Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data
Bibliographic record
Abstract
We are delighted to welcome you to SIGMOD 2014, the 2014 edition of the ACM SIGMOD International Conference on Management of Data, at Snowbird, Utah, in the Rocky Mountains of the United States. Snowbird is a mountain ski and summer resort. Many attractions, parks, and recreational areas -- including the Yellowstone, Zion, Bryce Canyon, Capitol Reef, Great Basin, Canyonlands, and Arches national parks -- are within a day's drive. The mountain scenery of Snowbird is also adjacent to the urban environment of Salt Lake City. SIGMOD 2014 hosts an exciting technical program, with two keynote talks, by Maurice Herlihy (Brown University) and Eric Sedlar (Oracle Labs); a panel session on Should we all be teaching 'Intro to Data Science' instead of 'Intro to Databases'?, by Bill Howe (University of Washington), Michael Franklin (University of California, Berkeley), Juliana Freire (New York University), James Frew (University of California, Santa Barbara), Tim Kraska (Brown University), and Raghu Ramakrishnan (Microsoft Corporation); an industrial panel on Are We Experiencing a Big Data Bubble?, by Fatma Ozcan (IBM Almaden Research Center), Daniel Abadi (Yale University), Marcel Kornacker (Cloudera), C Mohan (IBM Almaden Research Center), Karthik Ramasamy (Twitter), and Janet Wiener (Facebook, Inc. ); 107 research paper presentations; 6 tutorials; 30 demonstrations; and 15 industrial presentations selected from among 44 submissions. In addition to having 25-minute presentation slots, research papers are included in one of two Research Plenary Poster Sessions. One of these sessions is jointly for PODS and SIGMOD research papers, to deepen the ties between the two conferences. SIGMOD 2014 includes several technical and social events designed specifically for student attendees. The SIGMOD/PODS 2014 Ph.D. Symposium, the Undergraduate Research Poster Competition, and the New Researcher Symposium are all established components of the SIGMOD program and are all part of SIGMOD 2014. The conference also hosts a session dedicated to highlighting the finalists of the SIGMOD Programming Contest. (This year's task is to implement a multidimensional, high-throughput, in-memory indexing system.) In addition, the conference includes a Sponsor Session for our industry partners to present the cool things they have done and introduce career opportunities in industry. This helps bring student attendees together with our Gold, Platinum, and Diamond sponsors. A vis-a-vis meeting aimed at helping Ph.D. students meet internationally recognized researchers in their research areas, will also be organized to exchange ideas and receive guidance in a relaxed social setting. We are immensely grateful to the many researchers who have shaped the conference program. In particular, we thank the Keynotes Chair Gustavo Alonso (ETH Zurich), the Panels Chairs Susan Davidson (University of Pennsylvania) and Sunita Sarawagi (IIT Bombay), the Tutorial Chairs Chris Jermaine (Rice University) and Yufei Tao (Chinese University of Hong Kong), the Industrial Program Chairs Fatma Ozcan (IBM Almaden) and Nesime Tatbul (Intel Labs and MIT), together with the 13 members of the Industrial Program Committee, the Demonstrations Chairs Wolfgang Lehner (Technische Universitat Dresden) and Bettina Kemme (McGill University), together with the 53 members of the Demonstration Program Committee, the Workshops Chair Anastasia Ailamaki (EPFL), the Undergraduate Research Program Chairs Mario Nascimento (University of Alberta) and Anastasios Kementsietsidis (IBM TJ Watson Laboratories), the New Researcher Symposium Chairs Anish Das Sarma (Google Research) and Alexandra Meliou (University of Massachusetts, Amherst). We also express our enormous gratitude to the 13 Program Committee coordinators, Lei Chen (Hong Kong University of Science and Technology), Michael Franklin (University of California, Berkeley), Alfons Kemper (Technical University of Munich), Laks Lakshmanan (University of British Columbia), Ioana Manolescu (Inria Saclay), Tova Milo (Tel Aviv University), Elke Rundensteiner (Worcester Polytechnic Institute), Ken Salem (University of Waterloo), Dennis Shasha (New York University), Divesh Srivastava (AT&T Labs-Research), Kian-Lee Tan (National University of Singapore), Patrick Valduriez (Inria Sophia- Antipolis Mediterranee), and Xiaokui Xiao (Nanyang Technological University) along with the 111 members of the SIGMOD 2014 Program Committee. This year we had two submission cycles for SIGMOD research papers -- one in mid-September and the second one in mid-December. We received 421 research paper submissions across two cycles. As usual, each paper was reviewed by at least three program committee members, followed by a discussion led by the area coordinators. We followed a review process that resembles journal reviewing -- papers went through multiple rounds of reviews until a final decision was taken. Out of 421 submissions, 29 were directly accepted, 102 went through a major revision process, and 290 were rejected. Out of the 102 that went through a major revision 56 were accepted, a further 22 were accepted following a third round of minor revisions, and 24 were rejected. Since the review process resembled journal-style, the acceptance rates are also similar to top journals. We also acknowledge all members of the SIGMOD 2014 organizing committee, as well as the SIGMOD Executive Committee, for invaluable help and guidance throughout the many months leading to the conference. The strong organizing team for SIGMOD 2014 includes proceedings chairs Xiang Lian (University of Texas - Pan American) and Florin Rusu (University of California Merced), finance chair Nikolaus Augsten (University of Salzburg), publicity chairs Guoliang Li (Tsinghua University) and Ashwin Machanavajjhala (Duke University), social media chair Ming Hua (Facebook), sponsorship chairs Yi Chen (New Jersey Institute of Technology) and Nick Koudas (University of Toronto), exhibit chairs Rui Zhang (University of Melbourne) and Peixiang Zhao (Florida State University), local arrangements chair Ryan Johnson (University of Toronto), registration chairs Tingjian Ge (University of Massachusetts, Lowell) and Gabriel Ghinita (University of Massachusetts, Boston), demonstration and workshop local arrangement chair Jeff Phillips (University of Utah), web chairs Huiping Cao (New Mexico State University) and Bin Yao (Shanghai Jiao Tong University), travel award committee chairs Alexandra Meliou (University of Massachusetts, Amherst) and Cong Yu (Google Research), and programming contest chairs Sam Madden (MIT) and Jeong-Hyon Hwang (University of Albany). The success of this conference is impossible without their hard work and persistent dedication. K. Selcuk Candan deserves special thanks for providing us with his advice and SIGMOD institutional memory, as well as for his help with logistics throughout the conference planning. We are also grateful to the Microsoft Research Conference Management Toolkit (CMT) team for their extremely prompt and helpful support throughout the complex conference reviewing process. (We used CMT for the submission and reviewing of research papers, demonstrations, and industrial presentations.) We also extend our appreciation to the student volunteers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.110 | 0.093 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".