In J. Bailey, A. Moffat, C. C. Aggarwal, M. de Rijke, R. Kumar, V. Murdock, T. K. Sellis, & J. X. Yu (Eds.), CIKM’15 (pp. 713–722). Association for Computing Machinery. https://doi.org/10.1145/2806416.2806426
  9. Bidoit, N., Herschel, M., & Tzompanaki, K. (2014). Immutably Answering Why-Not Questions for Equivalent Conjunctive Queries. TAPP. http://dblp.uni-trier.de/db/conf/tapp/tapp2014.html#BidoitHT14
  10. Bidoit, N., Herschel, M., & Tzompanaki, K. (2014). Query-Based Why-Not Provenance with NedExplain. In S. Amer-Yahia, V. Christophides, A. Kementsietsidis, M. N. Garofalakis, S. Idreos, & V. Leroy (Eds.), EDBT (pp. 145–156). OpenProceedings.org. http://dblp.uni-trier.de/db/conf/edbt/edbt2014.html#BidoitHT14
  11. Herschel, M. (2013). Wondering why data are missing from query results?: ask conseil why-not. In Q. He, A. Iyengar, W. Nejdl, J. Pei, & R. Rastogi (Eds.), CIKM (pp. 2213–2218). ACM. http://dblp.uni-trier.de/db/conf/cikm/cikm2013.html#Herschel13
  12. Herschel, M., & Hernández, M. A. (2010). Explaining Missing Answers to SPJUA Queries. PVLDB, 3(1), Article 1. http://dblp.uni-trier.de/db/journals/pvldb/pvldb3.html#HerschelH10
  13. Herschel, M., Hernández, M. A., & Tan, W. C. (2009). Artemis: A System for Analyzing Missing Answers. Proceedings of the VLDB Endowment, 2(2), Article 2. https://doi.org/10.14778/1687553.1687588
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