Research Data Policy - International Multispeciality Journal of Health (IJOER)

IJOER Research Data Policy: Comprehensive Guidelines for Data Management, Sharing and Preservation

FAIR Data Principles
Our Commitment to Research Data Integrity

International Multispeciality Journal of Health recognizes research data as the backbone that ensures transparency, reproducibility, and thereby the credibility of the research being published. Our research data policy provides comprehensive guidelines related to data management, sharing, and preservation for all types of business, economic, and social research disciplines.

We encourage authors to share the research data underlying the publication, as this enables verification, replication, and further analysis. This policy is in line with the principles of open science while fully considering ethical, legal, and practical issues regarding data sharing.

Data Sharing Encouraged

IJOER strongly encourages authors to make research data openly available whenever possible. Data sharing enhances research transparency, enables verification, and maximizes the impact and utility of published research.

IJOER Research Data Policy - FAIR Data Principles and Data Management Guidelines

FAIR Data Principles

Authors are encouraged to follow the FAIR data principles to maximize the utility of data:

F
Findable
  • Assign persistent identifiers (DOIs)
  • Provide rich metadata
  • Store data in queryable repositories
  • Data availability statements
  • Use descriptive file names
  • Clearly cite data sources
A
Accessible
  • Use standard communication protocols
  • Long-term accessibility
  • Provide open access when possible
  • Use trusted repositories
  • Maintain authentication when necessary
  • Ensure metadata remains accessible
I
Interoperable
  • Use formal and accessible languages
  • Apply standard vocabularies
  • Include qualified references
  • Use common data formats
  • Document the data
  • Ensure cross-platform compatibility
R
Reusable
  • Provide clear usage licenses
  • Include detailed provenance
  • Meet domain-relevant standards
  • Provide full documentation
  • Ensure data quality measures
  • Include methodological information

Data Sharing Benefits

Research Advancement
  • Enables verification and replication
  • Facilitates meta-analysis
  • Supports new research questions
  • Reduces duplication of effort
  • Speeds up scientific advancements
  • Improves research impact
Author Benefits
  • Increases citation rates
  • Provides greater visibility for research
  • Builds research collaborations
  • Supports career growth
  • Demonstrates research integrity
  • Meets funder requirements

Data Availability Requirements

Data Availability Statement

All manuscripts must include a Data Availability Statement describing data accessibility:

Statement Requirements:
  • Location of supporting data
  • Access conditions and restrictions
  • Repository names and identifiers
  • Embargo periods if applicable
  • Contact details for dataset access
  • Licensing information
Statement Examples:
Open Data: "Data available in [Repository] at [DOI]"
Restricted Data: "Data available on request due to [reason]"
Third-party Data: "Data from [source] used under license"
No Data: "No new data generated"
Simulated Data: "Code to generate the data included"

Data Types and Formats

Common Data Types
  • Survey and questionnaire data
  • Experimental results
  • Interview transcripts
  • Statistical datasets
  • Economic indicators
  • Business performance data
  • Social research data
  • Simulation data
Recommended Formats
  • Tabular Data: CSV, TSV, XLSX
  • Statistical Data: SAV, DTA, RDA
  • Qualitative Data: TXT, PDF, DOCX
  • Code/Scripts: R, Python, SQL
  • Documentation: PDF, README, CODEBOOK
  • Metadata: XML, JSON

Data Repository Recommendations

Recommended Data Repositories
General Repositories:
  • Zenodo: CERN-based multidisciplinary repository
  • Figshare: General research data repository
  • Dryad: Curated general-purpose repository
  • Mendeley Data: Elsevier's research data platform
  • Harvard Dataverse: Open data repository
  • OSF: Open Science Framework
Discipline-Specific:
  • ICPSR: Political and Social Research data
  • World Bank Data: Development and economic data
  • UK Data Service: Social and economic data
  • RePEc: Research Papers in Economics
  • Business & Economics: Institutional repositories
  • Subject-specific archives
Repository Selection Criteria
Persistence

Long-term preservation commitment

Stability

Reliable infrastructure and funding

Access

Appropriate access controls

Metadata

Rich metadata support

Identifiers

Persistent identifier assignment

Licensing

Clear options for usage licenses

Cost

Free or reasonable costs

Integration

Compatibility with research workflows

Data Documentation and Metadata

Required Documentation
  • Data collection methods
  • Variable definitions and codes
  • Measurement instruments
  • Sampling procedures
  • Data processing steps
  • Quality control measures
  • Usage restrictions
  • Citation directions
Metadata Standards
  • Dublin Core: Basic bibliographic metadata
  • DDI: Data Documentation Initiative
  • Schema.org: Web markup for datasets
  • DataCite: Repository metadata schema
  • Discipline-specific standards
  • Custom metadata as needed
Documentation Templates

We provide data documentation templates for the most common research types: surveys, experiments, and observational studies. To access templates and get documentation guidance, contact us at info@globalacademician.com

Ethical and Legal Considerations

Privacy Protection
  • Anonymize personal identifiers
  • Remove direct and indirect identifiers
  • Aggregate sensitive information
  • Use statistical disclosure control
  • Obtain informed consent to share
  • Follow institutional review board guidelines
Legal Compliance
  • GDPR for European data
  • National data protection laws
  • Institutional data policies
  • Funder data sharing requirements
  • Copyright and database rights
  • Contractual obligations
Sensitive Data Handling

For data that cannot be openly shared, consider these alternatives:

Access Controls:
  • Embargo periods for delayed release
  • Restricted access archives
  • Data use agreements
  • Application processes for access
  • Secure data enclaves
  • Virtual data access systems
Alternative Sharing:
  • Share synthetic or simulated data
  • Share data analysis code
  • Share aggregated results
  • Provide detailed methodology
  • Provide information on request
  • Use secure remote access systems

Data Licensing and Reuse

Recommended Licenses
CC0

Public domain dedication

CC BY

Attribution must be provided

ODC BY

Open Data Commons Attribution

ODbL

Open Database License

Custom Licenses

For specific needs

Repository Defaults

Repository-specific licenses

License Compatibility

Ensure data licenses are compatible with the CC BY 4.0 license used for articles. Choose licenses that maximize reuse while providing appropriate attribution and protection for sensitive data.

Data Policy Support

For inquiries on data sharing, selection of a repository, documentation, or policy compliance, please reach out to our data management team:

Subject Line Requirement

Please use "Research Data Policy" in the subject line and include information about your specific data management requirements.

If you have complicated data sharing scenarios or sensitive data to manage, we will provide you with personalized guidance.

Need Help?

Contact our data management team for personalized guidance on data sharing and compliance.

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