An ontology for component‐based models of water resource systems

Abstract

[1] Component-based modeling is an approach for simulating water resource systems where a model is composed of a set of components, each with a defined modeling objective, interlinked through data exchanges. Component-based modeling frameworks are used within the hydrologic, atmospheric, and earth surface dynamics modeling communities. While these efforts have been advancing, it has become clear that the water resources modeling community in particular, and arguably the larger earth science modeling community as well, faces a challenge of fully and precisely defining the metadata for model components. The lack of a unified framework for model component metadata limits interoperability between modeling communities and the reuse of models across modeling frameworks due to ambiguity about the model and its capabilities. To address this need, we propose an ontology for water resources model components that describes core concepts and relationships using the Web Ontology Language (OWL). The ontology that we present, which is termed the Water Resources Component (WRC) ontology, is meant to serve as a starting point that can be refined over time through engagement by the larger community until a robust knowledge framework for water resource model components is achieved. This paper presents the methodology used to arrive at the WRC ontology, the WRC ontology itself, and examples of how the ontology can aid in component-based water resources modeling by (i) assisting in identifying relevant models, (ii) encouraging proper model coupling, and (iii) facilitating interoperability across earth science modeling frameworks.Citation: Elag, M., and J. L. Goodall (2013), An ontology for component-based models of water resource systems, Water Resour.

HydroShare: Sharing Diverse Environmental Data Types and Models as Social Objects with Application to the Hydrology Domain

“…For instance, the Community Surface Dynamics Modeling System (CSDMS) project developed a repository (http://csdms.colorado.edu/wiki/ Model_download_portal) that provides metadata for a large number of models used in the geosciences. CSDMS and others have proposed standards for model components, model metadata, and controlled vocabularies (Gregersen et al, 2007;Nagai et al, 2012;Elag and Goodall, 2013;Peckham et al, 2013;Peckham, 2014). However, there has been less focus on sharing Model Instances in a formal way that is well documented and associates instances with Model Programs to support reproducible science (e.g., Dunlap et al, 2008).…”

Using OpenMI and a Model MAP to Integrate WaterML2 and NetCDF Data Sources into Flood Modeling of Genoa, Italy

“…The metadata record has been derived from sources including reference to a study of five model catalogs conducted by Zaslavsky et al . () and by comparison with the Component‐Based Water Resources Model Ontology from Elag and Goodall (). The metadata record must include the information included in Table .…”

“…Each numerical model-as set up to simulate for a given time and place-must be supplied with a package including a metadata record, documentation, and a licence for its use. The metadata record has been derived from sources including reference to a study of five model catalogs conducted by Zaslavsky et al (2014) and by comparison with the Component-Based Water Resources Model Ontology from Elag and Goodall (2013). The metadata record must include the information included in Table 2.…”

Most computational hydrology is not reproducible, so is it really science?

“…[], for example, have developed OntoSoft for the geoscience community; a metadata repository and ontology to describe software metadata. The development of code metadata, and consistent use of such a repository, while more challenging than development of metadata standards for data, will greatly facilitate the process of code identification and reuse, and through broad community engagement, lead the way toward the development of more formal ontologies for specific components of hydrological software, which will greatly improve model interoperability [see Elag and Goodall , ].…”