Aims and Scope

With large amounts of data growing exponentially in most areas, collecting, processing, analyzing, mining, and using big data become very important in the data science communities. Journal of Data Science and Intelligent Systems (JDSIS) is an international, peer-reviewed, interdisciplinary journal that provides in-depth coverage of the latest advances in the closely related fields of data science and intelligent systems.

JDSIS considers researches that focus on data integration, data information and knowledge extraction, and data application in a wide range of fields, including health, education, agriculture, biology, medicine, finance, environment, engineering, commerce, and industry. By integration of data with computer science, artificial intelligence, and other appropriate methods, the scope of JDSIS covers the entire process of areas of Data Science and Intelligent Systems:

  • Big data itself, i.e., the nature and quality of the data
  • Data science and intelligent systems aspects of knowledge-based and expert systems
  • Principles and theories of data acquisition, extraction, and integration
  • Techniques and systems used to analyze and manage big data
  • Methods and algorithms designed for data mining, online analysis, decision-making, and other data-intensive computing
  • Artificial Intelligence techniques relating to data science and intelligent systems
  • Artificial Intelligence for database (AI4DB) and database for Artificial Intelligence (DB4AI) techniques
  • Knowledge and data engineering tools and techniques
  • Data management methodologies
  • Distributed and parallel databases processing
  • Architectures for knowledge and data-based intelligent systems
  • Database design and modeling
  • System integration and modeling of intelligent systems
  • Algorithms and technologies for intelligent systems
  • Hardware systems and software systems for data computing
  • Practical application and design of data algorithm, theory, or equation in aspecific field (industry, agriculture, manufacturing, and service) 

We encourage the application of the above methods and techniques in a wide range of Data Science and Intelligent Systems domains. For example, the following topics of life sciences are welcome:

  • Using parallel or high-performance computing for biological big data; e.g., multiple sequence alignment, clustering, redundancy eliminating, and evolutionary tree construction
  • Pattern recognition from the biological sequence, e.g., sequence classification, annotation, and function analysis
  • Modeling on multi-omics data for revealing their interaction and relationship with cancers, and applying the model in disease intelligent diagnosis and precision medicine
  • Advanced statistical and intelligent methods for medical data analysis and mining
  • Software, web tools, and database development