About the Journal

International Journal of Data Science (IJDS): ISSN Pending


The International Journal of Data Science (IJDS) is dedicated to publishing cutting-edge, peer-reviewed research that harnesses the transformative power of data science across various domains. The journal aims to provide a multidisciplinary platform that encourages the integration of methods, tools, and insights from data science with specific applications, fostering innovation and improving decision-making processes. IJDS seeks to inspire a dialogue among researchers, practitioners, and policymakers to explore how data-driven solutions can address complex challenges in science, industry, and society.


The scope of IJDS is broad and inclusive, oriented towards a range of thematic areas where data science plays a pivotal role:

  1. Agricultural Data Science:

    • Precision agriculture and sustainable farming techniques.
    • Integration of IoT devices and sensors for data collection and analysis in agricultural settings.
    • Predictive analytics for crop yield, pest management, and resource allocation.
    • Environmental impact assessments using big data.
  2. Health Sciences Data Science:

    • Application of machine learning in diagnostic processes, treatment optimization, and patient care.
    • Development of predictive models for disease progression and outcomes.
    • Analysis of biomedical data, including genomics, proteomics, and clinical data.
    • Digital health interventions and their effectiveness.
  3. Life Sciences Data Science:

    • Bioinformatics and computational biology, including systems biology and metabolic pathway analysis.
    • Ecological and environmental modeling to understand biodiversity and ecosystem health.
    • Integration of data science in pharmacology for drug discovery and repurposing.
    • Use of artificial intelligence in studying genetic diseases and personalized medicine.
  4. Forensic Sciences Data Science:

    • Advances in digital forensics and cybercrime analysis.
    • Statistical techniques for evidence evaluation and forensic anthropology.
    • Development of software tools for crime scene reconstruction and forensic visualization.
    • Data management in forensic case work, including DNA databases.
  5. General Data Science:

    • Theoretical advancements in algorithms and models for data processing and analysis.
    • Innovations in machine learning, deep learning, and artificial intelligence that impact multiple sectors.
    • Big data analytics, data mining, and data visualization techniques.
    • Ethical considerations, data privacy, and security issues in data science.
  6. Emerging Areas in Data Science:

    • Data science applications in urban planning and smart cities.
    • Analysis of social media data for trends, sentiment, and sociological insights.
    • Data-driven strategies in business, finance, and marketing.
    • Role of data science in educational advancements and e-learning technologies.

Mission: IJDS is committed to advancing scientific knowledge and understanding by providing a platform for researchers to share innovations and discoveries that bridge the gap between basic research and practical applications. The journal promotes the publication of high-quality research that demonstrates a clear data-driven approach, supports open data and reproducible science, and contributes to the global conversation on data-centric technologies and methodologies.

By featuring a broad range of topics within data science, IJDS serves as a valuable resource for academic researchers, industry professionals, and policymakers who are engaged in the development and application of data science to solve pressing challenges in diverse fields.