Conference Information

DSDE 2027: International Conference on Data Storage and Data Engineering

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Submission Date:
2027-01-15 Due in 110 days
Notification Date:
2027-02-15
Conference Date:
2027-07-09
Location:
Tokyo, Japan
Years:
QUALIS: B4   Viewed: 34966   Tracked: 10   Attend: 0

Conference Partner Index (CP-I)

54.2 / 100
Ranked #918 of 5,687 conferences · Top 17%

#45 of 337 in Data Mining & Databases #120 of 341 in Systems & Architecture

Academic recognition (35%)
54
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
65
Community attention (10%)
41
Public record completeness (15%)
55

Inputs used: Listed as QUALIS B4 · Editions on record: 10 · Researchers following it here: 10 · Researchers who opened this page in the past 24 months: 10

Missing from the public record: Historical acceptance rates (+4.5) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 80% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-27

Call For Papers

DSDE 2027 (International Conference on Data Storage and Data Engineering) is a QUALIS B4 conference held in Tokyo, Japan on 2027-07-09. The paper submission deadline is 2027-01-15. Acceptance notifications are sent on 2027-02-15.

The purpose of The 10th International Conference on Data Storage and Data Engineering (DSDE 2027) is to bring together researchers, engineers and practitioners interested on databases, big data, data mining, data management, data security and other aspects of information systems and technology involving advanced applications of data. Papers describing advanced methodologies, prototypes, systems, tools and techniques and general survey papers indicating future directions are also encouraged. Papers describing original work are invited in any of the areas listed. Each of these topic areas is expanded below but the sub-topics list is not exhaustive. Unlisted but related sub-topics are also acceptable, provided they fit in one of the following main topic areas: Track 1: Big Data and Analytics ▪ Big Data Applications and Case Studies ▪ Computational Models for Big Data ▪ Data Standards and Interoperability ▪ Social Data Analytics and Web Mining ▪ Big Data as a Service ▪ Big Data Infrastructure and Cloud/Grid/Stream Computing ▪ Big Data Search, Mining, and Visualization ▪ Big Data Security, Privacy, and Trust ▪ Deep Learning for Big Data ▪ Energy-Efficient Computing and In-Memory Databases ▪ Information Visualization and Visual Analytics ▪ Edge Computing and In-Network Data Processing Track 2: Data Management and Quality ▪ Architectural Concepts for Data Management ▪ Mobile Data Management and IoT Data ▪ Large Data Systems Modeling and Management ▪ Open Data and Transparency in Research Data ▪ Smart Cities and Urban Data Analytics ▪ Data and Information Quality Management ▪ Data Management for Analytics ▪ Data Modeling, Visualization, and Virtualization ▪ Industry 4.0 and Sensor Data Management ▪ Linked Data and Semantic Web Technologies ▪ Organizational Concepts and Best Practices in Data Management ▪ City Data Management and Governance Track 3: Data Science and Machine Learning ▪ Data Fusion and Integration ▪ Pattern Recognition and Predictive Modeling ▪ Support Vector Machines and Hybrid Methods ▪ Data Mining and Knowledge Discovery ▪ Deep Learning and Neural Network Applications ▪ Evolutionary Computing and Optimization ▪ Feature Selection and Granular Computing ▪ Fuzzy Computing and Uncertainty in Data Analysis ▪ Process Mining and Workflow Analytics ▪ Data Science Applications and Case Studies Track 4: Databases and Data Security ▪ Database Architecture and Performance Optimization ▪ Large-Scale and Distributed Databases ▪ Mobile and NoSQL Databases ▪ Object-Oriented and Open Source Databases ▪ Query Processing and Optimization ▪ Data Integrity and Consistency ▪ Data Privacy, Security, and Confidentiality ▪ WWW and Databases ▪ Blockchain Technology for Data Storage and Security ▪ Database Management in Cloud Environments
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