LEADER 02903nam 2200397 450 001 9910731404503321 005 20230829190542.0 024 7 $a10.1145/3584372 035 $a(CKB)5720000000232620 035 $a(NjHacI)995720000000232620 035 $a(EXLCZ)995720000000232620 100 $a20230829d2023 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPODS '23 $eProceedings of the 42nd ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems /$fFloris Geerts, Hung Q. Ngo, Stavros Sintos 210 1$aNew York, NY :$cAssociation for Computing Machinery,$d2023. 215 $a1 online resource (392 pages) 311 $a979-84-00-70127-6 330 $aIt is our great pleasure to welcome you to the 42nd ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (PODS 2023), held in Seattle, Washington, U.S.A., on June 18th - June 21st, 2023. As usual, PODS is held in conjunction with its sister conference, the 2023 ACM SIGMOD International Conference on Management of Data. Since the first edition of the symposium in 1982, PODS provides a premier annual forum for the communication of new advances in the theoretical foundations of data management. The PODS community aims to provide a solid scientific basis for methods, techniques and solutions for the data management problems that continually arise in our data-driven society. Our goal is to develop solutions that ensure a high level of efficiency, scalability, expressiveness, robustness, flexibility, security, and privacy, among others. In addition, the PODS community is an open space in which researchers from various areas related to the principles of computer science can discuss, interact, and propose solutions to pressing data management problems. PODS papers meet very high-quality standards and are distinguished by a rigorous approach to widely diverse problems in data management, often bringing to bear techniques from a variety of different areas, including computational logic, finite model theory, computational complexity, algorithm design and analysis, programming languages, privacy, statistical theory, and artificial intelligence. In particular, the papers included in this volume present principled contributions to modeling, application, system building, and both theoretical and experimental validation in the context of data management. 606 $aDatabase management$vCongresses 606 $aDatabase management$vSoftware 615 0$aDatabase management 615 0$aDatabase management 676 $a005.7565 700 $aGeerts$b Floris$01404385 702 $aNgo$b Hung Q. 702 $aSintos$b Stavros 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910731404503321 996 $aPODS '23$93478872 997 $aUNINA