qData – a web-based FAIRification workflow for (eco)toxicological dose(concentration)-response data

Abstract: Effect-based methods produce data across biological levels, from molecular to apical, which vary greatly in structure and format. This heterogeneity hinders integration into mechanistic frameworks like Adverse Outcome Pathways (AOPs) and limits their use in hazard and risk characterization. To address this, we developed a Data Reporting Format (DRF) and prototyped a web-based user interface (qData UI) to streamline data collection, validation, and analysis of quantitative dose–response data from (eco)toxicological studies. qData is currently under internal and external testing using example datasets, including a case study on Diuron toxicity in Chlamydomonas reinhardtii. This dataset spans multiple biological levels and time points (6–72 h), capturing endpoints such as PSII inhibition, mitochondrial membrane potential, ATP content, and growth. The interface supports structured data and metadata entry, submission to different repositories (e.g., NIVA Risk Assessment database and Zenodo), benchmark dose (BMD) analysis for event sensitivity ranking, and future implementations will facilitate structural equation modeling (SEM) to quantify causal relationships and time-dependent dynamics across the AOP continuum. The UI and connected workflows will ultimately be integrated into the Source-to-Outcome Predictor (STOPredictor), an UI linking environmental exposure assessment with hazard characterization for the risk assessment of single substances and mixtures. Acknowledgements: This work was supported by the Research Council of Norway project EXPECT (RCN-315969), the EU-HEU project PARC (#101057014), and NIVA’s Computational Toxicology Program, NCTP (RCN-342628). Keywords: toxicity data, hazard characterisation, FAIR, dose-response modeling