JOURNAL OF DATABASE MANAGEMENT

Scope & Guideline

Driving Excellence in Database Management Studies

Introduction

Immerse yourself in the scholarly insights of JOURNAL OF DATABASE MANAGEMENT with our comprehensive guidelines detailing its aims and scope. This page is your resource for understanding the journal's thematic priorities. Stay abreast of trending topics currently drawing significant attention and explore declining topics for a full picture of evolving interests. Our selection of highly cited topics and recent high-impact papers is curated within these guidelines to enhance your research impact.
LanguageEnglish
ISSN1063-8016
PublisherIGI GLOBAL
Support Open AccessNo
CountryUnited States
TypeJournal
Convergefrom 2003 to 2024
AbbreviationJ DATABASE MANAGE / J. Database Manage.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address701 E CHOCOLATE AVE, STE 200, HERSHEY, PA 17033-1240

Aims and Scopes

The Journal of Database Management focuses on the interdisciplinary aspects of database management systems, integrating advanced technologies and methodologies to address contemporary challenges in data management.
  1. Database Technologies and Architectures:
    This area encompasses research on various database architectures, including relational, NoSQL, and distributed databases, emphasizing the design, optimization, and performance of these systems.
  2. Data Analytics and Machine Learning:
    The journal highlights research that combines data management with machine learning and data analytics techniques, focusing on methods for processing, analyzing, and extracting insights from large datasets.
  3. Security and Privacy in Data Management:
    A core focus on securing data against unauthorized access and ensuring privacy in database systems, including studies on encryption, intrusion detection systems, and privacy-preserving data mining.
  4. Application of Emerging Technologies:
    Exploration of how emerging technologies like blockchain, edge computing, and artificial intelligence can be integrated into database management practices to enhance functionality and efficiency.
  5. User-Centric Database Solutions:
    Research that examines the user experience in database interactions, including user interfaces, feedback mechanisms, and the impact of developer responsiveness on application usability.
Recent publications in the Journal of Database Management reflect a growing interest in several emerging themes that are shaping the future of database management research.
  1. Integration of Machine Learning with Databases:
    There is a significant trend towards integrating machine learning techniques with database management systems, as seen in studies focusing on predictive analytics and intelligent data processing.
  2. Blockchain Technologies in Data Management:
    The application of blockchain technology for enhancing data security, integrity, and trust in database systems is gaining traction, indicating a shift towards decentralized solutions.
  3. Privacy and Security Innovations:
    Emerging themes around privacy-preserving technologies and security measures in database management are increasingly relevant, particularly in light of growing data privacy concerns.
  4. User Experience and Responsiveness:
    Research focusing on the impact of user experience and developer responsiveness in database applications is trending, highlighting the importance of user-centric design in database management.
  5. Application of Edge Computing in Data Management:
    The incorporation of edge computing strategies into database management practices is emerging as a vital area of research, addressing the needs of real-time data processing and analysis.

Declining or Waning

Certain themes within the Journal of Database Management have shown a decline in publication frequency or relevance, indicating a shift in research focus within the database management community.
  1. Traditional Database Management Practices:
    Research focusing on conventional database management techniques is becoming less prominent as new methodologies and technologies emerge, leading to a decreased interest in older paradigms.
  2. Basic Data Structures and Algorithms:
    While foundational topics remain important, there appears to be a shift away from basic discussions of data structures and algorithms towards more complex, application-driven research.
  3. General Software Engineering Practices:
    General software engineering topics related to database management are being overshadowed by more specialized research areas, such as those focusing on machine learning applications and security.

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