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Data model, dictionaries, and desiderata for biomolecular simulation data indexing and sharing
Julien C Thibault, Daniel R Roe, Julio C Facelli1
1Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA. julio.facelli@utah.edu.
Journal of Cheminformatics
|February 4, 2014
Summary
A new logical model and data dictionaries standardize biomolecular simulation data, improving data sharing and reuse for computational chemistry and molecular dynamics research. This facilitates better data management and exploration in the field.
Area of Science:
- Computational Biology
- Biomolecular Simulations
- Data Science
Background:
- Limited environments exist for sharing biomolecular simulation data and fostering collaborative exploration.
- Increasing data volume and complexity necessitate improved tools for managing and sharing simulation outputs.
- Growing application of simulation methods highlights the need for standardized data representation.
Purpose of the Study:
- To assess community needs for data representation standards in biomolecular simulations.
- To guide the development of future repositories for biomolecular simulation data.
- To establish a common logical model for representing diverse simulation data.
Main Methods:
- Community feedback gathered through surveys and interviews informed the selection of common data elements.
- Data elements were integrated to encompass concepts from quantum chemistry and molecular dynamics.
- A logical model and associated dictionaries were developed for database and API design.
Main Results:
- A comprehensive list of common data elements for biomolecular simulations was identified and refined.
- A logical model was created to structure data for new databases and application programming interfaces.
- SQL queryable and Java API-accessible dictionaries were implemented using the Apache Lucene search engine.
Conclusions:
- The proposed model and dictionaries offer a robust yet simple representation for biomolecular simulation concepts.
- This framework is extensible and supports future development of terminologies and ontologies.
- Use cases demonstrate benefits for data storage, indexing, and presentation, enhancing data accessibility and reuse.
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