Aims and Scope

ZAHRA  •  About This Journal

Aims and Scope

Bulletin Big Data, Data Science, and Artificial Intelligence | e-ISSN 2830-7984

ZAHRA publishes open-access scholarly contributions concerning big data, data science, data analytics, and artificial intelligence, with attention to both methodological advances and applied research.

Journal aims

The journal provides a scholarly forum for research addressing current and emerging challenges in the collection, management, analysis, sharing, and interpretation of data. It welcomes studies that develop, assess, or apply computational methods to generate reliable and meaningful insights. The journal connects theoretical, methodological, and practical considerations relevant to researchers and practitioners.

Core subject areas

  • Big data systems: data acquisition, ingestion, storage, retrieval, sharing, integration, data quality, and scalable data management.
  • Data science and analytics: exploratory analysis, statistical learning, data mining, knowledge discovery, predictive and prescriptive analytics, and decision support.
  • Artificial intelligence: machine learning, deep learning, intelligent algorithms, model development, optimization, evaluation, and AI-based applications.
  • Data infrastructure: parallel and distributed processing, cloud computing platforms, distributed file systems, databases, and scalable storage architectures.
  • Data representation: visualization, information retrieval, data interpretation, and communication of analytical findings.

Types of contributions

The journal considers original research articles, survey or review papers, and case studies aligned with its disciplinary scope. Original research should present a clear research question, appropriate methods, transparent results, and a defensible contribution. Survey papers should synthesize relevant literature critically, while case studies should explain their methodological and practical significance.

Interdisciplinary applications

Applications are welcome when the central scientific contribution remains relevant to big data, data science, data analytics, or artificial intelligence. Applied manuscripts should demonstrate how the chosen data and methods answer the stated research problem, rather than merely describing software implementation.

Evaluation of suitability

  • Clearly identify the research objective, scientific or practical problem, and relationship to the journal scope.
  • Describe datasets, methods, evaluation procedures, and limitations sufficiently for critical assessment.
  • Distinguish the contribution from related research and support conclusions with evidence.
For submission requirements, consult Author Guidelines and Online Submission.
Publisher: Asosiasi Peneliti Data Science Indonesia  |  ZAHRA homepage