Veri Bilimi

The Data Science journal aims to guide new interdisciplinary articles and project studies by creating a publication platform for research and compilation articles in the field of data science and its applications in the national and international scientific community.

Our journal covers topics related to scientific data in all areas, from data creation, mining, discovery, curation, modeling, processing and management to analysis, prediction, visualization, user interaction, communication, sharing and reuse. In addition to general tools and concepts, we are interested in specific tools, infrastructures and applications. The ultimate goal is to deepen our understanding of physical, biological and digital systems, to grasp human social and economic behaviors and to unleash the power of scientific data to design new solutions for daily life and the future. New methods are needed to extract, transfer, pool, refine, store, analyze and visualize data to unleash data and also to make tools and workflows easier to use. The Data Science journal evaluates contributions from data-based methods, applications and tools from all areas. In addition, our journal accepts articles that add a social, geographical and temporal dimension, as well as application-oriented articles that prepare and use data in exploratory research.

Data Science journal is indexed by nine international indexes.

Our journal covers studies on data analysis from both the natural and social sciences. In addition to the main topics below, all data-based studies are accepted.

Engineering Sciences (Computer Sciences, Biomedical, Electrical and Electronics, Industrial Engineering, Mathematics, Statistics, Chemical/Polymer Engineering, Mining Engineering, Mechanical Engineering, Metallurgical and Materials Engineering, Forest Industrial Engineering, Forest Engineering, Agricultural Sciences)
Natural Sciences (Physics, Chemistry, Biology)
Educational Sciences (Adult Education, Child Development, Special Education, Preschool Education, Foreign Language Education, Guidance and Psychological Counseling, Computerized Educational Technologies Education, etc.)
Administrative Sciences (Public Administration, Local Administrations, Political Sciences, Social Service, etc.)
Economic Sciences (Econometrics, Economics, Finance, Economics, Finance, Accounting, Banking and Insurance, Finance, Labor Economics and Industrial Relations, etc.)
Business (Management Information Systems, Management and Organization, Organizational Behavior, Marketing, International Relations, Public Relations, Marketing and Advertising, Office Management and Executive Assistantship)
Health Sciences: (Clinical Research, Patient and Employee Rights, Nursing, Health Tourism, Public Health Applications, Quantitative Techniques in Healthcare Institutions, e-Health, Telemedicine, Mobile Health, Lean Health Services, Quality in Healthcare Institutions, Patient-Friendly and Smart Health Services)

THEORETICAL TOPICS

Probabilistic and Statistical Models and Theories
Bioinformatics Analysis
Meta-Analysis with Structural Equation Model
ROC Analysis and Alternative Methods
FROC and AFROC Analysis
Learning Theory
Optimization Methods
Data Compression and Sampling
Statistical Learning
Evolutionary Computing
Operating Systems
Compiler Design
Deep Learning
Financial Modeling
Prediction
Classification
Clustering
Learning Classifiers
Parallel and Distributed Learning
Scientific Data and Big Data Analysis
Artificial Intelligence
Scalable Analysis and Learning
Educational Data Mining
Data Preprocessing, Sampling and Reduction
High Dimensional Data, Feature Selection and Feature Transformation
High Performance Computing for Data Analysis
Architecture, Management and Process for Data Science

MACHINE LEARNING AND KNOWLEDGE DISCOVERY

Knowledge Discovery Theories, Models and Systems
Human-Machine Interaction for Knowledge Discovery and Management
Biomedical Knowledge Discovery, Analysis of Microarray and Gene Data
Machine Learning for High Performance Computing
Machine Learning on the Cloud
Knowledge-Based Neural Networks
Knowledge Discovery from Unstructured and Multimedia Data
Knowledge Discovery in Network and Link Data
Knowledge Discovery in Social Networks
Data and Knowledge Visualization
Cross-media Data Analytics
Big Data Visualization, Modeling and Analytics
Multimedia/Streaming/Text/Visual Analytics
Database Technology
Programming Languages

COMPUTATIONAL DATA SCIENCE

Databases
Big Data
Computational Theories for Big Data Analysis
Computational Intelligence for Pattern Recognition and Medical Imaging
Incremental Learning - Theory, Algorithms and Applications in Big Data
Sparse Data, Feature Selection and Feature Transformation
Intelligent Information Retrieval
Probabilistic and Information Theoretic Methods
Support Vector Machines and Kernel Methods
Time Series Analysis
High Performance/Parallel Computing
Search and Mining
Data Collection, Integration, Cleaning
Data Visualization
Semantic Based Data Mining
Decision Making from Analytics, Hidden Patterns
Optimization for Data Analysis
Computer Architecture for Data Analysis
Computer Graphics for Data Analysis
Computer Application for Data Analysis
APPLICATIONS

Bioinformatics Applications
Biometrics Applications
Biomedical Informatics Applications
Computational Neuroscience Applications
Information Retrieval Applications
Healthcare Applications
Collaborative Filtering Applications
Human Activity Recognition Applications
Natural Language Processing Applications
Web Search Applications
Image Analysis Applications
Parallel and Distributed Data Applications
Data Stream Mining Applications
Graph Mining Applications
Spatial Data Mining Applications
Multimedia Data Mining Applications
Preprocessing Techniques Applications
Data and Information Network Applications
Data and Information Privacy Applications
Data and Information Semantics Applications
Data Management in Smart Grid Applications
Data Mining Algorithms Applications
Data Mining Systems Applications
Data Structures and Data Management Applications
Database and Information System Performance Applications
Electronic Commerce and Web Technologies Applications
Electronic Government and Participatory Applications
Sensor Data Management Applications
Database Systems and Applications
Statistical and Scientific Databases Applications
Temporal, Spatial and High Dimensional Databases
Security and Information Assurance
Soft Computing
Software Engineering
Web and Internet Computing
Theoretical Computer Science
Natural Language Processing Applications
Information Technology Management
Modeling and Simulation

Overview

1) You can download our journal's Article Template and Copyright Transfer Form from the links.

2) The uploaded article should not have been sent/published to another journal. Similarly, scientific studies sent to the journal should not be under evaluation for publication elsewhere as published/oral/poster/presentation.

3) In order to determine the originality of uploaded articles, the article study is subjected to similarity analysis before proceeding to the evaluation stage. The similarity rate with another article study (including your own studies) can be at most 20%. Studies with similarities above this value are not accepted to our journal.

4) In the editing stage after the article is accepted, the responsible author must upload the "Copyright Form", which includes the names and signatures of the other authors in the article, if any, to the Dergipark system.

5) The acceptance of the uploaded article is realized after at least two referee opinions are received and the relevant field editor accepts it.

6- Article name abbreviations should be made using Web of Science Abbreviations.

Article Preparation
Mandatory headings in the article:

Please prepare your work by considering the journal template.

1- Abstract: A short summary emphasizing the innovations of the study and showing its main findings should be given in this section. Cambria font should be used in writing the article text. The abstract text should be justified and should be 10 points. The abstract should be between 100 - 350 words and should not contain uncommon abbreviations or quotations. The number of keywords should be between 3 and 5.

2- Abstract (English Abstract): The full English translation of the Turkish abstract text.

3- Introduction: All texts except the abstract and summary should be in double columns. The introduction is the text section where the subject and problem addressed by the study are stated, the purpose and importance of the research, its limitations are stated and this information is supported by a literature review.
4- Material and Method: This is the section where all the experiments/observations and efforts made to conduct the study and reach a conclusion are stated.

5- Findings and Discussion: This is the section where the study is discussed in terms of similarities, parallels and differences with previous studies.

6- Conclusion: This is the section where the contribution of the study to scientific/daily life, what it has added to the literature, and what conclusions have been reached in terms of theory and practice are written.

7- Acknowledgements: This is the section where the persons/institutions that contributed to the study are specified.

8- Conflict of Interest (if any): This is the section where the persons/institutions that may have a conflict of interest regarding the study are specified.

9- References: This is the section where the scientific books/journals/web pages/visual and written materials used in the study are specified. A sample reference list can be viewed in the pre-loading format. Below are examples for references;

[1] Bennert T, Hanson D, Maher A. “Influence of pavement surface type on tire/pavement generated noise”. Journal of Testing & Evaluation, 33(2), 94-100, 2005.
[2] Erdoğan M, Tekin R, Kaya M. “Investigation of corrosion behavior of 6013 aluminum alloy artificially aged in microwave oven”. Pamukkale University Journal of Engineering Sciences, 20(1), 25-30, 2014.
[3] Haupt RL, Haupt SE. Practical Genetic Algorithms. 2nd ed. New York, USA, Wiley, 2004.
[4] State Planning Organization. “Special Expert Committee Report on Evaluation of State Aids”. State Planning Organization, Ankara, Turkey, 2681, 2004.

Publication Ethics Statement / Publication Ethics
Articles submitted for publication in the Data Science Journal must be prepared in accordance with the rules of research and publication ethics. Our journal observes the publication ethics principles, standards and recommendations determined by COPE (Committee on Publication Ethics) regarding publication ethics.
All rights of the studies uploaded to our journal are transferred to the journal by the authors. A copyright document is obtained from the responsible author for this transaction. The scientific, content, language, legal and ethical responsibilities of the studies published in the journal belong to the author/authors.
In studies evaluated within the journal, our journal addresses the responsible author, does not have a relationship with other authors and is not obliged to provide information to persons other than the responsible author.

Publication Principles
Submission of articles to the Data Science Journal is accepted as an application for publication. In addition, no application fee or referee fee is charged for articles. No royalty fee is paid for articles.
All authors of the article are responsible for the content of the study. All legal and ethical responsibilities regarding the content of the articles published in the journal belong to the authors. Data Science Journal has the right to make corrections to the articles sent to it, to publish or not to publish the articles. In order for the articles to be published, they must not have been published or accepted for publication elsewhere. In order for the studies previously presented as a report to be accepted into the evaluation process; it must be stated in the article that the study was previously presented as a report and that it has been expanded and revised.

Veri Bilimi dergisine gönderilen makale çalışmalarının değerlendirmesi ve yayımlanması ücretsizdir.