VLDB 2019: Call for Contributions - Research Track
VLDB 2019 invites submissions of original research papers to Volume 12 of the Proceedings of the VLDB Endowment (PVLDB). Papers accepted by June 15, 2019 will form the Research Track of the 2019 VLDB conference, together with any rollover papers from Volume 11. Papers accepted to Volume 12 after June 15, 2019 will be rolled over to the 2020 VLDB conference.
The annual VLDB conference is a premier annual international forum for database researchers, vendors, practitioners, application developers, and users. PVLDB, established in 2008, is a scholarly journal for short and timely research papers, with a journal-style review and quality assurance process. PVLDB is distinguished by a monthly submission process with rapid reviews. PVLDB issues are published regularly throughout the year. Your paper will appear in PVLDB soon after acceptance, and possibly in advance of the VLDB conference. All papers accepted in time will be published in PVLDB Vol. 12 and also presented at the VLDB 2019 conference. At least one author of every accepted paper is expected to attend the VLDB 2019 conference.
PVLDB is the only submission channel for research papers to appear in the VLDB 2019 conference. Please see the submission guidelines for paper submission instructions. The submission process for other VLDB 2019 tracks is different, and is described in their respective calls for papers.
Please refer to the link below for details on the PVLDB publication policy:
http://www.vldb.org/pvldb/policies/PVLDB Publication Policies.pdf
PVLDB welcomes original research papers on a broad range of topics related to all aspects of data management. The themes and topics listed below are intended to serve primarily as indicators of the kinds of data-centric subjects that are of interest to PVLDB - they do not represent an exhaustive list.
- Access Methods, Concurrency Control, Recovery, Transactions, Indexing and Search, In-memory Data Management, Hardware Accelerators, Query Processing and Optimization, Storage Management.
- Privacy and Security in Data Management.
- Graph Data Management, Social Networks, Recommendation Systems.
- Data Mining and Analytics, Warehousing.
- Crowdsourcing, Embedded and Mobile Databases, Real-time Databases, Sensors and IoT, Stream Databases.
- Data Models and Query Languages, Schema Management and Design, Database Usability, User Interfaces and Visualization.
- Tuning, Benchmarking, Performance Measurement, Database Administration and Manageability.
- Distributed Database Systems, Cloud Data Management, NoSQL, Scalable Analytics, Distributed Transactions, Consistency, P2P and Networked Data Management, Database-as-a-Service, Content Delivery Networks.
- Provenance and Workflows, Spatial, Temporal, and Multimedia Databases, Scientific and Medical Data Management, Profile-based or Context-Aware Data Management.
- Data Cleaning, Information Filtering and Dissemination, Information Integration, Metadata Management, Data Discovery, Web Data Management, Semantic Web, Heterogeneous and Federated Database Systems.
- Fuzzy, Probabilistic and Approximate Databases, Information Retrieval, Text in Databases.
In addition to traditional research papers, PVLDB welcomes thought provoking papers that fall under the following special categories within the research track:
Experiment and Analysis Papers
These papers focus on the evaluation of existing algorithms, data structures, and systems that are of wide interest. The scientific contribution of an E&A track paper lies in providing new insights into the strengths and weaknesses of existing methods rather than providing new methods. Some examples of types of papers suitable for the Experiment and Analysis category are:
- Experimental surveys that compare existing solutions to a problem and, through extensive experiments, provide a comprehensive perspective on their strengths and weaknesses, or
- papers that verify or refute results published in the past and that, through a renewed performance evaluation, help to advance the state of the art, or
- papers that discuss the development or use of open resources (including data or metadata, benchmarks, evaluation tools, or other resources) that benefit the research community or evaluation of research ideas, or
- papers that focus on relevant problems or phenomena and through analysis and/or experimentation provide insights on the nature or characteristics of these phenomena.
We encourage authors of accepted E&A papers, at the time of the publication, to make available all the experimental data and, whenever possible, the related software. For papers that identify negative or contradictory results for published results by third parties, the Program Committee may ask the third party to comment on the submission and even request a short rebuttal/explanation to be published along with the submission in the event of acceptance.
Innovative Systems and Applications Papers
These papers describe novel architectures for data systems, and non-obvious lessons learned in their application. The details of design goals (e.g., the class of workload to be supported), systems architecture, new abstractions, and design justifications are expected. Papers in this category make a major contribution to the field but do not meet typical criteria for a research paper. In particular, this is the right category for an overview paper of a significant system, particular aspects of which may have been explored in greater detail in previous publications.
Systems papers come in many flavors. They may describe the design issues and architecture of a complete system, or focus on specific issues, such as storage, query processor, indexes, transaction management of a system, or extension of an open source for certain applications not well supported, or address specific performance issues, such as algorithms designed to exploit new hardware (multi core, SIMD, NUMA, HTM, SGX, etc).
Vision Papers
Vision papers outline futuristic information systems and architectures or anticipate new challenges. Submissions would describe novel projects that are in an early stage but hold out the strong promise of eventual high impact. The focus should be on the key insight behind the project (e.g., a new set of ground rules or a novel technology), as well as explaining how the key insight can be leveraged in building a system. The paper must describe what the success criteria are for the vision project.
VLDB is a single-blind conference. Therefore, authors MUST include their names and affiliations on the manuscript cover page. In addition, for research track papers that belong to a special category authors MUST append the category tag as a SUFFIX to the title of the paper. For example, "Comparison of Top-K algorithms (Experimental Track)". This must be done both in the paper file and in the CMT submission title.
For instructions on how to format and submit a research paper to PVLDB Volume 12 (VLDB'19), please see the submission guidelines.
Errata Notes
It is the policy of PVLDB to accept submission of Errata Notes for publication. Errata Notes are short (1-2 pages) papers that report and correct errors in papers published earlier in PVLDB/VLDB, as defined in section 4 of the PVLDB Publication Policies, see:
http://www.vldb.org/pvldb/policies/PVLDB Publication Policies.pdf
Errata Notes may be submitted by the authors of the original paper, or by others who have found bugs in earlier papers. Errata Notes that are accepted for publication will appear in PVLDB, but will not be part of the VLDB conference program. In PVLDB, Errata Notes will be identified by including the keywords "Errata for" in the title.
Errata notes should be submitted through CMT, using the same submission process as research papers. Submitted Errata Notes must be identifed as such by a title of the form "Errata for: X", where X is the title of the earlier PVLDB paper that is being corrected. Errata Notes will be subjected to a basic level of reviewing if submitted by original authors, and to more detailed reviewing plus feedback/rebuttal from original authors if submitted by someone other than the original authors.