Browsing by Subject "data-source integration"

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    An open-data open-model framework for hydrological models’ integration, evaluation and application
    (Elsevier, 2020-04) Salas, Daniel; Liang, Xu; Navarro, Miguel; Liang, Yao; Luna, Daniel; Computer and Information Science, School of Science
    To tackle fundamental scientific questions regarding health, resilience and sustainability of water resources which encompass multiple disciplines, researchers need to be able to easily access diverse data sources and to also effectively incorporate these data into heterogeneous models. To address these cyberinfrastructure challenges, a new sustainable and easy-to-use Open Data and Open Modeling framework called Meta-Scientific-Modeling (MSM) is developed. MSM addresses the challenges of accessing heterogeneous data sources via the Open Data architecture which facilitates integration of various external data sources. Data Agents are used to handle remote data access protocols, metadata standards, and source-specific implementations. The Open Modeling architecture allows different models to be easily integrated into MSM via Model Agents, enabling direct heterogeneous model coupling. MSM adopts a graphical scientific workflow system (VisTrails) and does not require re-compiling or adding interface codes for any diverse model integration. A study case is presented to illustrate the merit of MSM.