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Very Large Data Base Endowment

48th International Conference on Very Large Data Bases (VLDB)

Location: Sydney , Australia

Submission deadline: 3/1/2022

Conference dates: 9/5/2022 - 9/9/2022

Research H-index
27

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 79 116 109 27

Call for Papers

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.

Data Mining and Analytics
Data Warehousing, OLAP, Parallel and Distributed Data Mining
Mining and Analytics for Scientific and Business data, Social Networks, Time Series, Streams, Text, Web, Graphs, Rules, Patterns, Logs, and Spatio-temporal Data
Data Privacy and Security
Blockchain
Access Control and Privacy
Database Engines
Access Methods, Concurrency Control, Recovery and Transactions
Hardware Accelerators
Query Processing and Optimization
Storage Management, Multi-core Databases, In-memory Data Management
Views, Indexing and Search
Database Performance
Tuning, Benchmarking and Performance Measurement
Administration and Manageability
Distributed Database Systems
Content Delivery Networks, Database-as-a-service, and Resource Management
Cloud Data Management
Distributed Analytics
Distributed Transactions
Graphs, Networks, and Semistructured Data
Graph Data Management, Recommendation Systems, Social Networks
Hierarchical, Non-relational, and other Modern Data Models
Information Integration and Data Quality
Data Cleaning, Data Discovery and Data Exploration
Heterogeneous and Federated DBMS, Metadata Management
Web Data Management and Semantic Web
Knowledge Graphs and Knowledge Management
Languages
Data Models and Query Languages
Schema Management and Design
Machine Learning, AI and Databases
Data Management Issues and Support for Machine Learning and AI
Machine Learning and Applied AI for Data Management
Novel DB Architectures
Embedded and Mobile Databases
Data management on novel hardware
Real-time databases, Sensors and IoT, Stream Databases
Crowd-sourcing
Provenance and Workflows
Profile-based and Context-Aware Data Management
Process Mining
Provenance analytics
Debugging
Specialized and Domain-Specific Data Management
Spatial Databases and Temporal Databases
Crowdsourcing
Ethical Data Management
Fuzzy, Probabilistic and Approximate Data
Image and Multimedia Databases
Scientific and Medical Data Management
Text, Semi-Structured Data, and IR
Information Retrieval
Text in Databases
Data Extraction
User Interfaces

Overview

This ranking presents a comprehensive and meticulously researched list of scientific conferences in the field of Computer Science. Developed by Research.com, a trusted authority in science research since 2014, this ranking reflects the leading conferences that have made significant contributions to the advancement of the discipline. Research.com is renowned for providing reliable and authoritative data in all major areas of science, including Computer Science.

The position of each conference in the ranking is determined by a unique bibliometric score formulated by Research.com. This score is derived from a combination of factors, including the estimated h-index of the conference and the number of leading scientists who have contributed presentations or papers at the event during the three most recent years. The ranking is based on impact score values gathered as of 2024-11-27, ensuring the most current and relevant assessment of scientific influence.

The process for ranking conferences involved a detailed inspection and rigorous analysis of more than 2,742 conferences, selected from an extensive review of over 148,739 scientific documents published in the preceding three years by 13,184 leading and well-respected scientists in Computer Science. This comprehensive evaluation highlights the depth of research and the complexity of the analysis undertaken by our team of experts.

For further details regarding the methodology used to compute the ranking scores, please refer to our Methodology Page.

Papers citation over time

A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing at Very Large Data Bases (based on the number of publications) are:

  • Divesh Srivastava (81 papers) published 3 papers at the last edition, 1 less than at the previous edition,
  • Lei Chen (74 papers) published 4 papers at the last edition, 7 less than at the previous edition,
  • Xuemin Lin (71 papers) published 8 papers at the last edition, 2 less than at the previous edition,
  • H. V. Jagadish (69 papers) published 2 papers at the last edition, 4 less than at the previous edition,
  • Christian S. Jensen (69 papers) absent at the last edition.

The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing at Very Large Data Bases (based on the number of publications) are:

  • IBM (384 papers) published 4 papers at the last edition, 8 less than at the previous edition,
  • Microsoft (321 papers) published 26 papers at the last edition, 6 more than at the previous edition,
  • National University of Singapore (169 papers) published 6 papers at the last edition, 9 less than at the previous edition,
  • University of Wisconsin-Madison (150 papers) published 5 papers at the last edition, 1 less than at the previous edition,
  • Stanford University (149 papers) published 5 papers at the last edition, 5 less than at the previous edition.

The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 3.67% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 25.26% were posted by at least one author from the top 10 institutions publishing at the conference. Another 15.22% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 23.53% of all publications and 35.99% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Related Online Degrees & Career Pathways

For those interested in expanding their expertise beyond traditional computer science, exploring related online degrees can open new career doors. A popular option is pursuing a data analytics masters, which focuses on interpreting complex datasets to inform business decisions. This degree is ideal for professionals seeking to harness big data in practical applications.

For advanced researchers and academics, enrolling in an online PhD in data science provides opportunities to lead innovations in machine learning, artificial intelligence, and statistical modeling. This path often leads to roles in academia or cutting-edge industry research.

Another interdisciplinary option is a careers with a bioinformatics degree, blending computer science with biology and healthcare. This specialization is crucial for developments in genomics, pharmaceuticals, and personalized medicine.

Additionally, the rise of telehealth and digital medicine means that online healthcare degrees are increasingly relevant. Combining these with computational skills can lead to transformative roles in medical informatics and healthcare technology.

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