Data Integration with Knowledge Graphs: A Space Weather Use-case

Abstract:

Knowledge graphs (KG) are a key tool for managing data and transforming facts into knowledge. They are a method for sharing, integrating, and interoperating complex data. The backbone of a KG is the schema for the data and the system they are used to describe, or an ontology. Ontologies are human conceptualizations of data, and in particular, modular ontologies which promote adaptability and evolvability as both data and user needs change. These ontologies are thus a useful structure for acting as schema for knowledge graphs.

In order to support a burgeoning movement in the Space Weather community that is driving data and knowledge integration across many related fields, the Convergence Hub for the Exploration of Space Science (CHESS) , supported by the Spatially-Explicit Models, Methods, and Services for Open Knowledge Networks (SpEx) from the National Science Foundation Convergence Accelerator have begun the development of a modular ontology, which is a type of ontology that promotes adaptability and evolvability as both data and user needs change, and is therefore critical to space weather

We present the CHESS modular ontology, its design philosophy, and how it can be used as the schema of a knowledge graph that supports integration across the myriad of fields and industries that support and interact with the Space Weather community.