Instructions for Authors
Comprehensive Guidelines for Manuscript Preparation and Submission
Welcome Authors
Thank you for considering Journal of Big Data Research (JBR) for publishing your research. These comprehensive instructions will guide you through manuscript preparation, formatting requirements, and submission procedures. Following these guidelines ensures efficient peer review and accelerates publication.
JBR is an open access, peer-reviewed journal dedicated to advancing research in big data analytics, machine learning, artificial intelligence, data mining, and computational data science. We publish original research articles, comprehensive reviews, case studies, short communications, and methodological papers that contribute to the field's theoretical foundations or practical applications.
Important Notice: All manuscripts submitted to JBR undergo rigorous Single-Blind Peer Review as standard. Double-Blind Review is available upon request to ensure impartial evaluation. No fees are charged for submission or peer review—Article Processing Charges apply only after acceptance.
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Article Types and Specifications
Original Research Articles
Word Count: 6,000-10,000 words (excluding references)
Abstract: 250-300 words
Keywords: 4-6 terms
Content: Present original research with novel findings in big data analytics, machine learning algorithms, data mining techniques, or AI applications. Include comprehensive methodology, results, discussion, and implications for theory or practice.
Review Articles
Word Count: 8,000-12,000 words
Abstract: 300-350 words
Keywords: 5-7 terms
Content: Comprehensive, critical analysis of existing literature on specific big data topics. Synthesize current knowledge, identify research gaps, and propose future directions. Minimum 80-100 references required.
Short Communications
Word Count: 2,000-4,000 words
Abstract: 150-200 words
Keywords: 3-5 terms
Content: Concise reports of preliminary findings, novel datasets, technical innovations, or methodological advances that warrant rapid dissemination. Limited figures/tables (maximum 3 combined).
Case Studies
Word Count: 4,000-6,000 words
Abstract: 200-250 words
Keywords: 4-6 terms
Content: Real-world applications of big data technologies in specific domains. Include problem context, implementation details, challenges encountered, solutions developed, and lessons learned. Emphasize practical insights and reproducibility.
Methodological Papers
Word Count: 5,000-8,000 words
Abstract: 250-300 words
Keywords: 4-6 terms
Content: Novel algorithms, frameworks, analytical approaches, or experimental methodologies for big data research. Include theoretical foundation, algorithmic description, complexity analysis, validation, and comparative evaluation.
Manuscript Preparation Guidelines
Standard Manuscript Structure
Organize your manuscript using the following structure:
- Title Page: Title (concise, descriptive), author names, affiliations, corresponding author contact, ORCID IDs
- Abstract: Structured or unstructured summary (see specifications by article type)
- Keywords: 4-6 relevant terms for indexing and discoverability
- Introduction: Background, research gap, objectives, significance
- Literature Review: Critical analysis of relevant prior work (can be integrated with Introduction)
- Methodology/Materials and Methods: Detailed description enabling reproducibility
- Results: Present findings objectively with supporting data, figures, and tables
- Discussion: Interpret results, compare with existing literature, address limitations
- Conclusion: Summarize key findings, implications, and future research directions
- Acknowledgments: Funding sources, contributor recognition
- References: Complete citation list (see formatting section)
- Supplementary Materials: Datasets, code, additional figures (if applicable)
Title Requirements
- Concise yet descriptive (10-15 words recommended)
- Include key terms for SEO and discoverability
- Avoid abbreviations, jargon, or ambiguous terms
- Use title case capitalization
- Accurately reflect manuscript content and contribution
Abstract Guidelines
Write a standalone summary that conveys:
- Background/Context: Brief problem statement and motivation
- Objectives: Clear research goals or hypotheses
- Methods: Key approaches, datasets, or algorithms used
- Results: Main findings with specific outcomes or metrics
- Conclusions: Significance and implications
- Do NOT include citations, abbreviations (unless defined), or references to figures/tables
Keywords Selection
- Choose 4-6 specific, relevant terms not in the title
- Use established terminology from big data, ML, AI domains
- Include both broad concepts and specific techniques
- Consider terms researchers would use to find your work
- Examples: "deep learning," "data mining," "predictive analytics," "neural networks," "classification algorithms"
Formatting Requirements
File Format
Microsoft Word (.docx), LaTeX (.tex), or PDF. Word format preferred for efficient editing and production.
Font & Spacing
Times New Roman, Arial, or Calibri, 12pt. Double-spaced throughout. 1-inch (2.5cm) margins on all sides.
Line Numbering
Enable continuous line numbering for reviewer reference. Essential for efficient peer review process.
Page Numbers
Number all pages consecutively starting from title page. Center or right-aligned footer.
Headings
Use hierarchical heading structure (H1, H2, H3). Clear, descriptive section titles in bold or larger font.
Language
English (US or UK, but consistent). Clear, grammatically correct writing. Language editing available if needed.
LaTeX Users: JBR accepts LaTeX submissions. Include all source files (.tex, .bib, figures) and a compiled PDF. Use standard document classes (article, IEEEtran) rather than publisher-specific templates.
References and Citations
Citation Style
JBR uses APA Style (7th edition) or IEEE style for references. Choose one style and apply consistently throughout the manuscript.
APA Style Example:
Smith, J., & Johnson, M. (2023). Deep learning approaches for big data analytics. Journal of Big Data Research, 5(2), 123-145. https://doi.org/10.14302/issn.2768-0207.jbr-23-1234
IEEE Style Example:
[1] J. Smith and M. Johnson, "Deep learning approaches for big data analytics," J. Big Data Res., vol. 5, no. 2, pp. 123-145, 2023, doi: 10.14302/issn.2768-0207.jbr-23-1234.
Reference Requirements
- Include DOIs for all references where available
- Cite original sources rather than secondary citations
- Verify accuracy of all citations (authors, titles, years, page numbers)
- Include recent literature (50%+ from last 5 years recommended)
- Balance self-citations (typically <10% of total references)
- Minimum references: Research articles (30+), Reviews (80+), Case studies (20+)
Acceptable Reference Types
- Preferred: Peer-reviewed journal articles, conference proceedings, published books
- Acceptable: Preprints (arXiv, bioRxiv), technical reports, theses/dissertations, datasets with DOIs
- Use sparingly: Websites, blogs, white papers (cite only when essential and stable URLs available)
- Avoid: Personal communications, unpublished data, non-archival sources
Figures, Tables, and Supplementary Materials
Figure Requirements
Technical Specifications:
- Resolution: Minimum 300 DPI for photos, 600 DPI for line art
- Format: TIFF, PNG, JPEG, or EPS. Vector formats (SVG, EPS) preferred for graphs/diagrams
- Size: Minimum 1000 pixels width for single-column figures
- Color: RGB for online; provide CMYK if print reproduction anticipated
- Labeling: Clear axis labels, legends, and annotations. Use sans-serif fonts (Arial, Helvetica)
- File naming: Figure1.png, Figure2.tiff, etc. (descriptive names accepted)
Figure Captions:
Provide concise, descriptive captions that enable figure interpretation without referencing main text. Include: (1) Brief title, (2) Explanation of components/symbols, (3) Statistical details if applicable, (4) Permission statements for reproduced figures.
Table Guidelines
- Use editable table format (Word tables, LaTeX tabular) rather than images
- Number tables consecutively (Table 1, Table 2, etc.)
- Provide descriptive table titles above the table
- Include column headers with units where applicable
- Use footnotes (a, b, c) for table-specific notes
- Indicate statistical significance clearly (*, **, p-values)
- Ensure tables are self-explanatory without main text reference
Supplementary Materials
Support reproducibility and transparency by providing:
- Datasets: Raw or processed data in standard formats (CSV, JSON, HDF5)
- Source code: Algorithms, analysis scripts (Python, R, MATLAB) with documentation
- Additional figures: Extended visualizations not fitting main manuscript
- Video demonstrations: Algorithm visualizations, system demos (MP4, AVI)
- Technical appendices: Detailed proofs, extended methodology
- See data archiving guidelines for data sharing requirements
Submission Process
Ready to submit? Follow our streamlined submission process:
Submit Your Manuscript
Use our online submission system for the fastest, most efficient submission experience:
Submit Manuscript NowNeed Help? Contact our editorial office at [email protected] for submission assistance, formatting questions, or scope inquiries.
Additional Resources
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