A semantic annotation framework for retrieving and analyzing observational datasets

In many scientific disciplines, including ecology, hydrology, and earth science, scientific analysis requires access to a broad range of observational data. However, because of the amount and heterogeneity (both in the structure and semantics) of observational data, approaches are needed that allow scientists to easily discover and analyze them. To address this issue, we describe a framework for accessing observational data. This framework combines a core observational model, domain-specific ontologies compatible with the core model, and a semantic annotation language. The annotation language provides a formal bridge between the core model and the underlying data to enable queries and analysis over annotations. The framework has been implemented to take advantage of ontology and web-based standards, and has also been integrated within a popular metadata tool for managing ecological datasets.