ArticlePloS one2025
SIMPROV: Provenance capturing for simulation studies.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- VIOLIN: A modular framework for scalable reconciliation of heterogeneous interaction graphs.bioRxiv : the preprint server for biology · 2026Article
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5 authors.
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Abstract
Improving interpretability and reusability has become paramount for modeling and simulation studies. Provenance, which encompasses information about the entities, activities, and agents involved in producing a model, experiment, or data, is pivotal in achieving this goal. However, capturing provenance in simulation studies presents a tremendous challenge due to the diverse software systems employed by modelers and the various entities and activities to be considered. Existing methods only automatically capture partial provenance from individual software systems, leaving gaps in the overall story of a simulation study. To address this limitation, we introduce a lightweight method that can record the provenance of complete simulation studies by monitoring the modeler in their familiar yet heterogeneous work environment, posing as few restrictions as possible. The approach emphasizes a clear separation of concerns between provenance capturers, which collect data from the diverse software systems used, and a provenance builder, which assembles this information into a coherent provenance graph. Furthermore, we provide a web interface that enables modelers to enhance and explore their provenance graphs. We showcase the practicality of SIMPROV through two cell biological case studies.
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Registered trials
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