The web, and more recently the concept and technology of the Semantic Web, has created a wealth of new ideas and innovative tools for data management, integration and computation in an open framework and at a very large scale. One area of particular interest to the science of hydrology is the capture, representation, inference and presentation of provenance information: information that helps to explain how data were computed and how they should be interpreted. This paper is among the first to bring recent developments in the management of provenance developed for e-science and the Semantic Web to the problems of hydrology. Our main result is a formal ontological model for the representation of provenance information driven by a hydrologic case study. Along the way, we support usability, extensibility and reusability for provenance representation, relying on the concept of modelling both domain-independent and domain-specific aspects of provenance. We evaluate our model with respect to its ability to satisfy identified requirements arising from the case study on streamflow forecasting for the South Esk River catchment in Tasmania, Australia.
Modelling provenance in hydrologic science: a case study on streamflow forecasting
Yanfeng Shu, Kerry Taylor, Prasantha Hapuarachchi, Chris Peters; Modelling provenance in hydrologic science: a case study on streamflow forecasting. Journal of Hydroinformatics 1 October 2012; 14 (4): 944–959. doi: https://doi.org/10.2166/hydro.2012.134
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