About
IEEE Transactions on Knowledge and Data Engineering
TKDE is an archival journal published monthly designed to inform researchers, developers, managers, strategic planners, users, and others interested in state-of-the-art and state-of-the-practice activities in the knowledge and data engineering area.
Scope of Interest
The scope includes the knowledge and data engineering aspects of computer science, artificial intelligence, electrical engineering, computer engineering, and other appropriate fields. This Transactions provides an international and interdisciplinary forum to communicate results of new developments in knowledge and data engineering and the feasibility studies of these ideas in hardware and software.
To reflect the current trends in knowledge and data engineering research and development practice,
TKDE gives priority to submissions on emerging topics, including but not limited to big data and applications, and new frontiers of knowledge and data engineering, such as social networks, social media, and crowd sourcing. Submissions purely focusing on topics centered in some other sister IEEE Transactions, such as core machine learning theory, pattern recognition, image processing, computer vision, neural networks, and fuzzy systems, will not be considered.
Topics of interest include, but are not limited to, the following:
Fields and Areas of Knowledge and Data Engineering:
- Knowledge and data engineering aspects of knowledge based and expert systems
- Artificial Intelligence techniques relating to knowledge and data management
- Knowledge and data engineering tools and techniques
- Distributed knowledge base and database processing
- Real-time knowledge bases and databases
- Architectures for knowledge and data based systems
- Data management methodologies
- Database design and modeling
- Query, design, and implementation languages
- Integrity, security, and fault tolerance
- Distributed database control
- Statistical databases
- System integration and modeling of these systems
- Algorithms for these systems
- Performance evaluation of these algorithms
- Data communications aspects of these systems
- Applications of these systems.
Submission Instructions:
This journal is a hybrid publication, allowing either traditional manuscript submission or author-paid Open Access (OA) manuscript submission. Read about
OA submissions here.
For author information and guidelines on submission criteria, please visit the
TKDE Information and
Submission Guidelines page on
IEEE Transactions on Knowledge and Data Engineering.
In addition to submitting your paper to
TDKE, you are also encouraged to upload the data related to your paper to
IEEE DataPort. IEEE DataPort is IEEE's data platform that supports the storage and publishing of datasets while also providing access to thousands of research datasets. Uploading your dataset to IEEE DataPort will strengthen your paper and will support research reproducibility. Your paper and the dataset can be linked, providing a good opportunity for you to increase the number of citations you receive. Data can be uploaded to IEEE DataPort prior to submitting your paper or concurrent with the paper submission.
TKDE now offers authors access to Code Ocean. Code Ocean is a cloud-based executable research platform that allows authors to share their algorithms in an effort to make the world’s scientific code more open and reproducible.
Sign up for free.
Questions?
Contact:
Editorial board and
staff
