ABOUT IJDE

Data Engineering refers to the use of data engineering techniques and methodologies in the design, development and assessment of computer systems for different computing platforms and application environments. With the proliferation of the different forms of data and its rich semantics, the need for sophisticated techniques has resulted an in-depth content processing, engineering analysis, indexing, learning, mining, searching, management, and retrieval of data.

International Journal of Data Engineering (IJDE) is a peer review open access scientific journal for sharing and exchanging research and results to problems encountered in today's data engineering societies. IJDE especially encourage submissions that make efforts (1) to expose practitioners to the most recent research results, tools, and practices in data engineering topics; (2) to raise awareness in the research community of the data engineering problems that arise in practice; (3) to promote the exchange of data & information engineering technologies and experiences among researchers and practitioners; and (4) to identify new issues and directions for future research and development in the data & information engineering fields.

The journal aims to publish and promote the research in data and information engineering technologies among researchers and scientists in the field of data engineering algorithms, data engineering models, data integration, data ontologies, data privacy and security, data warehousing, personalized databases and web data engineering and management. The journal welcomes researchers, scientists, information technology professionals, business analysts, academics, managers and industrial experts to exchange their ideas, opinions and interests with respect to data engineering.

READERSHIP

IJDE aims to publish and promote the research in data and information engineering technologies among researchers and scientists in the field of data engineering algorithms, data engineering models, data integration, data ontologies and data privacy and security. The journal welcomes researchers, scientists and industrial experts to exchange their ideas, opinions and interests with respect to data engineering.

The journal mainly targets information technology professionals, researchers, business analysts, scientists, academics, designers, managers and research centers and encourages them not only to circulate scientific information but also to make latest researches and developments in the field of data engineering.

IJDE is dedicated to publish high quality research papers that include theoretical and empirical results in the field of data warehousing, knowledge technologies, social information management and web data engineering and management. The journal will help the intended audience to learn more about the latest and innovative techniques used in data engineering.

LIST OF TOPICS

ABSTRACTING & INDEXING		CITATION ANALYSIS
The publications of IJDE are abstracted and indexed in following databases and websites.		Below calculations are based on in-process citations that are extracted through Google Scholar. Total Citations = 69 Self Citations = 0 Total Publications = 34 Citation Impact (Total Citations - Self Citations) / Total Publications Citation Impact (69 - 0) / 34 = 2.029   In-Process Citation Report for IJDE
Google Scholar Academia Academic Index CiteSeerX BibSonomy refSeek TechRepublic iSEEK ResearchGate Doc Player Bielefeld Academic Search Engine (BASE) J-Gate Scribd SlideShare PdfSR Google Books