DINGO: an ontology for projects and grants linked data

TL;DR

DINGO is an extensible ontology designed to model research projects, funding, actors, and policies, enabling semantically-enabled applications with high flexibility and applicability across various domains.

Contribution

The paper introduces DINGO, a novel ontology that offers a flexible, extensible framework for modeling research funding data and policies in a machine-readable format.

Findings

DINGO supports diverse funding and policy practices.

The ontology facilitates semantic integration of research data.

Community uptake and maintenance strategies are discussed.

Abstract

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.