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
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Architectures of database, expert, or knowledge-based systems
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Construction of data/knowledge bases
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Applications, case studies, and management issues
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Tools for specifying and developing data and knowledge bases using
tools based on linguistics
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Communication aspects involved in implementing, designing and
using KBSs in cyberspace.
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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:
Submission Deadline
|
August 18th, 2024
|
Publication Date
|
October 2024
|
Guest Editor:
For further
questions or inquiries
Please contact the
Editorial Assistant at
eng@scirp.org