8. Data and Code Availability

Data and Code Availability is a cornerstone for fostering transparency, reproducibility, and collaborative innovation in academic publishing. Nexus Journals is committed to upholding the highest standards in data and code sharing, ensuring that research outputs are accessible, reusable, and interoperable. This section comprehensively outlines the policies, practices, and strategic initiatives that Nexus Journals employs to facilitate effective data and code availability, reflecting the latest advancements and best practices in scholarly communication.

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8.1 Importance of Data and Code Availability

Ensuring that data and code used in research are publicly available is fundamental to the integrity and advancement of scientific knowledge. Nexus Journals emphasizes the following critical aspects:

1. Reproducibility:

   • Objective: Enable other researchers to replicate and validate findings.

   • Implementation: By providing access to the underlying data and analytical code, Nexus Journals ensures that studies can be independently verified, fostering trust in the research outcomes.

2. Transparency:

   • Objective: Enhance the credibility and trustworthiness of published research.

   • Implementation: Open access to data and code demystifies the research process, allowing stakeholders to scrutinize methodologies and analyses, thereby reinforcing the robustness of the findings.

3. Collaboration:

   • Objective: Facilitate further research and innovation through shared resources.

   • Implementation: Publicly available data and code serve as valuable resources for the academic community, encouraging collaborative efforts, meta-analyses, and the development of new methodologies.

4. Efficiency:

   • Objective: Reduce duplication of effort and accelerate scientific discovery.

   • Implementation: Sharing data and code allows researchers to build upon existing work without redundant data collection or code development, streamlining the research process.

5. Educational Value:

   • Objective: Serve as learning tools for students and emerging researchers.

   • Implementation: Access to real-world data and code examples provides practical insights into research methodologies and computational techniques.

Contextual Implementation at Nexus Journals: Nexus Journals integrates these principles into its publication framework by mandating data and code availability as essential components of the submission process. This integration ensures that published research not only contributes novel insights but also provides the necessary tools for the academic community to build upon these foundations.

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8.2 Data Sharing Policies

Adhering to the FAIR Principles—Findable, Accessible, Interoperable, and Reusable—is central to Nexus Journals’ data sharing policies. These principles guide the effective management and dissemination of research data, ensuring that they are of maximum utility to the scientific community.

1. Findable:

   • Policy: Data should be easily discoverable through standardized metadata and indexing.

   • Implementation:

     • Metadata Standards: Authors must provide comprehensive metadata that adheres to standardized formats (e.g., Dublin Core, DataCite), facilitating easy discovery via search engines and repository tools.

     • Persistent Identifiers: Assign DOIs or other persistent identifiers to datasets to ensure they can be reliably located and cited.

2. Accessible:

   • Policy: Data must be available through open-access repositories or upon reasonable request.

   • Implementation:

     • Repository Selection: Authors are encouraged to deposit data in reputable open-access repositories (e.g., Zenodo, Figshare) that ensure long-term accessibility.

     • Access Conditions: When data cannot be made openly accessible due to privacy or proprietary constraints, authors must provide clear instructions on how to access the data upon reasonable request, including any necessary permissions or agreements.

3. Interoperable:

   • Policy: Data should be compatible with various platforms and formats to enable seamless integration and analysis.

   • Implementation:

     • Standard Formats: Authors should use widely accepted data formats (e.g., CSV, JSON, XML) and ensure that data structures are well-documented to facilitate interoperability.

     • APIs and Documentation: Provide APIs or detailed documentation that allows other researchers to interact with the data programmatically, enhancing usability across different systems.

4. Reusable:

   • Policy: Data should be well-documented and licensed to allow for reuse in different contexts.

   • Implementation:

     • Comprehensive Documentation: Include detailed data dictionaries, codebooks, and methodological descriptions to ensure that data can be understood and utilized effectively by others.

     • Licensing: Apply clear and appropriate licenses (e.g., Creative Commons licenses) that specify the terms under which data can be reused, modified, and redistributed.

Contextual Implementation at Nexus Journals: Nexus Journals mandates adherence to the FAIR principles through its submission guidelines, ensuring that all published research data meets these standards. The journal provides detailed instructions and resources to assist authors in preparing their data for sharing, thereby promoting best practices in data management and dissemination.

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8.3 Code Availability Requirements

In addition to data sharing, making research code publicly available is crucial for ensuring the reproducibility and transparency of computational analyses. Nexus Journals enforces stringent requirements to facilitate the effective sharing of code used in research studies.

1. Share Code:

   • Policy: Authors must provide access to the code used in their analyses, ensuring it is well-documented and functional.

   • Implementation:

     • Supplementary Materials: Code can be included as supplementary materials or linked to through established repositories.

     • Documentation: Authors must include comprehensive documentation, including installation instructions, usage examples, and comments within the code to facilitate understanding and use by others.

2. Use Reputable Repositories:

   • Policy: Deposit code in recognized platforms such as GitHub, GitLab, or Bitbucket, with appropriate version control.

   • Implementation:

     • Version Control: Utilize version control systems to track changes, manage updates, and enable collaborative development.

     • Public Access: Ensure that repositories are set to public access unless there are compelling reasons to restrict access, in which case, clear access instructions must be provided.

3. License Appropriately:

   • Policy: Assign clear licensing terms (e.g., MIT, GPL) to facilitate legal and ethical reuse of the code.

   • Implementation:

     • License Selection: Authors must select an appropriate open-source license that defines the permissible uses and modifications of their code.

     • License Documentation: Include a LICENSE file within the repository and reference the chosen license within the manuscript to ensure clarity on usage rights.

Contextual Implementation at Nexus Journals: Nexus Journals requires authors to submit their code alongside their manuscripts, adhering to the outlined requirements. The journal provides guidance on selecting suitable repositories and licenses, ensuring that shared code is both accessible and reusable, thereby enhancing the overall impact and utility of the published research.

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8.4 Data Repositories

Choosing the right repository is essential for ensuring the longevity, accessibility, and discoverability of shared data and code. Nexus Journals encourages the use of reputable data repositories that align with the FAIR principles and support the specific needs of various research disciplines.

Recommended Repositories:

1. Zenodo:

   • Description: A versatile repository for a wide range of research data and software.

   • Features:

     • Assigns DOIs to datasets and code repositories.

     • Integrates seamlessly with GitHub for automated deposition.

     • Supports a variety of file types and metadata standards.

2. Figshare:

   • Description: A platform for datasets, figures, and other research outputs.

   • Features:

     • Provides DOIs for all uploads.

     • Facilitates easy sharing and embedding of data in publications.

     • Supports multimedia and interactive data formats.

3. Dryad:

   • Description: Specializes in curated, open-access research data.

   • Features:

     • Ensures data undergoes quality checks before deposition.

     • Assigns DOIs for persistent citation.

     • Integrates with numerous publishing platforms for streamlined workflows.

4. GitHub:

   • Description: A leading platform for version-controlled code repositories.

   • Features:

     • Supports collaboration through branching, pull requests, and issue tracking.

     • Integrates with CI/CD tools for automated testing and deployment.

     • Facilitates community contributions and open-source development.

5. Institutional Repositories:

   • Description: Repositories managed by academic institutions.

   • Features:

     • Often tailored to specific disciplinary needs.

     • May provide additional support and services for data management.

     • Enhance institutional visibility and data stewardship.

Contextual Implementation at Nexus Journals: Nexus Journals mandates that authors deposit their data and code in recognized repositories, specifying the chosen repository within their manuscript submission. The journal maintains a curated list of recommended repositories and provides links and instructions to facilitate seamless data and code deposition, ensuring compliance with data sharing policies. Additionally, Nexus Journals offers support through detailed guides and tutorials to help authors navigate repository selection and deposition processes effectively.

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8.5 Metadata Standards

Comprehensive metadata is essential for the effective discovery, interpretation, and reuse of research data and code. Nexus Journals requires authors to provide detailed metadata that accompanies their datasets and code, enhancing their utility and interoperability.

Required Metadata Components:

1. Descriptive Information:

   • Details: Titles, authors, affiliations, abstracts, and keywords.

   • Purpose: Facilitate the identification and understanding of the dataset or code’s context and content.

2. Technical Details:

   • Details: Data collection methods, formats, structures, variables, units of measurement, and any preprocessing steps.

   • Purpose: Ensure that users can comprehend the technical aspects of the data or code, enabling accurate analysis and replication.

3. Usage Instructions:

   • Details: Guidelines on how to access, interpret, and utilize the data and code, including any dependencies or software requirements.

   • Purpose: Provide clear instructions to users, enhancing the ease of reuse and integration into their own research.

4. Licensing Information:

   • Details: Specific licenses applied to the data and code, outlining permissible uses and restrictions.

   • Purpose: Clarify the legal terms under which data and code can be accessed and reused, ensuring compliance with ethical and legal standards.

5. Versioning Information:

   • Details: Version numbers, update histories, and change logs.

   • Purpose: Track the evolution of datasets and code, facilitating reproducibility and proper citation of specific versions.

6. Provenance Information:

   • Details: Detailed descriptions of the data’s origins, including sources, authorship, and any transformations undergone.

   • Purpose: Establish the data’s lineage, providing context and ensuring traceability of data modifications and analyses.

Contextual Implementation at Nexus Journals: Nexus Journals integrates metadata requirements into its submission guidelines, outlining the specific information authors must include when sharing data and code. The journal provides templates and examples of well-documented metadata to assist authors in preparing comprehensive and standardized metadata, thereby promoting consistency and facilitating the effective use of shared resources. Additionally, Nexus Journals collaborates with repository providers to ensure that metadata submission processes are streamlined and user-friendly.

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8.6 Licensing and Copyright

Proper licensing is crucial to define the terms under which data and code can be accessed, reused, and modified. Nexus Journals advocates for the use of open licenses that balance accessibility with the protection of authors’ rights, ensuring that research outputs are shared responsibly and ethically.

1. Creative Commons Licenses:

   • Policy: Nexus Journals promotes the use of Creative Commons licenses (e.g., CC BY, CC0) to facilitate broad dissemination and reuse of research outputs while protecting authors’ rights.

   • Implementation:

     • License Selection: Authors must select an appropriate Creative Commons license based on their sharing preferences and the desired level of reuse.

     • License Documentation: Include the chosen license in the repository’s metadata and reference it within the manuscript to ensure clarity on usage rights.

     • Public Access: Ensure that licenses are clearly visible and accessible alongside the data and code to inform potential users of the terms.

2. Open-Source Software Licenses:

   • Policy: For code sharing, authors must assign clear open-source licenses (e.g., MIT, GPL, Apache 2.0) to define the permissible uses and modifications of their software.

   • Implementation:

     • License Inclusion: Authors should include a LICENSE file within their code repository, specifying the chosen license and its terms.

     • Compliance: Ensure that all dependencies and third-party libraries used in the code are compatible with the selected license, avoiding legal conflicts.

3. Institutional and Funder Requirements:

   • Policy: Adhere to any additional licensing or copyright requirements imposed by institutional policies or research funders.

   • Implementation:

     • Compliance Checks: Authors must review and comply with institutional guidelines and funder mandates regarding data and code sharing.

     • Documentation: Provide evidence of compliance, such as signed data management plans or funder agreements, when required.

Contextual Implementation at Nexus Journals: Nexus Journals provides detailed guidance on selecting suitable licenses, including links to license descriptions and tools for generating license texts. The journal emphasizes the importance of clear licensing to facilitate legal and ethical reuse, ensuring that authors understand their obligations and the rights granted to users of their data and code. Additionally, Nexus Journals collaborates with legal experts to update its policies in response to evolving licensing standards and legal frameworks.

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8.7 Data Citation

Proper citation of data and code is essential to acknowledge the contributions of data providers and to enable traceability and reproducibility in research. Nexus Journals mandates specific practices to ensure accurate and consistent data citation.

1. Cite Data Properly:

   • Policy: Authors must provide appropriate citations for datasets and code repositories used or produced in their research.

   • Implementation:

     • Citation Formats: Follow standardized citation formats (e.g., DataCite) that include essential elements such as author names, publication year, title, repository name, and DOI.

     • Manuscript Integration: Include data and code citations within the manuscript’s references section, ensuring they are linked to the relevant sections of the text.

2. Assign DOIs:

   • Policy: Ensure that shared datasets and code repositories have Digital Object Identifiers (DOIs) for persistent and accurate citation.

   • Implementation:

     • Repository Use: Authors must deposit their data and code in repositories that assign DOIs, ensuring that citations remain valid and accessible over time.

     • DOI Inclusion: Reference the assigned DOI within the manuscript and metadata to facilitate seamless citation and access.

3. Data Citation Best Practices:

   • Granularity: Cite specific versions or snapshots of datasets and code to ensure that others can replicate the exact conditions of the research.

   • Accessibility: Make data and code citations easily accessible through hyperlinks in the digital version of the manuscript, enhancing usability for readers.

Contextual Implementation at Nexus Journals: Nexus Journals includes specific instructions and examples for data and code citation within its author guidelines. The journal encourages the use of reference management tools that support data citation formats, facilitating seamless integration of data and code references into manuscripts. Additionally, Nexus Journals verifies the presence of DOIs in cited repositories during the editorial process to ensure citation accuracy and persistence. The journal also provides support through citation guides and resources, helping authors navigate the complexities of data and code citation effectively.

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8.8 Privacy and Ethical Considerations

When handling sensitive or personal data, it is imperative to uphold ethical standards and protect the privacy of individuals. Nexus Journals enforces strict guidelines to ensure that data sharing complies with ethical norms and legal requirements, safeguarding the rights and confidentiality of data subjects.

1. Sensitive Data:

   • Policy: When dealing with sensitive or personal data, authors must implement measures to protect privacy and comply with relevant regulations.

   • Implementation:

     • Informed Consent: Obtain explicit informed consent from data subjects where applicable, detailing how their data will be used and shared.

     • Data Minimization: Collect only the data necessary for the research objectives, reducing the risk of unnecessary exposure of personal information.

     • Ethical Approvals: Provide documentation of ethical approvals (e.g., Institutional Review Board approvals) when required.

2. Anonymization Techniques:

   • Policy: Ensure that all personal identifiers are removed or obfuscated to prevent re-identification of individuals.

   • Implementation:

     • De-identification: Remove direct identifiers (e.g., names, addresses) and apply techniques such as data masking, pseudonymization, and aggregation to minimize the risk of re-identification.

     • Secure Processing: Handle sensitive data in secure environments, employing encryption and access controls to prevent unauthorized access.

3. Compliance with Regulations:

   • Policy: Adhere to international and regional data protection laws governing the collection, storage, and sharing of personal data (e.g., GDPR, HIPAA).

   • Implementation:

     • Legal Adherence: Ensure that data sharing practices comply with all applicable legal frameworks, providing evidence of compliance through documentation and certifications when required.

     • Data Transfer Safeguards: Implement safeguards for data transfers across borders, ensuring that data protection standards are maintained in different jurisdictions.

4. Ethical Data Sharing:

   • Policy: Promote ethical data sharing practices that respect the rights and dignity of individuals.

   • Implementation:

     • Transparency: Clearly communicate data sharing practices to data subjects and obtain their consent where necessary.

     • Responsibility: Maintain accountability for the ethical use and distribution of shared data, addressing any breaches or ethical concerns promptly and effectively.

Contextual Implementation at Nexus Journals: Nexus Journals mandates that authors address privacy and ethical considerations as part of their data sharing practices. Submissions involving sensitive data must include statements confirming compliance with ethical guidelines and data protection regulations. The journal provides resources and guidelines to assist authors in navigating ethical data sharing, ensuring that all shared data respects the rights and privacy of individuals. Additionally, Nexus Journals collaborates with institutional ethics boards and legal advisors to stay abreast of evolving regulations and ethical standards, ensuring that its policies remain robust and comprehensive.

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8.9 Data Management Plans

A Data Management Plan (DMP) outlines how data will be handled both during and after the research project. Nexus Journals encourages authors to develop and include DMPs, promoting responsible data management and sharing practices that align with the journal’s commitment to reproducibility and transparency.

1. Data Collection:

   • Details: Methods and sources of data acquisition, including sampling techniques, instruments used, and protocols followed.

   • Implementation: Authors should describe how data were collected, ensuring that the processes are robust, ethical, and well-documented to facilitate replication and validation.

2. Data Storage:

   • Details: Strategies for secure data storage, including data formats, backup procedures, and access controls.

   • Implementation: Outline where and how data are stored, ensuring that storage solutions are secure, reliable, and compliant with relevant data protection regulations.

3. Data Sharing:

   • Details: Plans for data dissemination and accessibility, including repository selection, access conditions, and any restrictions based on ethical or legal considerations.

   • Implementation: Specify how data will be shared, the repositories to be used, and the terms of access, ensuring that data sharing practices are aligned with the FAIR principles and journal policies.

4. Data Preservation:

   • Details: Long-term preservation strategies to ensure data remain accessible and usable over time.

   • Implementation: Describe measures for data preservation, such as selecting repositories with strong data retention policies and ensuring data formats are sustainable and widely supported.

5. Data Documentation:

   • Details: Comprehensive documentation to accompany data, including metadata, data dictionaries, and methodological descriptions.

   • Implementation: Provide detailed documentation that enables other researchers to understand, interpret, and reuse the data effectively.

Contextual Implementation at Nexus Journals: Nexus Journals recommends that authors include a DMP as part of their manuscript submission, particularly for projects funded by organizations that require detailed data management documentation. The journal provides templates and examples of effective DMPs, guiding authors in articulating their data management strategies comprehensively. Additionally, Nexus Journals integrates DMP evaluation into its review process, ensuring that data management practices meet the journal’s standards for transparency and reproducibility. The journal also offers support through workshops and online resources to assist authors in developing robust DMPs that align with best practices and regulatory requirements.

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8.10 Continuous Improvement in Data Practices

Nexus Journals is steadfast in its commitment to the ongoing enhancement of its data and code availability policies, recognizing the dynamic nature of research practices and technological advancements. This commitment ensures that the journal remains at the forefront of best practices in data management and sharing, fostering an environment of excellence and adaptability.

Strategies for Continuous Improvement:

1. Updating Policies:

   • Objective: Regularly revise data and code availability policies to align with emerging standards, technologies, and community expectations.

   • Implementation: Conduct annual reviews of policies, incorporating feedback from authors, reviewers, and stakeholders to ensure they remain relevant and effective.

2. Educating Authors:

   • Objective: Provide resources and training to support authors in effective data and code management.

   • Implementation: Offer workshops, webinars, and detailed guides on data management, sharing practices, and repository usage, empowering authors to comply with policies confidently.

3. Encouraging Best Practices:

   • Objective: Promote adherence to best practices in data sharing and reproducibility across all submissions.

   • Implementation: Highlight exemplary data and code sharing practices in communications, recognize authors who excel in data management, and integrate best practice guidelines into submission requirements.

4. Technological Integration:

   • Objective: Leverage technological advancements to streamline data and code sharing processes.

   • Implementation:

     • Automation Tools: Implement advanced software solutions to facilitate manuscript tracking, reviewer assignments, and data/code deposition.

     • AI Integration: Explore the use of artificial intelligence (AI) to assist in preliminary screenings, plagiarism detection, and matching manuscripts with appropriate reviewers.

5. Feedback Mechanisms:

   • Objective: Continuously gather and incorporate feedback from the academic community to refine data practices.

   • Implementation: Utilize surveys, focus groups, and feedback forms to collect insights from authors, reviewers, and editors, using this data to inform policy updates and process improvements.

6. Policy Refinement:

   • Objective: Continuously refine ethical guidelines to address new challenges and uphold high standards of data management.

   • Implementation: Update guidelines to reflect evolving data protection laws, technological innovations, and community standards, ensuring that policies are comprehensive and forward-thinking.

7. Diversity and Inclusion:

   • Objective: Foster a diverse and inclusive data sharing ecosystem by actively recruiting experts from varied backgrounds and disciplines.

   • Implementation: Implement recruitment strategies that prioritize diversity in the reviewer pool, provide support for underrepresented groups, and promote inclusive data sharing practices.

8. Global Outreach:

   • Objective: Expand the reach and impact of data sharing practices on a global scale.

   • Implementation: Engage with international research communities, participate in global data sharing initiatives, and collaborate with international repositories to enhance the accessibility and interoperability of shared data.

Best Practices Inspired by GCRI:

• Proactive Adaptation: Stay ahead of emerging trends and incorporate relevant innovations into the data and code availability process, ensuring that Nexus Journals remains cutting-edge and responsive to the needs of the academic community.

• Collaborative Ecosystem: Foster a collaborative environment where technological advancements and community feedback drive the evolution of data practices, similar to GCRI’s collaborative approach to resilience initiatives.

Contextual Practices at Nexus Journals: By embracing these continuous improvement strategies, Nexus Journals ensures that its data and code availability policies remain robust, dynamic, and aligned with the latest advancements in data management and sharing. The journal’s editorial team collaborates with data management experts, participates in relevant forums and working groups, and actively seeks out opportunities to integrate new technologies and methodologies into its data practices. This proactive stance ensures that Nexus Journals’ data and code availability framework meets current standards and anticipates future developments, fostering a culture of excellence and innovation in scholarly publishing.

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Data and Code Availability is integral to the mission of Nexus Journals, underpinning the principles of reproducibility, transparency, and collaborative innovation. By adhering to the FAIR principles, implementing stringent data sharing and code availability requirements, and fostering continuous improvement in data practices, Nexus Journals ensures that published research is not only impactful but also accessible and usable by the broader scientific community. These comprehensive policies and practices reinforce the journal’s commitment to advancing knowledge, enhancing research integrity, and promoting a collaborative academic ecosystem that drives global resilience and sustainability.