ENABLING KNOWLEDGE SHARING BY MANAGING DEPENDENCIES AND INTEROPERABILITY BETWEEN INTERLINKED SPATIAL KNOWLEDGE GRAPHS

Abstract. Knowledge sharing is increasingly being recognized as necessary to address societal, economic, environmental, and public health challenges. This often requires collaboration between federal, local, and tribal governments along with the private sector, nonprofit organizations, and institutions of higher education. To achieve this, there needs to be a move away from data-centric to knowledge sharing architectures, such as a Geospatial Knowledge Infrastructure (GKI). Data from multiple organizations need to be properly contextualized in both space and time to support geographically based planning, decision making, cooperation and coordination. A spatial knowledge graph (SKG) is a useful paradigm for facilitating knowledge sharing and collaboration. However, interoperability between independently developed SKGs from different organizations that reference the same geographies is often not automated in a machine-readable way due to a lack of standardization. This paper outlines an architecture that automates interoperability and dependency management between SKGs as they are formally published by version and period of validity. We are calling this approach a spatial knowledge mesh (SKM), as it is a specialization of the data mesh architecture along with the concept of a common geo-registry to facilitate knowledge sharing more easily. The initial implementation, called GeoPrism Registry, is being developed as an open-source spatial knowledge infrastructure as a platform to help countries meet their NSDI and GKI objectives. It was fist funded and deployed to support ministries of health and is more recently being utilized in GeoPlatform.gov.