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  • Döhmen T, Geacu R, Hulsebos M and Schelter S. (2024). SchemaPile: A Large Collection of Relational Database Schemas. Proceedings of the ACM on Management of Data. 2:3. (1-25). Online publication date: 29-May-2024.

    https://doi.org/10.1145/3654975

  • Fang J, Lychagin D, Carey M and Tsotras V. (2023). A new window Clause for SQL++. The VLDB Journal. 10.1007/s00778-023-00830-z. 33:3. (595-623). Online publication date: 1-May-2024.

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  • Zirak F, Choudhury F and Borovica-Gajic R. (2024). SeLeP: Learning Based Semantic Prefetching for Exploratory Database Workloads. Proceedings of the VLDB Endowment. 17:8. (2064-2076). Online publication date: 1-Apr-2024.

    https://doi.org/10.14778/3659437.3659458

  • Francia M, Rizzi S and Marcel P. (2024). Explaining cube measures through Intentional Analytics. Information Systems. 10.1016/j.is.2023.102338. 121. (102338). Online publication date: 1-Mar-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S0306437923001746

  • Tahmasebi S, Payberah A, Soylu A, Roman D and Matskin M. (2023). TRANSQLATION: TRANsformer-based SQL RecommendATION 2023 IEEE International Conference on Big Data (BigData). 10.1109/BigData59044.2023.10386277. 979-8-3503-2445-7. (4703-4711).

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  • Schuler R, Singla J, Vallat B, White K, Berman H and Kesselman C. (2023). Database Evolution, by Scientists, for Scientists: A Case Study 2023 IEEE 19th International Conference on e-Science (e-Science). 10.1109/e-Science58273.2023.10254872. 979-8-3503-2223-1. (1-10).

    https://ieeexplore.ieee.org/document/10254872/

  • Zhao J, Gal A and Krishnan S. Data Makes Better Data Scientists. Proceedings of the Workshop on Human-In-the-Loop Data Analytics. (1-3).

    https://doi.org/10.1145/3597465.3605228

  • Bimonte S, Gallinucci E, Marcel P and Rizzi S. (2022). Logical design of multi-model data warehouses. Knowledge and Information Systems. 65:3. (1067-1103). Online publication date: 1-Mar-2023.

    https://doi.org/10.1007/s10115-022-01788-0

  • Garg S, Mitra S, Yu T, Gadhia Y and Kashettiwar A. Reinforced approximate exploratory data analysis. Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence. (7660-7669).

    https://doi.org/10.1609/aaai.v37i6.25929

  • Dosso D, Davidson S and Silvello G. (2022). Credit distribution in relational scientific databases. Information Systems. 109:C. Online publication date: 1-Nov-2022.

    https://doi.org/10.1016/j.is.2022.102060

  • Vogelsgesang A, Neumann T, Leis V and Kemper A. Efficient Evaluation of Arbitrarily-Framed Holistic SQL Aggregates and Window Functions. Proceedings of the 2022 International Conference on Management of Data. (1243-1256).

    https://doi.org/10.1145/3514221.3526184

  • Aleyasen A, Morcos M, Antova L, Sugiyama M, Korablev D, Patvarczki J, Mutreja R, Duller M, Waas F and Winslett M. Intelligent Automated Workload Analysis for Database Replatforming. Proceedings of the 2022 International Conference on Management of Data. (2273-2285).

    https://doi.org/10.1145/3514221.3526050

  • Kamara S, Kati A, Moataz T, Schneider T, Treiber A and Yonli M. (2022). SoK: Cryptanalysis of Encrypted Search with LEAKER – A framework for LEakage AttacK Evaluation on Real-world data 2022 IEEE 7th European Symposium on Security and Privacy (EuroS&P). 10.1109/EuroSP53844.2022.00014. 978-1-6654-1614-6. (90-108).

    https://ieeexplore.ieee.org/document/9797348/

  • Bimonte S, Gallinucci E, Marcel P and Rizzi S. (2022). Data variety, come as you are in multi-model data warehouses. Information Systems. 104:C. Online publication date: 1-Feb-2022.

    https://doi.org/10.1016/j.is.2021.101734

  • Francia M, Marcel P, Peralta V and Rizzi S. (2021). Enhancing Cubes with Models to Describe Multidimensional Data. Information Systems Frontiers. 24:1. (31-48). Online publication date: 1-Feb-2022.

    https://doi.org/10.1007/s10796-021-10147-3

  • Gubner T, Leis V and Boncz P. (2021). Optimistically Compressed Hash Tables & Strings in theUSSR. ACM SIGMOD Record. 50:1. (60-67). Online publication date: 15-Jun-2021.

    https://doi.org/10.1145/3471485.3471500

  • Marcus R, Negi P, Mao H, Tatbul N, Alizadeh M and Kraska T. Bao: Making Learned Query Optimization Practical. Proceedings of the 2021 International Conference on Management of Data. (1275-1288).

    https://doi.org/10.1145/3448016.3452838

  • Schuler R and Kesselman C. (2021). CHiSEL: a user-oriented framework for simplifing database evolution. Distributed and Parallel Databases. 39:2. (483-543). Online publication date: 1-Jun-2021.

    https://doi.org/10.1007/s10619-020-07314-x

  • Bindschaedler L, Kipf A, Kraska T, Marcus R and Minhas U. (2021). Towards a Benchmark for Learned Systems 2021 IEEE 37th International Conference on Data Engineering Workshops (ICDEW). 10.1109/ICDEW53142.2021.00029. 978-1-6654-4890-1. (127-133).

    https://ieeexplore.ieee.org/document/9438803/

  • Gottlob G, Lanzinger M, Longo D, Okulmus C and Pichler R. The HyperTrac Project: Recent Progress and Future Research Directions on Hypergraph Decompositions. Integration of Constraint Programming, Artificial Intelligence, and Operations Research. (3-21).

    https://doi.org/10.1007/978-3-030-58942-4_1

  • Peralta V, Marcel P, Verdeaux W and Diakhaby A. (2020). Detecting coherent explorations in SQL workloads. Information Systems. 10.1016/j.is.2019.101479. 92. (101479). Online publication date: 1-Sep-2020.

    https://linkinghub.elsevier.com/retrieve/pii/S0306437919305319

  • Mouna M, Bellatreche L and Boustia N. HYRAQ. Proceedings of the 24th Symposium on International Database Engineering & Applications. (1-10).

    https://doi.org/10.1145/3410566.3410582

  • Boncz P, Neumann T and Leis V. (2020). FSST. Proceedings of the VLDB Endowment. 13:12. (2649-2661). Online publication date: 1-Aug-2020.

    https://doi.org/10.14778/3407790.3407851

  • Zolaktaf Z, Milani M and Pottinger R. Facilitating SQL Query Composition and Analysis. Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. (209-224).

    https://doi.org/10.1145/3318464.3380602

  • Gathani S, Lim P and Battle L. Debugging Database Queries: A Survey of Tools, Techniques, and Users. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. (1-16).

    https://doi.org/10.1145/3313831.3376485

  • Gubner T, Leis V and Boncz P. (2020). Efficient Query Processing with Optimistically Compressed Hash Tables & Strings in the USSR 2020 IEEE 36th International Conference on Data Engineering (ICDE). 10.1109/ICDE48307.2020.00033. 978-1-7281-2903-7. (301-312).

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  • Atzeni P, Bugiotti F, Cabibbo L and Torlone R. (2020). Data modeling in the NoSQL world. Computer Standards & Interfaces. 67:C. Online publication date: 1-Jan-2020.

    https://doi.org/10.1016/j.csi.2016.10.003

  • Huang S, Xu L, Liu J, Elmore A and Parameswaran A. (2019). DB: bolt-on versioning for relational databases (extended version). The VLDB Journal — The International Journal on Very Large Data Bases. 29:1. (509-538). Online publication date: 1-Jan-2020.

    https://doi.org/10.1007/s00778-019-00594-5

  • Ramjit L, Interlandi M, Wu E and Netravali R. Acorn. Proceedings of the ACM Symposium on Cloud Computing. (206-219).

    https://doi.org/10.1145/3357223.3362702

  • Schuler R and Kessleman C. A High-level User-oriented Framework for Database Evolution. Proceedings of the 31st International Conference on Scientific and Statistical Database Management. (157-168).

    https://doi.org/10.1145/3335783.3335787

  • Fischl W, Gottlob G, Longo D and Pichler R. HyperBench. Proceedings of the 38th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems. (464-480).

    https://doi.org/10.1145/3294052.3319683

  • Djedaini M, Drushku K, Labroche N, Marcel P, Peralta V and Verdeaux W. (2022). Automatic assessment of interactive OLAP explorations. Information Systems. 82:C. (148-163). Online publication date: 1-May-2019.

    https://doi.org/10.1016/j.is.2018.06.008

  • Young M, Rodriguez L, Keller E, Sun F, Sa B, Whittington J and Howe B. Beyond Open vs. Closed. Proceedings of the Conference on Fairness, Accountability, and Transparency. (191-200).

    https://doi.org/10.1145/3287560.3287577

  • Mustard C and Fedorova A. (2018). Practical Cross Program Memoization with KeyChain 2018 IEEE International Conference on Big Data (Big Data). 10.1109/BigData.2018.8622210. 978-1-5386-5035-6. (262-271).

    https://ieeexplore.ieee.org/document/8622210/

  • Savva F, Anagnostopoulos C and Triantafillou P. (2018). Explaining Aggregates for Exploratory Analytics 2018 IEEE International Conference on Big Data (Big Data). 10.1109/BigData.2018.8621953. 978-1-5386-5035-6. (478-487).

    https://ieeexplore.ieee.org/document/8621953/

  • Schuler R and Kesselman C. Towards an efficient and effective framework for the evolution of scientific databases. Proceedings of the 30th International Conference on Scientific and Statistical Database Management. (1-4).

    https://doi.org/10.1145/3221269.3221300

  • Vogelsgesang A, Haubenschild M, Finis J, Kemper A, Leis V, Muehlbauer T, Neumann T and Then M. Get Real. Proceedings of the Workshop on Testing Database Systems. (1-6).

    https://doi.org/10.1145/3209950.3209952

  • Seabolt E, Kandogan E and Roth M. Contextual Intelligence for Unified Data Governance. Proceedings of the First International Workshop on Exploiting Artificial Intelligence Techniques for Data Management. (1-9).

    https://doi.org/10.1145/3211954.3211955

  • Ping H, Stoyanovich J and Howe B. DataSynthesizer. Proceedings of the 29th International Conference on Scientific and Statistical Database Management. (1-5).

    https://doi.org/10.1145/3085504.3091117

  • Stoyanovich J, Howe B, Abiteboul S, Miklau G, Sahuguet A and Weikum G. Fides. Proceedings of the 29th International Conference on Scientific and Statistical Database Management. (1-6).

    https://doi.org/10.1145/3085504.3085530

  • Wasay A, Wei X, Dayan N and Idreos S. Data Canopy. Proceedings of the 2017 ACM International Conference on Management of Data. (557-572).

    https://doi.org/10.1145/3035918.3064051

  • Djedaini M, Labroche N, Marcel P and Peralta V. (2017). Detecting User Focus in OLAP Analyses. Advances in Databases and Information Systems. 10.1007/978-3-319-66917-5_8. (105-119).

    https://link.springer.com/10.1007/978-3-319-66917-5_8

  • Wesley R and Xu F. (2016). Incremental computation of common windowed holistic aggregates. Proceedings of the VLDB Endowment. 9:12. (1221-1232). Online publication date: 1-Aug-2016.

    https://doi.org/10.14778/2994509.2994537