A FAIR-Compliant Management Solution for Molecular Simulation Trajectories

Simulation studies of molecules primarily produce data that represent the configuration of the system as a function of the progress variable, usually time. Because of the high-dimensional nature of these data, which grow very quickly, compromises are often necessary and achieved by storing only a subset of the system's components, for example, stripping solvent, and by restricting the time resolution to a scale significantly coarser than the basic time step of the simulation. The resultant trajectories thus describe the essentially stochastic evolution of the molecules of interest. Maintaining their interpretability through metadata is of interest not only because they can aid researchers interested in specific systems but also for reproducibility studies and model refinement. Here, we introduce a standard for the storage of data created by molecular simulations that improves compliance with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. We describe a solution conceived in PostgreSQL, along with reference implementations, that provides stringent links between metadata and raw data, which is a major weakness of the established file formats used for storing these data. A possible structure for the logic of SQL queries is included along with salient performance testing. To close, we suggest that a PostgreSQL-based storage of simulation data, in particular when coupled to a visual user interface, can improve the FAIR compliance of molecular simulation data at all levels of visibility, and a prototype solution for accomplishing this is presented.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2025-02-20
DOI
https://doi.org/10.1021/acs.jcim.4c01301
Citations
2
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
8.34
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article

A FAIR-Compliant Management Solution for Molecular Simulation Trajectories

Andreas Vitalis, Amedeo Caflisch, Julian Widmer, Yang Zhang et al.
2 citations
Journal of Chemical Information and Modeling
Scientific Computing and Data Management
8.34
article

A FAIR-Compliant Management Solution for Molecular Simulation Trajectories

Andreas Vitalis, Amedeo Caflisch, Julian Widmer, Yang Zhang, Steffen Winkler
article en
2 citations

Abstract

Simulation studies of molecules primarily produce data that represent the configuration of the system as a function of the progress variable, usually time. Because of the high-dimensional nature of these data, which grow very quickly, compromises are often necessary and achieved by storing only a subset of the system's components, for example, stripping solvent, and by restricting the time resolution to a scale significantly coarser than the basic time step of the simulation. The resultant trajectories thus describe the essentially stochastic evolution of the molecules of interest. Maintaining their interpretability through metadata is of interest not only because they can aid researchers interested in specific systems but also for reproducibility studies and model refinement. Here, we introduce a standard for the storage of data created by molecular simulations that improves compliance with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. We describe a solution conceived in PostgreSQL, along with reference implementations, that provides stringent links between metadata and raw data, which is a major weakness of the established file formats used for storing these data. A possible structure for the logic of SQL queries is included along with salient performance testing. To close, we suggest that a PostgreSQL-based storage of simulation data, in particular when coupled to a visual user interface, can improve the FAIR compliance of molecular simulation data at all levels of visibility, and a prototype solution for accomplishing this is presented.

Journal of Chemical Information and ModelingVol. 65(5)
University of Zurich (CH)
Openalex Percentile: Top 4%
Scientific Computing and Data Management
8.34
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