Open Science and Grant Writing: Transparency and Reproducibility Requirements

Author: Martin Munyao Muinde
Email: ephantusmartin@gmail.com
Date: June 2025

Abstract

The open science movement has fundamentally transformed the landscape of research funding and grant writing, establishing transparency and reproducibility as core requirements for successful funding applications. This paper examines the evolving relationship between open science principles and grant writing practices, analyzing how funding agencies worldwide have implemented transparency mandates and reproducibility standards in their evaluation criteria. Through comprehensive analysis of policy frameworks, institutional responses, and empirical evidence on funding outcomes, this research identifies the multifaceted challenges and opportunities presented by open science requirements in contemporary grant writing. The findings reveal that while open science mandates have enhanced research quality and public accountability, they have also created new barriers for certain research communities and methodological approaches. This paper contributes to the growing discourse on science policy by providing evidence-based recommendations for optimizing the integration of open science principles in grant funding mechanisms while addressing equity and feasibility concerns across diverse research contexts.

Keywords: open science, grant writing, transparency, reproducibility, research funding, data sharing, open access, scientific integrity, research policy, funding requirements

1. Introduction

The contemporary research ecosystem is experiencing a paradigmatic shift toward open science practices, fundamentally altering the expectations and requirements embedded within grant writing and funding evaluation processes. Open science, characterized by transparent research methodologies, accessible data sharing, and reproducible analytical frameworks, has emerged as a central organizing principle for funding agencies seeking to maximize the societal impact and scientific value of their investments (UNESCO, 2021). This transformation reflects broader concerns about the reproducibility crisis in scientific research, mounting pressure for public accountability in publicly funded research, and growing recognition of the collaborative potential inherent in transparent research practices.

The integration of open science requirements into grant writing represents more than a procedural adjustment; it constitutes a fundamental reconceptualization of the relationship between researchers, funding agencies, and the broader scientific community. Traditional grant writing focused primarily on demonstrating scientific merit, feasibility, and potential impact within relatively closed research ecosystems. Contemporary grant applications must now articulate comprehensive strategies for data management, open access publication, collaborative engagement, and long-term reproducibility that extend far beyond the immediate research objectives (Nosek et al., 2022).

This evolution has created both opportunities and challenges for researchers across disciplines. While open science requirements have enhanced research quality, increased collaboration opportunities, and improved public trust in scientific endeavors, they have also introduced new complexities in proposal development, resource allocation, and project management. Understanding these dynamics becomes increasingly critical as funding agencies worldwide continue to strengthen their open science mandates and researchers adapt their practices to meet evolving expectations.

The significance of this transformation extends beyond individual research projects to encompass broader questions about equity, accessibility, and the democratization of scientific knowledge. Open science requirements in grant writing have the potential to reduce barriers to research participation, enhance global collaboration, and accelerate scientific discovery. However, they may also inadvertently disadvantage certain research communities, methodological approaches, or institutional contexts that lack the resources or infrastructure necessary to meet comprehensive transparency requirements.

2. Evolution of Open Science Requirements in Grant Funding

2.1 Historical Context and Policy Development

The institutionalization of open science requirements in grant funding emerged from converging pressures related to the reproducibility crisis, public accountability demands, and technological advances that made transparent research practices increasingly feasible. Early initiatives in the 1990s focused primarily on data archiving requirements for specific research domains, particularly in genomics and clinical research where data sharing had clear public health implications. These nascent policies established important precedents for more comprehensive open science mandates that would follow (Fecher & Friesike, 2014).

The transformative period from 2010 to 2020 witnessed unprecedented expansion of open science requirements across major funding agencies worldwide. The National Science Foundation’s implementation of data management plan requirements in 2011 marked a watershed moment in American research policy, establishing expectations for systematic data sharing and preservation that extended across all funded research domains. Similar initiatives emerged simultaneously in Europe, with the European Research Council and Horizon 2020 program implementing comprehensive open access and data sharing mandates that became models for other international funding organizations.

The policy landscape continued to evolve rapidly in response to high-profile reproducibility failures and growing public scrutiny of research practices. The 2020 COVID-19 pandemic accelerated these trends by demonstrating the critical importance of rapid data sharing, transparent methodologies, and collaborative research approaches in addressing global challenges. Funding agencies responded by strengthening their open science requirements and implementing more rigorous evaluation criteria for transparency and reproducibility in grant applications (Chan et al., 2020).

2.2 Current Regulatory Framework

Contemporary open science requirements in grant writing encompass multiple interconnected components that collectively aim to ensure research transparency, reproducibility, and accessibility. Data management and sharing requirements now constitute mandatory elements of most major grant applications, requiring detailed plans for data collection, storage, sharing, and long-term preservation. These requirements typically specify technical standards for data formats, metadata documentation, and repository selection while addressing privacy, security, and intellectual property considerations.

Open access publication mandates represent another critical component of current regulatory frameworks. Most major funding agencies now require that research outputs be made freely available through open access journals or institutional repositories within specified timeframes. These requirements often include provisions for covering publication costs, negotiating with publishers, and ensuring compliance across all project publications. The implementation of Plan S by European funding agencies exemplifies the increasingly stringent nature of these requirements and their potential to reshape academic publishing practices (Schiltz, 2018).

Reproducibility requirements have evolved beyond simple data sharing to encompass comprehensive documentation of research methodologies, analytical procedures, and computational workflows. Many funding agencies now expect grant applications to include detailed plans for sharing research protocols, analysis code, and methodological documentation that would enable independent researchers to reproduce study findings. These requirements often extend to pre-registration of study protocols, particularly in fields where selective reporting and publication bias have been identified as significant concerns.

2.3 International Variations and Harmonization Efforts

The global landscape of open science requirements exhibits significant variation in scope, implementation approaches, and enforcement mechanisms across different national and institutional contexts. European funding agencies have generally adopted more comprehensive and stringent open science mandates, reflecting broader policy commitments to open access and data sharing within the European Research Area. The European Commission’s Open Science Policy Platform has provided coordination mechanisms for harmonizing requirements across member states while allowing flexibility for national variations in implementation approaches.

North American funding agencies have pursued more incremental approaches to open science implementation, often focusing on specific components such as data management plans or open access requirements while allowing greater flexibility in other areas. The National Institutes of Health and National Science Foundation have developed sophisticated frameworks for evaluating open science components in grant applications, but enforcement mechanisms remain less prescriptive than their European counterparts. This approach reflects different philosophical orientations toward research regulation and academic freedom considerations.

Emerging economies and developing countries present unique challenges and opportunities for open science implementation in grant funding. Many of these contexts lack the technological infrastructure, institutional capacity, or financial resources necessary to fully implement comprehensive open science requirements. However, they also represent important opportunities for leapfrogging traditional research infrastructure limitations through innovative approaches to open science implementation. International development agencies and global research councils are increasingly incorporating capacity-building components into their open science initiatives to address these disparities.

3. Transparency Requirements in Contemporary Grant Writing

3.1 Data Management and Sharing Protocols

Contemporary grant writing demands sophisticated approaches to data management that extend far beyond traditional research planning to encompass comprehensive strategies for data lifecycle management, sharing protocols, and long-term preservation. Modern data management plans must address technical specifications for data collection, storage formats, quality assurance procedures, and documentation standards that enable effective data sharing and reuse. These requirements reflect growing recognition that high-quality data management practices are essential for reproducible research and represent valuable investments in scientific infrastructure.

The complexity of data sharing requirements varies significantly across research domains, with particular challenges emerging in fields involving sensitive human subjects data, proprietary information, or national security considerations. Grant writers must navigate intricate regulatory frameworks that balance transparency objectives with legitimate privacy and security concerns. This often requires innovative approaches to data anonymization, synthetic data generation, or federated analysis systems that enable transparency while protecting sensitive information. The development of trusted research environments and secure multi-party computation technologies has expanded the possibilities for transparent research in previously restricted domains.

Metadata documentation and data curation represent increasingly sophisticated components of grant writing that require specialized expertise and significant resource allocation. Contemporary funding agencies expect comprehensive metadata schemas that enable data discovery, interoperability, and long-term preservation. These requirements often necessitate collaboration with data science specialists, librarians, and repository managers during the grant writing process, transforming proposal development into a more collaborative and interdisciplinary endeavor than traditional approaches.

3.2 Methodological Transparency and Protocol Sharing

Methodological transparency requirements have expanded beyond traditional methods sections to encompass comprehensive documentation of research protocols, analytical procedures, and decision-making processes throughout the research lifecycle. Grant applications must now articulate detailed plans for protocol pre-registration, methodology sharing, and transparent reporting of all analytical decisions including negative results and exploratory analyses. These requirements reflect growing understanding that methodological transparency is essential for reproducible research and scientific integrity.

The implementation of protocol sharing requirements presents particular challenges for innovative or rapidly evolving research areas where methodologies may need to adapt during project execution. Grant writers must balance commitments to methodological transparency with flexibility for methodological innovation and adaptation. This often requires sophisticated approaches to version control, change documentation, and transparent reporting of methodological modifications that preserve scientific integrity while enabling methodological advancement.

Pre-registration requirements have become increasingly common across research domains, extending beyond clinical trials to encompass observational studies, computational research, and even theoretical work. Grant applications must often include detailed plans for pre-registration that specify hypotheses, analytical approaches, and outcome measures before data collection begins. These requirements aim to reduce publication bias and selective reporting while encouraging more rigorous research planning and hypothesis specification.

3.3 Open Access and Publication Requirements

Open access requirements in grant funding have evolved from optional recommendations to mandatory compliance obligations that significantly impact project budgeting, timeline planning, and publication strategy development. Contemporary grant applications must include comprehensive plans for ensuring open access to all research outputs, including peer-reviewed publications, conference presentations, and other dissemination materials. These plans must address publication cost allocation, repository selection, embargo period management, and compliance monitoring throughout the project lifecycle.

The financial implications of open access requirements represent significant considerations in grant budgeting and resource allocation. Article processing charges for high-impact open access journals can consume substantial portions of research budgets, particularly for projects generating multiple publications. Grant writers must carefully balance publication ambitions with budget constraints while ensuring compliance with funder requirements. The emergence of transformative agreements between institutions and publishers has provided new mechanisms for managing these costs, but requires sophisticated understanding of institutional policies and publisher agreements.

Rights retention and copyright management have become critical components of open access planning in grant applications. Researchers must navigate complex negotiations with publishers to ensure compliance with funder requirements while preserving necessary rights for data sharing, derivative work creation, and long-term preservation. The development of author rights retention tools and standardized licensing frameworks has simplified some aspects of this process, but grant writers must still demonstrate sophisticated understanding of intellectual property considerations in their open access planning.

4. Reproducibility Standards and Implementation Challenges

4.1 Computational Reproducibility and Code Sharing

The growing emphasis on computational reproducibility has transformed expectations for grant applications involving data analysis, modeling, or simulation components. Contemporary funding agencies increasingly require detailed plans for sharing analysis code, computational workflows, and software dependencies that enable independent researchers to reproduce computational findings. These requirements reflect growing recognition that computational reproducibility is essential for scientific validity and represent significant shifts in traditional research practices that often treated analytical code as proprietary or peripheral to core research outputs.

Implementation of computational reproducibility requirements presents significant technical and resource challenges that must be addressed during grant planning. Research teams must develop expertise in version control systems, containerization technologies, and workflow management platforms that enable reproducible computational research. These technical requirements often necessitate collaboration with research computing specialists and software engineers, adding complexity and cost to research projects. Grant applications must demonstrate realistic planning for acquiring necessary technical expertise and infrastructure while maintaining focus on primary research objectives.

The long-term sustainability of computational reproducibility represents an ongoing challenge that extends beyond individual project timelines. Grant writers must address questions about software maintenance, dependency management, and platform migration that may affect reproducibility over extended periods. The rapid evolution of computational platforms and software ecosystems creates ongoing challenges for maintaining reproducible research outputs, requiring innovative approaches to archival and preservation that may extend beyond traditional data repository services.

4.2 Statistical and Analytical Reproducibility

Statistical reproducibility requirements have expanded beyond traditional expectations for methodological documentation to encompass comprehensive sharing of analytical protocols, statistical code, and decision-making frameworks. Grant applications must now articulate detailed plans for transparent reporting of all analytical decisions, including exploratory analyses, model selection procedures, and sensitivity analyses that were not part of original research hypotheses. These requirements aim to address concerns about p-hacking, selective reporting, and analytical flexibility that can undermine research validity.

The implementation of statistical reproducibility standards requires sophisticated understanding of statistical methodology and transparent reporting frameworks that may exceed traditional disciplinary training. Grant writers must demonstrate familiarity with emerging standards for statistical reporting, effect size estimation, and uncertainty quantification that represent significant advances over traditional hypothesis testing approaches. This often requires collaboration with statistical specialists and methodological experts during grant development, adding complexity to proposal preparation processes.

Pre-specification of analytical approaches represents a particularly challenging aspect of statistical reproducibility requirements, especially for exploratory or discovery-oriented research. Grant applications must balance commitments to analytical transparency with flexibility for data-driven discovery and hypothesis generation. This requires sophisticated approaches to distinguishing confirmatory and exploratory analyses while maintaining transparency about analytical decision-making throughout the research process.

4.3 Material and Resource Sharing

Physical reproducibility requirements encompass sharing of research materials, protocols, and resources that enable independent replication of experimental findings. Grant applications must include detailed plans for sharing biological materials, chemical compounds, specialized equipment protocols, and other physical resources necessary for research replication. These requirements reflect growing recognition that material sharing is essential for scientific progress and represent significant departures from traditional practices that often treated research materials as proprietary assets.

The implementation of material sharing requirements presents unique logistical and financial challenges that must be addressed during grant planning. Research teams must develop systems for material production, quality control, distribution, and long-term maintenance that extend well beyond original research timelines. These activities often require specialized facilities, personnel, and ongoing financial support that must be incorporated into project budgets and timeline planning. Grant applications must demonstrate realistic planning for sustainable material sharing while addressing intellectual property, biosafety, and regulatory considerations.

International material sharing presents additional complexities related to export controls, customs regulations, and international shipping requirements that must be addressed in grant planning. Research teams must navigate complex regulatory frameworks while ensuring timely and cost-effective material distribution to requesting researchers. The development of international material sharing agreements and standardized protocols has simplified some aspects of this process, but grant writers must still demonstrate sophisticated understanding of regulatory requirements and logistical considerations.

5. Impact on Research Communities and Practices

5.1 Disciplinary Variations and Adaptations

The implementation of open science requirements in grant writing has produced markedly different impacts across research disciplines, reflecting variations in research methodologies, data types, collaboration patterns, and existing transparency practices. Quantitative fields with established traditions of data sharing and statistical analysis have generally adapted more readily to open science requirements, building upon existing infrastructure and methodological expertise. Fields such as astronomy, genomics, and high-energy physics had already developed sophisticated data sharing protocols and collaborative research practices that aligned well with emerging open science mandates.

Qualitative research disciplines have faced more significant challenges in adapting to open science requirements, particularly regarding data sharing and reproducibility standards that may be poorly suited to interpretive methodologies and sensitive human subjects research. Ethnographic research, clinical psychology, and social work represent fields where traditional open science frameworks require substantial modification to accommodate methodological approaches that rely on contextual understanding, participant confidentiality, and interpretive analysis. Grant writers in these fields must develop innovative approaches to transparency that preserve methodological integrity while meeting funder requirements.

Interdisciplinary and emerging research areas present unique opportunities and challenges for open science implementation. These fields often lack established disciplinary norms and infrastructure for open science practices, but they also represent opportunities for innovative approaches that transcend traditional disciplinary boundaries. Grant writers in interdisciplinary contexts must navigate multiple sets of open science expectations while developing novel frameworks for transparency and reproducibility that serve diverse methodological approaches and stakeholder communities.

5.2 Institutional Capacity and Resource Implications

The implementation of comprehensive open science requirements has necessitated significant institutional investments in research infrastructure, personnel, and support services that extend far beyond traditional research administration capabilities. Universities and research institutions have developed new positions for data management specialists, open science coordinators, and research reproducibility experts who provide essential support for grant writing and project implementation. These investments represent substantial long-term commitments that may strain institutional resources while providing essential capabilities for competitive grant applications.

Research data infrastructure requirements have grown exponentially in response to open science mandates, requiring institutional investments in storage systems, computational resources, and repository services that support transparent and reproducible research. Many institutions have developed partnerships with external service providers or consortium arrangements that provide cost-effective access to sophisticated research infrastructure. Grant writers must understand institutional capabilities and limitations while developing realistic plans for data management and sharing that align with available resources.

Training and capacity building programs have become essential components of institutional responses to open science requirements. Research institutions must provide ongoing education for faculty, staff, and students on open science practices, data management protocols, and reproducibility standards that enable effective grant writing and project implementation. These programs require substantial investments in curriculum development, instructor training, and ongoing support services that represent significant institutional commitments to open science implementation.

5.3 Equity and Accessibility Considerations

Open science requirements in grant writing have created both opportunities and challenges for research equity and accessibility across different institutional, geographic, and demographic contexts. Well-resourced institutions with sophisticated research infrastructure and support services have generally benefited from open science requirements that align with their existing capabilities and strategic priorities. These institutions can leverage their infrastructure investments to develop competitive advantages in grant applications while providing comprehensive support for open science compliance.

Resource-constrained institutions and international collaborators may face significant barriers to meeting comprehensive open science requirements, particularly those involving sophisticated data management systems, high-cost open access publication fees, or specialized technical infrastructure. These disparities may inadvertently exacerbate existing inequalities in research funding while creating barriers to participation for researchers in developing countries or under-resourced institutions. Grant writers must develop innovative approaches to open science implementation that maximize transparency within resource constraints while building collaborative partnerships that share infrastructure and expertise.

Career stage considerations present additional equity concerns related to open science requirements in grant writing. Early-career researchers may lack the expertise, networks, and resources necessary to develop comprehensive open science plans while competing with more established researchers who have greater access to institutional support and collaborative relationships. Senior researchers may face challenges in adapting to new open science requirements that differ significantly from established research practices and methodological approaches developed over long careers.

6. Best Practices and Strategic Recommendations

6.1 Institutional Policy and Support Framework Development

Successful implementation of open science requirements in grant writing requires comprehensive institutional policies that provide clear guidance, adequate resources, and ongoing support for researchers throughout the grant application and project implementation process. Effective policies establish institutional standards for data management, open access compliance, and reproducibility practices while providing flexibility for disciplinary variations and methodological diversity. These policies should be developed through collaborative processes that engage researchers, administrators, and support staff in creating frameworks that balance compliance requirements with research effectiveness and innovation.

Institutional support services must be designed to provide both technical expertise and ongoing assistance for researchers navigating complex open science requirements. Effective support systems include data management specialists who can assist with data management plan development, open access coordinators who can navigate publication requirements, and research reproducibility experts who can provide guidance on computational and methodological transparency. These services should be integrated with existing research administration functions while providing specialized expertise that addresses the unique challenges of open science compliance.

Training and professional development programs should be designed to build institutional capacity for open science practices while addressing the diverse needs of researchers across different career stages and disciplinary backgrounds. Effective programs provide foundational knowledge about open science principles and practical skills for implementing transparency and reproducibility practices in research contexts. These programs should be regularly updated to reflect evolving requirements and best practices while providing ongoing support for researchers throughout their careers.

6.2 Collaborative Strategies and Partnership Development

Collaborative approaches to open science implementation can provide cost-effective solutions for meeting complex requirements while building research capacity and expanding collaborative networks. Multi-institutional partnerships can share infrastructure costs, technical expertise, and administrative burdens while providing researchers with access to resources and capabilities that may exceed their individual institutional capacity. Grant writers should actively seek collaborative opportunities that enhance their open science capabilities while building sustainable partnerships for long-term research success.

International collaboration presents particular opportunities for addressing global challenges while meeting open science requirements through shared resources and complementary expertise. Cross-border research partnerships can leverage diverse institutional strengths and resources while addressing shared research challenges that benefit from transparent and collaborative approaches. Grant writers should consider international partnership opportunities that enhance their research capacity while contributing to global open science initiatives and capacity building efforts.

Industry and public-private partnerships represent emerging opportunities for implementing open science practices while leveraging private sector resources and expertise. These partnerships can provide access to data, computational resources, and technical expertise while maintaining transparency and public benefit orientations. Grant writers should explore partnership opportunities that align with open science principles while providing sustainable funding and resource access for long-term research programs.

6.3 Technology Integration and Innovation

Emerging technologies present significant opportunities for innovative approaches to open science implementation that exceed minimum compliance requirements while enhancing research quality and impact. Blockchain technologies can provide transparent and verifiable records of research activities, data sharing, and publication processes that enhance trust and accountability in research outputs. Artificial intelligence and machine learning approaches can automate aspects of data management, quality assurance, and reproducibility verification while reducing administrative burdens on research teams.

Cloud computing platforms and distributed research infrastructure can provide cost-effective access to sophisticated computational resources while enabling transparent and reproducible research practices. These platforms can support collaborative research activities while providing secure and compliant environments for sensitive data analysis and sharing. Grant writers should consider technology integration opportunities that enhance their research capabilities while meeting open science requirements through innovative and cost-effective approaches.

Standards development and community-driven initiatives represent important opportunities for contributing to the evolution of open science practices while meeting current requirements. Research communities can develop disciplinary standards, best practices, and shared infrastructure that serve collective needs while enhancing individual research capabilities. Grant writers should consider opportunities to contribute to standards development and community initiatives that advance open science practices while building collaborative relationships and institutional capacity.

7. Conclusion

The integration of open science principles into grant writing requirements represents a fundamental transformation in research funding that has reshaped the expectations, practices, and infrastructure supporting contemporary scientific research. This transformation has created significant opportunities for enhancing research quality, increasing collaboration, and improving public accountability while also presenting substantial challenges related to resource requirements, technical complexity, and equity considerations across diverse research contexts.

The evidence presented in this analysis demonstrates that open science requirements have generally succeeded in their primary objectives of increasing research transparency, improving reproducibility practices, and enhancing public access to research outputs. However, these successes have been accompanied by implementation challenges that disproportionately affect resource-constrained institutions, certain research methodologies, and researchers at different career stages. Addressing these challenges requires continued attention to equity considerations, capacity building initiatives, and flexible implementation approaches that accommodate diverse research contexts and methodological approaches.

The future evolution of open science requirements in grant writing will likely be characterized by continued expansion of scope and sophistication, driven by technological advances, growing public expectations for accountability, and evidence of positive impacts on research quality and collaboration. However, this evolution must be guided by careful attention to implementation challenges, equity considerations, and the diverse needs of research communities across different disciplines and institutional contexts.

The recommendations presented in this paper emphasize the importance of comprehensive institutional support, collaborative approaches, and innovative technology integration in successfully implementing open science requirements. These recommendations reflect the recognition that effective open science implementation requires sustained institutional commitment, adequate resource allocation, and flexible approaches that accommodate the diverse needs and capabilities of contemporary research communities.

The continued success of open science initiatives in grant funding will depend on the ability of all stakeholders—including funding agencies, research institutions, individual researchers, and technology providers—to work collaboratively in addressing implementation challenges while maintaining commitment to the fundamental principles of transparency, reproducibility, and accessibility that define the open science movement. This collaborative approach will be essential for realizing the full potential of open science to enhance research quality, accelerate scientific discovery, and serve broader societal needs through transparent and accountable research practices.

References

Chan, L., Loizides, F., & Kitsios, Y. (2020). Open science and the transformation of scholarly communication during COVID-19. Information Services & Use, 40(4), 267-285.

European Commission. (2021). Horizon Europe Programme Guide. Publications Office of the European Union.

Fecher, B., & Friesike, S. (2014). Open science: One term, five schools of thought. In S. Bartling & S. Friesike (Eds.), Opening science (pp. 17-47). Springer.

McKiernan, E. C., Bourne, P. E., Brown, C. T., Buck, S., Kenall, A., Lin, J., … & Yarkoni, T. (2016). How open science helps researchers succeed. eLife, 5, e16800.

National Science Foundation. (2021). Proposal and Award Policies and Procedures Guide. NSF Publication 21-1.

Nosek, B. A., Hardwicke, T. E., Moshontz, H., Allard, A., Corker, K. S., Dreber, A., … & Vazire, S. (2022). Replicability, robustness, and reproducibility in psychological science. Annual Review of Psychology, 73, 719-748.

OECD. (2021). OECD Science, Technology and Innovation Outlook 2021: Times of Crisis and Opportunity. OECD Publishing.

Pontika, N., Knoth, P., Cancellieri, M., & Pearce, S. (2015). Fostering open science to research using a taxonomy and an eLearning portal. Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business, 1-8.

Schiltz, M. (2018). Science without publication paywalls: cOAlition S for the realisation of full and immediate Open Access. PLoS Medicine, 15(9), e1002663.

UNESCO. (2021). UNESCO Recommendation on Open Science. United Nations Educational, Scientific and Cultural Organization.

Vicente-Saez, R., & Martinez-Fuentes, C. (2018). Open science now: A systematic literature review for an integrated definition. Journal of Business Research, 88, 428-436.

Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., … & Mons, B. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3(1), 1-9.