• News item 163

New paper - Universal Digital Twin – A Dynamic Knowledge Graph

06 September 2021
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Very excited to share our new paper proposing a design for a Universal Digital Twin!

This application of dynamic knowledge graphs presents a candidate to solve problems caused by lack of interoperability between different types of data and models. We believe that it has the potential to unify many different research streams, promoting synergistic effects that would be difficult to achieve in other ways. The paper explains how this approach is by design naturally suited to realizing the vision of a Universal Digital Twin. The dynamic knowledge graph is implemented using technologies from the Semantic Web. It is composed of concepts and instances that are defined using ontologies, and of computational agents that operate on both the concepts and instances to update the dynamic knowledge graph. By construction, it is distributed, supports cross-domain interoperability, and ensures that data are connected, portable, discoverable, and queryable via a uniform interface. The knowledge graph includes the notions of a “base world” that describes the real world and that is maintained by agents that incorporate real-time data, and of “parallel worlds” that support the intelligent exploration of alternative designs without affecting the base world. Use cases are presented that demonstrate the ability of the dynamic knowledge graph to host geospatial and chemical data, control chemistry experiments, perform cross-domain simulations, and perform scenario analysis. The questions of how to make intelligent suggestions for alternative scenarios and how to ensure alignment between the scenarios considered by the knowledge graph and the goals of society are considered. Work to extend the dynamic knowledge graph to develop a digital twin of the UK to support the decarbonization of the energy system is discussed. Important directions for future research are highlighted. A preview of some of the areas that we have investigated with our collaborators at CMCL can be found here: https://kg.cmclinnovations.com/.