Data Technologies and Applications - Emerald - Impact Factor

Data Technologies and Applications - Emerald | 2024 Impact Factor:1.5 | Cite Score:4.7 | Q2

Data Technologies and Applications Journal

Impact Factor and Journal Rank of Data Technologies and Applications

About: Data Technologies and Applications (DTA) is a peer-reviewed journal that publishes high-quality research papers and reviews covering all aspects of data technologies. The journal aims to foster the exchange of knowledge and innovations in data management, analytics, and applications across diverse disciplines.
Objectives
The primary objectives of the journal are:
Advancing Data Technologies: To publish cutting-edge research on the development and application of data technologies.
Data Management and Analytics: To explore methods and techniques for managing, processing, and analyzing large-scale datasets.
Applications Across Disciplines: To showcase practical applications of data technologies in various domains, including healthcare, finance, engineering, and social sciences.
Interdisciplinary Collaboration: To encourage collaboration between researchers and practitioners in data science, computer science, statistics, and other relevant fields.
Impact on Society: To highlight the societal impact of data technologies through improved decision-making, innovation, and efficiency.
Key Topics Covered
Big Data Technologies: Tools and platforms for managing and analyzing large-scale datasets.
Data Mining and Machine Learning: Techniques for extracting insights and patterns from data.
Data Integration and Interoperability: Methods for integrating heterogeneous data sources and ensuring data compatibility.
Data Privacy and Security: Solutions and strategies for protecting data privacy and ensuring data security.
Cloud Computing: Applications of cloud technologies in data storage, processing, and analytics.
Blockchain and Distributed Ledger Technologies: Use cases and applications of blockchain in data management and security.
Internet of Things (IoT): Data technologies for collecting, processing, and analyzing IoT data.
Social Media Analytics: Techniques for analyzing social media data to extract trends and insights.
Healthcare Informatics: Applications of data technologies in healthcare for improving patient care and outcomes.
Business Intelligence: Tools and techniques for business analytics and decision support.
Impact and Significance
Data Technologies and Applications contributes significantly to:
Technological Advancement: By publishing research that advances the state-of-the-art in data technologies.
Cross-Disciplinary Innovation: By fostering collaboration and innovation across diverse disciplines.
Practical Applications: By showcasing real-world applications of data technologies that benefit organizations and society.
Education and Knowledge Dissemination: By serving as a resource for researchers, practitioners, and educators in data science and related fields.
Ethical Considerations: By addressing ethical and societal implications of data technologies.

Journal Home: Journal Homepage

Editor-in-Chief: Dr Miguel-Angel Sicilia

Scope: Interdisciplinary Journal on Computing, Information Science, and Social Sciences is a scholarly publication that spans multiple disciplines, focusing on digital data and its impact across various fields. The journal aims to foster research that includes relevant empirical content and evaluation. The journal welcomes research papers addressing topics such as:
Information Creation and Use: Studies on the creation, dissemination, and use of digital information, including web-based platforms like wikis, social media, and collaborative tools.
Web of Data/Linked Data: Research on sharing and integrating data using web-based and linked data approaches to enhance accessibility and interoperability.
E-Science and Data Science: Advances in computational methods and technologies for managing, analyzing, and interpreting large-scale datasets across scientific domains.
Semantic Web and Intelligent Techniques: Applications of semantic web technologies and intelligent techniques to exploit digital information effectively on the web.
Big Data Processing: Novel techniques for processing and analyzing large volumes of data, including data mining, machine learning, and predictive analytics.
Social Networks and Platforms: Studies on the structure, dynamics, and impact of social networks and online platforms on society, communication, and behavior.