DINGO: an ontology for projects and grants linked data
This work addresses the need for standardized data integration in research funding and policy, though it appears incremental as an ontology development.
The authors tackled the problem of modeling projects, funding, and policies in research by developing DINGO, an ontology that provides a machine-readable framework for semantically-enabled applications, with applicability extending to other funding-related areas.
We present DINGO (Data INtegration for Grants Ontology), an ontology that provides a machine readable extensible framework to model data for semantically-enabled applications relative to projects, funding, actors, and, notably, funding policies in the research landscape. DINGO is designed to yield high modeling power and elasticity to cope with the huge variety in funding, research and policy practices, which makes it applicable also to other areas besides research where funding is an important aspect. We discuss its main features, the principles followed for its development, its community uptake, its maintenance and evolution.