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Published on: November 4, 2025
OpenStats: how to combine statistics and research data management (RDM) to leverage efficient scientific data
Konrad Krämer1, Pierre Tremouilhac1, Fabian Mauz2
1Institute of Biological and Chemical Systems, Functional Molecular Systems (IBCS), Karlsruhe Institute of Technology, Kaiserstraße 12, 76131, Karlsruhe, Germany.
Journal of Cheminformatics
|July 2, 2026
Summary
OpenStats is a new web application that simplifies statistical analysis for researchers by integrating with electronic lab notebooks. It enhances data reproducibility and integrity through a structured analysis history.
Area of Science:
- Bioinformatics
- Computational Biology
- Data Science
Background:
- Research Data Management (RDM) tools like electronic lab notebooks (ELNs) are essential for reproducible scientific data.
- Integrating statistical analysis tools into RDM systems has been a significant challenge.
- Traceable and reproducible data analysis workflows are critical in modern research.
Purpose of the Study:
- To develop a user-friendly web application, OpenStats, for statistical analysis.
- To integrate OpenStats with an electronic lab notebook (ELN) for seamless data exchange.
- To enhance the reproducibility and integrity of scientific data through traceable analysis.
Main Methods:
- Development of OpenStats, a web application with a high-level interface for R statistical methods.
- Integration of OpenStats into the Chemotion ELN via a third-party API.
- Implementation of a structured history feature for recording and replaying analysis steps.
- Application of OpenStats to a standard dose-response assay for demonstration.
Main Results:
- OpenStats provides a user-friendly interface for statistical analysis (t-tests, ANOVA) using R.
- Seamless data exchange between OpenStats and Chemotion ELN was achieved.
- The structured history feature enables full traceability and automatic replay of analyses.
- Successful integration of statistical analysis into an RDM system, creating a closed, traceable workflow.
Conclusions:
- OpenStats effectively bridges the gap between statistical analysis and RDM systems.
- The application promotes reproducible, repeatable, and transparently documented research.
- OpenStats enhances long-term data integrity and complements standardized scientific workflows.
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