Editorial Policies

Focus 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

 

Section Policies

Articles

Checked Open Submissions Checked Indexed Checked Peer Reviewed
 

Peer Review Process

ZAHRA  •  For Authors

Peer Review Process

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

ZAHRA currently describes its editorial evaluation as a double-blind peer-review process following an initial editor and section-editor screening.

Review model and reviewer assignment

The publicly displayed policy states that a manuscript passing the editor’s initial originality screening is sent to a section editor and then to at least one reviewer. ZAHRA describes this arrangement as double-blind peer review: the identities of authors and reviewers should be withheld from each other during review as far as the editorial system and files permit.

Step-by-step evaluation

StageWhat happensResponsibility
1. SubmissionManuscript and metadata are submitted online.Authors
2. Preliminary screeningScope, completeness, originality, and text similarity are considered.Editor
3. Section handlingThe manuscript is assigned to the appropriate editorial section.Section editor
4. Scholarly reviewReviewer evaluates scientific contribution, methodology, evidence, presentation, and references.Reviewer
5. Editorial evaluationReports and any revision are assessed to determine the next action.Editor / section editor
6. Author responseIf invited, authors revise the paper and provide a detailed response.Authors
7. Final outcomeThe editor communicates the final editorial outcome.Editor

Review criteria

  • Research relevance to the journal and clarity of the research problem.
  • Originality or value of the methodological, empirical, or review contribution.
  • Appropriateness of research design, data processing, experimental protocol, and metrics.
  • Credibility of the reported findings and consistency between evidence and conclusions.
  • Strength and accuracy of related literature, citation practices, and research-ethics compliance.
  • Clarity of scientific writing, tables, figures, and reproducibility information.

Published review timelines

The existing editorial policy states that reviewer assessment is expected to take no more than three weeks and describes an overall acceptance decision period of approximately 3–8 weeks. These published timelines are indicative and may vary if substantial revision or further review is required.

Types of editorial decisions

  1. Accepted for publication.
  2. Revision requested.
  3. Resubmit for renewed review.
  4. Suggested submission to a different journal.
  5. Rejected.

Double-blind manuscript preparation

  • Remove author names, affiliations, acknowledgments, and identifying contact information from the blinded manuscript file when requested.
  • Review document properties and file metadata for identifying details.
  • Use neutral self-citation language that does not disclose identity unnecessarily.
  • Keep title page and other identifying files separate if the submission workflow requests them.
The live ZAHRA policy currently specifies at least one reviewer. A two-reviewer requirement is a possible enhancement, but it must not be stated as current policy until formally implemented and published.
Publisher: Asosiasi Peneliti Data Science Indonesia  |  ZAHRA homepage

 

Publication Frequency

ZAHRA  •  Journal Updates

Publication Schedule

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

According to the journal’s public homepage, ZAHRA follows a twice-yearly publication schedule, with one issue planned for June and another for December.

Regular issue calendar

Issue numberPublication monthFrequency
No. 1JuneFirst regular issue of the year
No. 2DecemberSecond regular issue of the year

Publication dates and verification

The schedule above states the intended publication calendar. The availability and final publication date of a particular volume or issue can only be confirmed from the issue record and the associated article pages in the public Archives.

Manuscript handling and issue assignment

Manuscripts undergo editorial screening and peer review before an acceptance decision. Acceptance should not be confused with immediate placement in a particular issue. Authors should contact the editorial office for issue planning and status questions rather than treating the journal frequency as a guaranteed acceptance deadline.

Publication record

The archive available at the time of this preparation displays volumes for 2022 and 2023. Publication continuity and records for any later periods require editorial verification. New issues must be published using the actual publication process and accurate dates.

Useful links

Publisher: Asosiasi Peneliti Data Science Indonesia  |  ZAHRA homepage

 

Open Access Policy

ZAHRA  •  About This Journal

Open Access Policy

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

ZAHRA provides immediate open access to published content on the principle that making research freely available supports wider exchange and use of scholarly knowledge.

Access to published articles

Readers can access the journal’s published articles online without a subscription paywall. Immediate access facilitates scholarly reading, education, research discussion, and dissemination of published results.

Reading access and reuse rights are distinct

Open access permits reading the publication, but permissions for redistribution, adaptation, commercial reuse, and related activities are determined by the applicable copyright license. Users should examine the article’s displayed license and any accompanying copyright statement before reuse.

Author copyright and first publication

The current OJS Copyright Notice states that authors retain copyright, grant the journal the right of first publication, and license the work under Creative Commons Attribution 4.0 International (CC BY 4.0). It also permits separate non-exclusive dissemination agreements that acknowledge first publication in this journal.

Repository sharing

The OJS notice expressly permits and encourages authors to place their work on websites or institutional repositories, including before or during submission, consistent with proper acknowledgement and any applicable third-party rights.

Citation and attribution

  • Identify the authors, original title, journal title, publication details, and persistent identifier when available.
  • Include the correct Creative Commons license and indicate whether changes were made when required.
  • Do not imply author or journal endorsement of a reuse or derivative work.
Publisher: Asosiasi Peneliti Data Science Indonesia  |  ZAHRA homepage

 

History of the Journal

 
ZAHRA   /   About This Journal

History of the Journal

A factual account of the journal identity, public issues and publication development.
 

ZAHRA: Bulletin Big Data, Data Science, and Artificial Intelligence (e-ISSN 2830-7984) is an open-access scholarly journal published by Asosiasi Peneliti Data Science Indonesia (PDSI). It was established as a publication venue for scholarly exchange on big data, data science, and artificial intelligence, including data engineering, analytics, machine learning, and intelligent computational methods.

1. Journal identity and publication model

Journal attributeDocumented information
Journal nameZAHRA: Bulletin Big Data, Data Science, and Artificial Intelligence
e-ISSN2830-7984
PublisherAsosiasi Peneliti Data Science Indonesia (PDSI)
Stated frequencyTwo issues per year: June and December
First publicly listed volumeVolume 1 (2022)
Public issue catalogueZAHRA Archives

2. Chronology of publicly listed issues

YearIssueWhat can be verified in the public archive
2022Vol. 1, No. 1 — JuneJune 2022 issue; the archive describes seven research articles, available online from 30 June 2022.
2022Vol. 1, No. 2 — DecemberDecember 2022 issue; the archive describes seven research articles, available online from 30 December 2022.
2023Vol. 2, No. 1 — JuneJune 2023 issue is listed in the public archive; article-level completeness should be checked against the OJS record.
2023Vol. 2, No. 2 — DecemberDecember 2023 issue is listed in the public archive; article-level completeness should be checked against the OJS record.

3. Development of the journal’s scholarly scope

The journal’s published description identifies research challenges in data capture, storage, search, sharing, analysis, visualisation, scalable architectures, distributed file systems and databases, data mining, machine learning for big data, and cloud-based computation. The journal’s editorial information can evolve to reflect developments in deep learning and responsible AI, provided any expanded scope is supported by published research and clearly documented policies.

4. Publication continuity and archive transparency

At the time this history was prepared (26 October 2026), the public Archives page listed four issues spanning 2022–2023. Later volumes or issues were not visible in that archive inspection. The journal should publish future history updates only after authentic issue and article records are available; planned covers, volume numbers, or templates alone are not evidence of publication.

5. Commitment to a verifiable scholarly record

An accurate journal history records actual publication dates, issue details, and article metadata. Corrections, the development of editorial policies, and changes to publishing operations should be documented transparently. Readers should consult the live Archives for the authoritative issue list, and direct requests for historical clarification to the editorial office.

The issue sequence and dates above are derived from publicly displayed records, not from projected volume plans. This page should be reviewed after each verified new issue is published.
ZAHRA: Bulletin Big Data, Data Science, and Artificial Intelligence
e-ISSN 2830-7984   |   Published by Asosiasi Peneliti Data Science Indonesia (PDSI)   |   Contact the Journal