VLDB 2018

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VLDB 2018
44th International Conference on Very Large Databases
Event in series VLDB
Dates 2018/08/27 (iCal) - 2018/08/31
Location
Location: Rio De Janeiro, Brazil
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Important dates
Submissions: 2018/03/01
Table of Contents


VLDB is a premier annual international forum for data management and database researchers, vendors, practitioners, application developers, and users. The VLDB 2018 conference will feature research talks, tutorials, demonstrations, and workshops. It will cover issues in data management, database and information systems research, since they are the technological cornerstones of the emerging applications of the 21st century.

VLDB 2018 will take place in Rio de Janeiro, Brazil, from August 27th to August 31st, 2018.

Topics

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 Mining and Analytics, Warehousing. Data Models and Query Languages, Schema Management and Design, Database Usability, User Interfaces and Visualization. Data Mining and Analytics, Warehousing. 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. 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, \”Data Management in the Year 3000 [Vision]\”. This must be done both in the paper file and in the CMT submission title.


Committees

Facts about "VLDB 2018"
AcronymVLDB 2018 +
End dateAugust 31, 2018 +
Event in seriesVLDB +
Event typeConference +
Has coordinates-22° 54' 40", -43° 12' 34"Latitude: -22.911013888889
Longitude: -43.209372222222
+
Has location cityRio De Janeiro +
Has location countryCategory:Brazil +
IsAEvent +
Start dateAugust 27, 2018 +
Submission deadlineMarch 1, 2018 +
Title44th International Conference on Very Large Databases +