Open Science and Reproducibility
Open Science and reproducibility are fundamental pillars of modern scientific practice, ensuring that results can be independently verified, reused, and built upon across domains. As European scientific communities move toward exascale data volumes and increasingly complex AI-enhanced workflows, the ability to preserve, share, and reproduce results becomes both more challenging and more essential. In an environment where scientific discovery is data-driven, collaboration-intensive, and reliant on heterogeneous infrastructures, reproducibility emerges as a prerequisite for trust, transparency. Evidence from major SPECTRUM research communities shows that only infrastructures with FAIR-by-design principles, robust provenance tracking, and transparent workflow environments can support long-term scientific value and compliance with open science mandates. For SPECTRUM, Open Science and reproducibility are core enabling conditions for a truly interoperable, cross-domain compute and data continuum. They ensure that scientific knowledge generated in Europe remains accessible, verifiable, and re-usable across communities and generations of infrastructure and crucial way to ensure European sovereignty for research outputs including data, research software and workflows
Strategic Rationale and Evidence Base
Strategic Importance
Open Science and reproducibility are fundamental pillars of modern scientific practice, ensuring that results can be independently verified, reused, and built upon across domains. As European scientific communities move toward exascale data volumes and increasingly complex AI-enhanced workflows, the ability to preserve, share, and reproduce results becomes both more challenging and more essential. In an environment where scientific discovery is data-driven, collaboration-intensive, and reliant on heterogeneous infrastructures, reproducibility emerges as a prerequisite for trust, transparency. Evidence from major SPECTRUM research communities shows that only infrastructures with FAIR-by-design principles, robust provenance tracking, and transparent workflow environments can support long-term scientific value and compliance with open science mandates. For SPECTRUM, Open Science and reproducibility are core enabling conditions for a truly interoperable, cross-domain compute and data continuum. They ensure that scientific knowledge generated in Europe remains accessible, verifiable, and re-usable across communities and generations of infrastructure and crucial way to ensure European sovereignty for research outputs including data, research software and workflows
Current State
While many European e-Infrastructures have adopted elements of FAIR data management and workflow packaging, the landscape remains fragmented. Metadata standards vary significantly by community, workflow environments are often tied to specific compute centres, and reproducibility across heterogeneous HPC/HTC/Cloud platforms is not consistently guaranteed. Storage and software preservation practices differ strongly between national and thematic infrastructures and cross-domain interoperability remains limited.
Community Evidence
Findings from the SPECTRUM Technical Blueprint, particularly Section 2.5 (software stacks, workflow systems, portability, and reproducibility gaps), reinforce that reproducibility challenges are widespread. Key gaps highlighted by communities include: inconsistent metadata and provenance capture across infrastructures, lack of standardised workflow systems supported by multiple HPC/HTC centres; divergent software stacks and insufficiently portable execution environments; limited long-term preservation of workflows, containers, and software artefacts; absence of domain-agnostic interfaces enabling reproducible execution on heterogeneous architectures.
Technical Foundation
This priority is captured in the following SPECTRUM Compute and Data Continuum Capability map (D6.1 Section 4.3 Software Distribution and Execution; Section 4.2 Data Resources)
European Alignment
Promotion of Open Science best practices stands at the core of EOSC mission. OpenAIRE provides the research graph connecting publications, datasets, and software with persistent identifiers, enabling discovery and citation tracking across European research outputs. EuroHPC JU is currently developing a federation platform aiming to bring together the diverse computational and data analysis capabilities, advanced software environments, and high-performance storage solutions available on the hosting sites. ESFRI roadmaps highlight long-term data preservation and reproducibility as essential infrastructure requirements for large-scale research facilities. EU Digital Decade prioritises trustworthy digital infrastructures, transparency, and secure data spaces, all of which depend on reproducible, open, verifiable scientific workflows. There are currently several European initiatives such as EVERSE, OSCARS directly working towards consolidating Open Science best practices across European Research Infrastructures and Scientific Communities. A number of open data alliances have been introducing open community standards (e.g., the IVOA (international virtual observatory alliance), the IHDEA (international heliophysics data environment alliance), or the IPDA (international planetary data alliance).
Target Outcomes and Impact Assessment
Strategic Outcomes
Ensure scientific workflows and results remain reproducible for many years through preservation of complete computational context. This includes standardised metadata, provenance tracking, and FAIR-compliant practices for software and workflows alongside data.
Success Indicators
Qualitative measures showing progress toward outcomes
- Increased adoption of FAIR-aligned data services across communities.
- Increased transparency and verifiability of scientific publications.
- Growth in cross-border, cross-domain scientific collaborations enabled by reproducible environments.
- Reduced operational overhead for infrastructure providers.
- Stronger alignment with European Open Science policy frameworks.
European Impact
A Europe-wide adoption of reproducibility practices enhances scientific credibility, supports evidence-based policy making, and accelerates joint scientific innovation. It positions Europe as a global leader in trustworthy, transparent, and FAIR science and contributes to strategic objectives under the EOSC, EuroHPC JU, ESFRI, and Digital Decade initiatives as explained in the European alignment.
Implementation Pathway and Stakeholder Roles
Implementation Phases
Short-term (1-3 years)
- Consolidation of guidelines and best practices for implementation of FAIR and reproducible workflows under Open Science
- Implementation specific tools to increase cross-domain collaboration such as the establishment and provision of execution environments streamlining the whole data cycle from findability, analysis, reproducibility and provenance by harmonising meta-data standards, workflow- systems and software stacks across european infrastructures.
- Training & upskilling all stakeholders on Open Science and FAIR paradigms
- Establishment of Open Science-based career recognition best practices and policies
Medium-term (3-5 years)
- Consolidation of aligned interoperability standards between major EU initiatives (EOSC, EuroHPC JU, ESFRI)
- Consolidation of FAIR-by-design services available across borders and across scientific disciplines
- Develop plans for both data & software & results preservation & reproducibility as an integral part of the preparation of scientific research activities & programmes and promoting the reuse of already existing community standards
- Promotion of Open Science part of educational curricula in university programmes
long-term actions (5+ years)
- Enforcement of FAIR standard policies for publicly funded research
- Provision of long-term funding for data and software preservation across scientific disciplines
Stakeholder Roles
Scientific Communities and Research Infrastructures
- Responsibilities: Implement FAIR and reproducible workflow guidelines following Open Science best practices, This includes contributing with domain-specific metadata, standards, and workflow definitions and sharing the best practices across scientific communities, the provision of domain-specific FAIR repositories with provenance tracking that ensure long-term curation of data, software artefacts and metadata.
- Benefits: Increased trust in results, easier collaboration, reduced technical debt, enhanced global visibility. Stronger integration between European infrastructures and enablers for long-term sustainability.
Computing & Data Service Providers / e-Infrastructures
- Responsibilities: Provide execution environments for software and containers that enable reproducibility and provenance capture. This includes the provision of common workflow engines and the integration of reproducibility checks into compute environments.
- Benefits: Reduced operational overhead, simplified user support, increased cross-site interoperability.
Policy Makers / Funding Bodies
- Responsibilities: Provide long-term funding for data and software preservation. Require and enforce the use of FAIR standards in publicly funded research Support governance frameworks for Open Science and reproducibility standards. and align national and European priorities and ensure regulatory compliance.
- Benefits: Greater return on investment and increased impact of scientific outputs from publicly funded scientific projects is not hindered due to lack of FAIRness. Increase transparency in the scientific process due to the increased reusability and reproducibility.
Resource Needs
- Updated compute and data infrastructure able to store FAIR scientific data and provide the execution environments
- Manpower including infrastructure operators, software developers to develop and maintain the SW workflows, data stewards / specialists to support the data curation across the whole data-cycle,
Critical Dependencies
Cross-priority dependencies:
- P04- Heterogeneous computing integration,
- P05-Data Management and Transport,
- P08-Software Portability,
- P10-Software Preservation and Sustainability,
- P13 Skills, Careers and Training