AIM AND SCOPE
Journal of Data science and Modern Techniques (JDMT) aims at rapid publication of high quality results in Data science and Modern Techniques while maintaining rigorous peer-review process. All accepted papers will be appearing online immediately.
JDMT encourages submission of manuscripts related to (but not limited to) Basic/advanced statistics, Bayesian networks, queuing theory, Data warehousing/mining, Dempster-Shafer theory, mathematical programming, Fuzzy sets/logic, genetic algorithms, neural networks Publishing Areas:
- Case studies, cross-case/within-case displays, document studies
- Focus groups, interviews, key informants, observations
- Grounded theory, making good sense, narrative summary analyses
- Matrix displays, responsibility charts, triangulation, influence diagrams
- Balanced scorecard, benchmarking, stakeholder analysis
- Business process models/reengineering, strategy
- Computer simulation, data envelopment analysis, Pareto analysis
- Decision support systems, decision theory, knowledge management
Publication of article types:
Original research articles: Describes original research within the scope of the journal.
Case reports: Reports of clinical presentations describing a diagnostic or therapeutic dilemma followed by evaluative studies
Editorial comments: Introduce current research and comment on major advances and developments in the field.
Methodology: Present a new experimental method, test or procedure. The methods described may be completely new or a better version of already existing one. The method should demonstrate all the possible tests and results.
Rapid communications: Short papers presenting highly significant and original material.
Review articles: To review the progression of a research in the field and make suggestions for future work includes authoritative, comprehensive, descriptions of any subject within the scope of Data science and Modern Techniques journal.
Letters to the editor: Letter consisting of comments directly on publications of journal which are already published or introduces a specific issue of a general interest.
As Journal of Data science and Modern Techniques follows the Creative Commons Attribution License and scholars open access publishing policies, readers can freely access the published articles through online and JDMT will be kept up to date with latest advances in the field of Data science and Modern Techniques. All published articles will be assigned with unique Digital Objective Identifier provided by Cross Ref