Special Issue on Data and Knowledge Engineering

Data Engineering is the discipline of designing, building, and maintaining a robust infrastructure for collecting, transforming, storing, and serving data for use in machine learning, analytic reporting, and decision management.?Data Engineering enables efficient and operationalized Data Science. The goal of this special issue is to provide a platform for scientists and academics all over the world to promote, share and discuss various new issues and developments in Data and Knowledge Engineering .

In this special issue, we invite front-line researchers and authors to submit original research and review articles that explore Data and Knowledge Engineering. In this special issue, potential topics include, but are not limited to:

• Representation and manipulation of data & knowledge
• Architectures of database, expert, or knowledge-based systems
• Construction of data/knowledge bases
• Applications, case studies, and management issues
• Tools for specifying and developing data and knowledge bases using tools based on linguistics
• Communication aspects involved in implementing, designing and using KBSs in cyberspace.
• Drilling and completion safety

Authors should read over the journal’s For Authors carefully before submission. Prospective authors should submit an electronic copy of their complete manuscript through the journal’s Paper Submission System.

Please kindly specify the “Special Issue” under your manuscript title. The research field “Special Issue - Data and Knowledge Engineering” should be selected during your submission.

Special Issue timetable:

Guest Editor:

For further questions or inquiries

Please contact the Editorial Assistant at

eng@scirp.org