Reanalys

Reanalys is a platform and collaborative initiative that coordinates efforts to reanalyse existing datasets and published results. It aims to improve transparency, reproducibility, and methodological rigor by providing shared workflows, provenance tracking, and community guidelines for reanalysis work.

Developed as a cross-disciplinary project, Reanalys offers an open-source software suite and a cloud-based environment for designing, executing, and auditing reanalysis pipelines. Key components include Reanalys Core for workflow orchestration, Reanalys Cloud for scalable compute, and data provenance tooling that records transformations and version history. The platform supports common workflow languages, containerization, and FAIR data practices to facilitate reuse.

Organizationally, Reanalys operates as a non-profit consortium funded by academic grants, philanthropic foundations, and partnered research institutions. Governance emphasizes community governance, transparency of funding, and open licensing of tools and documentation. Training programs and certification tracks are offered to promote best practices in data curation and reproducible analysis.

Reanalys has been adopted by universities, research labs, and some government statistical agencies to validate results and extend analyses. Critics note that reanalysis requires careful methodological framing to avoid data dredging and to respect original authors. Overall, supporters view it as a practical infrastructure for advancing open science and methodological accountability.

Related topics include reproducible research, data provenance, and open science.