Imagine following a recipe but getting a different cake every time; that's the problem with some scientific research today. This work looks at why this happens in medicine, computers, and social sciences. It creates a shared set of tools and rules so that different teams can get the same results, making science more like a reliable instruction manual.
Research results are often not reproducible, leading to wasted funding and a loss of societal trust. This inefficiency slows down innovation in medical and computer sciences.
A ReproducibilityHub, training modules, and a set of EOSC-interoperable tools and practices tested through pilot activities.
If you are a drug discovery lab dealing with inconsistent trial results — this project developed reproducibility-related tools that increase the reliability of research findings. This reduces the risk of pursuing dead-end leads based on non-reproducible data.
If you are a scientific journal publisher dealing with a lack of transparency in reported data — this project developed new practices and a ReproducibilityHub that helps verify the integrity of submitted papers. This protects the publisher's reputation and trust in their content.
If you are an AI research firm dealing with the inability to replicate computer science results — this project developed EOSC-interoperable tools that ensure analysis can be repeated. This speeds up the development cycle by avoiding redundant work.
Based on available project data, no specific pricing or licensing costs are mentioned; the project was funded by an EU contribution of EUR 1,791,500.
The project implemented tools via a series of pilot activities across social, life, and computer sciences, suggesting a design intended for broad application.
Based on available project data, specific IP or licensing terms are not provided, though the tools are designed to be EOSC-interoperable.
The project ran for three years, from 2023-01-01 to 2025-12-31.
The project included alignment activities to ensure that the developed tools are EOSC-interoperable.
The consortium consists of 10 partners across 7 countries, showing a strong European reach. It is heavily weighted toward research and academic entities (8 combined), but includes a 10% industry ratio with 1 industry partner and 2 SMEs, including the coordinator. This suggests the project is primarily research-driven but has a direct link to small-scale commercial implementation.
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