{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,5]],"date-time":"2026-09-05T01:09:46Z","timestamp":1788570586911,"version":"build-2803163510"},"reference-count":49,"publisher":"Association for Computing Machinery (ACM)","issue":"11","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2018,7]]},"abstract":"<jats:p>\n            SQL declaratively specifies\n            <jats:italic>what<\/jats:italic>\n            the desired output of a query is. This work shows that a non-standard interpretation of the SQL semantics can, instead, disclose\n            <jats:italic>where<\/jats:italic>\n            a piece of the output originated in the input and\n            <jats:italic>why<\/jats:italic>\n            that piece found its way into the result. We derive such data provenance for very rich SQL dialects---including recursion, windowed aggregates, and user-defined functions---at the fine-grained level of individual table cells. The approach is non-invasive and implemented as a compositional source-level SQL rewrite: an input SQL query is transformed into its own interpreter that wields data dependencies instead of regular values. We deliberately design this transformation to preserve the shape of both data and query, which allows provenance derivation to scale to complex queries without overwhelming the underlying database system.\n          <\/jats:p>","DOI":"10.14778\/3236187.3236204","type":"journal-article","created":{"date-parts":[[2018,9,10]],"date-time":"2018-09-10T12:12:28Z","timestamp":1536581548000},"page":"1536-1549","source":"Crossref","is-referenced-by-count":9,"title":["You say 'what', i hear 'where' and 'why'"],"prefix":"10.14778","volume":"11","author":[{"given":"Tobias","family":"M\u00fcller","sequence":"first","affiliation":[{"name":"Universit\u00e4t T\u00fcbingen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Benjamin","family":"Dietrich","sequence":"additional","affiliation":[{"name":"Universit\u00e4t T\u00fcbingen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Torsten","family":"Grust","sequence":"additional","affiliation":[{"name":"Universit\u00e4t T\u00fcbingen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2018,7]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2723372.2742797"},{"key":"e_1_2_1_2_1","volume-title":"GProM---A Swiss Army Knife for Your Provenance Needs","author":"Bahareh S.","year":"2018","unstructured":"S. Bahareh , S. Feng , B. Glavic , S. Lee , X. Niu , and Q. Zeng . GProM---A Swiss Army Knife for Your Provenance Needs . IEEE Data Engineering Bulletin , 41(1), 2018 . S. Bahareh, S. Feng, B. Glavic, S. Lee, X. Niu, and Q. Zeng. GProM---A Swiss Army Knife for Your Provenance Needs. IEEE Data Engineering Bulletin, 41(1), 2018."},{"key":"e_1_2_1_3_1","volume-title":"Proc. VLDB","author":"Benjelloun O.","year":"2006","unstructured":"O. Benjelloun , A. Sarma , A. Halevy , and J. Widom . ULDBs: Databases with Uncertainty and Lineage . In Proc. VLDB , Seoul, Korea , 2006 . O. Benjelloun, A. Sarma, A. Halevy, and J. Widom. ULDBs: Databases with Uncertainty and Lineage. In Proc. VLDB, Seoul, Korea, 2006."},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-04936-6_5"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1412331.1412340"},{"key":"e_1_2_1_6_1","volume-title":"Tan. Why and Where: A Characterization of Data Provenance. In Proc. ICDT","author":"Buneman P.","year":"2001","unstructured":"P. Buneman , S. Khanna , and W.- C. Tan. Why and Where: A Characterization of Data Provenance. In Proc. ICDT , London, UK , 2001 . P. Buneman, S. Khanna, and W.-C. Tan. Why and Where: A Characterization of Data Provenance. In Proc. ICDT, London, UK, 2001."},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/spe.2325"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1559845.1559901"},{"key":"e_1_2_1_9_1","unstructured":"J. Cheney. Program Slicing and Data Provenance. IEEE Data Engineering Bulletin 2007 30 4"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0960129511000211"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2643135.2643143"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1561\/1900000006"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.14778\/2994509.2994530"},{"key":"e_1_2_1_14_1","volume-title":"Proc. VLDB","author":"Cui Y.","year":"2001","unstructured":"Y. Cui and J. Widom . Lineage Tracing for General Data Warehouse Transformations . In Proc. VLDB , Rome, Italy , 2001 . Y. Cui and J. Widom. Lineage Tracing for General Data Warehouse Transformations. In Proc. VLDB, Rome, Italy, 2001."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/357775.357777"},{"key":"e_1_2_1_16_1","volume-title":"Proc. EDBT","author":"Dietrich B.","year":"2016","unstructured":"B. Dietrich , T. M\u00fcller , and T. Grust . The Best Bang for Your Bu(ck)g---When SQL Debugging and Data Provenance Go Hand in Hand . In Proc. EDBT , Bordeaux, France , 2016 . B. Dietrich, T. M\u00fcller, and T. Grust. The Best Bang for Your Bu(ck)g---When SQL Debugging and Data Provenance Go Hand in Hand. In Proc. EDBT, Bordeaux, France, 2016."},{"key":"e_1_2_1_17_1","volume-title":"Proc. CIDR","author":"Fan J.","year":"2015","unstructured":"J. Fan , A. Gerald , S. Raj , and J. Patel . The Case Against Specialized Graph Analytics Engines . In Proc. CIDR , Asilomar, CA, USA , 2015 . J. Fan, A. Gerald, S. Raj, and J. Patel. The Case Against Specialized Graph Analytics Engines. In Proc. CIDR, Asilomar, CA, USA, 2015."},{"key":"e_1_2_1_18_1","volume-title":"Science of Computer Programming","author":"Fehrenbach S.","year":"2017","unstructured":"S. Fehrenbach and J. Cheney . Language-Integrated Provenance . Science of Computer Programming , 2017 . S. Fehrenbach and J. Cheney. Language-Integrated Provenance. Science of Computer Programming, 2017."},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2213836.2213908"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2009.15"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/1516360.1516472"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/1516360.1516472"},{"key":"e_1_2_1_24_1","series-title":"Lecture Notes in Computer Science, 8000","volume-title":"Using SQL for Efficient Generation and Querying of Provenance Information","author":"Glavic B.","year":"2013","unstructured":"B. Glavic , R. Miller , and G. Alonso . Using SQL for Efficient Generation and Querying of Provenance Information . Lecture Notes in Computer Science, 8000 , 2013 . B. Glavic, R. Miller, and G. Alonso. Using SQL for Efficient Generation and Querying of Provenance Information. Lecture Notes in Computer Science, 8000, 2013."},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/1265530.1265535"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/2445583.2445586"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.14778\/2367502.2367510"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-003-0106-0"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-017-0486-1"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/258948.258964"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/234528.234749"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.5555\/645390.651624"},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/1807167.1807269"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/0306-4379(92)90008-B"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2011.5767867"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.14778\/2824032.2824089"},{"key":"e_1_2_1_37_1","volume-title":"Proc. BTW","author":"Neumann T.","year":"2015","unstructured":"T. Neumann and A. Kemper . Unnesting Arbitrary Queries . In Proc. BTW , Hamburg, Germany , 2015 . T. Neumann and A. Kemper. Unnesting Arbitrary Queries. In Proc. BTW, Hamburg, Germany, 2015."},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.14778\/3137765.3137793"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2017.104"},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2827074"},{"key":"e_1_2_1_41_1","volume-title":"Proc. TaPP","author":"O'Grady D.","year":"2018","unstructured":"D. O'Grady , T. M\u00fcller , and T. Grust . How 'How' Explains What 'What' Computes---How-Provenance for SQL and Query Compilers . In Proc. TaPP , London, UK , 2018 . D. O'Grady, T. M\u00fcller, and T. Grust. How 'How' Explains What 'What' Computes---How-Provenance for SQL and Query Compilers. In Proc. TaPP, London, UK, 2018."},{"key":"e_1_2_1_42_1","volume-title":"Proc. VLDB","author":"Ramasamy K.","year":"2000","unstructured":"K. Ramasamy , J. Patel , J. Naughton , and R. Kaushik . Set Containment Joins: The Good, the Bad, and the Ugly . In Proc. VLDB , Cairo, Egypt , 2000 . K. Ramasamy, J. Patel, J. Naughton, and R. Kaushik. Set Containment Joins: The Good, the Bad, and the Ugly. In Proc. VLDB, Cairo, Egypt, 2000."},{"key":"e_1_2_1_43_1","volume-title":"ISO\/IEC 9075-2","author":"Foundation Database","year":"2016","unstructured":"Database Languages-SQL-Part 2: Foundation . ISO\/IEC 9075-2 : 2016 . Database Languages-SQL-Part 2: Foundation. ISO\/IEC 9075-2:2016."},{"key":"e_1_2_1_44_1","volume-title":"Provenance in Databases: Past, Present, and Future","author":"Tan W.-C.","year":"2007","unstructured":"W.-C. Tan . Provenance in Databases: Past, Present, and Future . IEEE Data Engineering Bulletin , 32(4), 2007 . W.-C. Tan. Provenance in Databases: Past, Present, and Future. IEEE Data Engineering Bulletin, 32(4), 2007."},{"key":"e_1_2_1_45_1","volume-title":"CWI","author":"Tip F.","year":"1994","unstructured":"F. Tip . A Survey of Program Slicing Techniques. Technical report , CWI , Amsterdam , The Netherlands , 1994 . F. Tip. A Survey of Program Slicing Techniques. Technical report, CWI, Amsterdam, The Netherlands, 1994."},{"key":"e_1_2_1_46_1","unstructured":"The TPC Benchmark H. tpc.org\/tpch. The TPC Benchmark H . tpc.org\/tpch."},{"key":"e_1_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/22952.22955"},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/99370.99404"},{"key":"e_1_2_1_49_1","volume-title":"Proc. VLDB","author":"Wang Y.","year":"1990","unstructured":"Y. Wang and S. Madnick . A Polygen Model for Heterogeneous Database Systems: The Source Tagging Perspective . In Proc. VLDB , Brisbane, Australia , 1990 . Y. Wang and S. Madnick. A Polygen Model for Heterogeneous Database Systems: The Source Tagging Perspective. In Proc. VLDB, Brisbane, Australia, 1990."},{"key":"e_1_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.1984.5010248"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3236187.3236204","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T09:47:42Z","timestamp":1672220862000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3236187.3236204"}},"subtitle":["(mis-)interpreting SQL to derive fine-grained provenance"],"short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":49,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2018,7]]}},"alternative-id":["10.14778\/3236187.3236204"],"URL":"https:\/\/doi.org\/10.14778\/3236187.3236204","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2018,7]]}}}