A Parallel World Framework for scenario analysis in knowledge graphs

Abstract

This paper presents Parallel World Framework as a solution for simulations of complex systems within a time-varying knowledge graph and its application to the electric grid of Jurong Island in Singapore. The underlying modeling system is based on the Semantic Web Stack. Its linked data layer is described by means of ontologies, which span multiple domains. The framework is designed to allow what-if scenarios to be simulated generically, even for complex, inter-linked, cross-domain applications, as well as conducting multi-scale optimizations of complex superstructures within the system. Parallel world containers, introduced by the framework, ensure data separation and versioning of structures crossing various domain boundaries. Separation of operations, belonging to a particular version of the world, is taken care of by a scenario agent. It encapsulates functionality of operations on data and acts as a parallel world proxy to all of the other agents operating on the knowledge graph. Electric network optimization for carbon tax is demonstrated as a use case. The framework allows to model and evaluate electrical networks corresponding to set carbon tax values by retrofitting different types of power generators and optimizing the grid accordingly. The use case shows the possibility of using this solution as a tool for CO2 reduction modeling and planning at scale due to its distributed architecture.

Universal Digital Twin: Land use

“…• Providing an interface to computational models to calculate quantities, for example estimates of air quality (Farazi et al, 2020c), and updating the instances in the knowledge graph. • Restructuring the knowledge graph by adding instances, for example to explore the consequences of design choices (Devanand et al, 2019;Eibeck et al, 2020), or by adding concepts and relationships between concepts and instances, for example using ontology matching to improve the coverage of the knowledge graph. • Discover and compose new agents simply by reading from and writing to the knowledge graph so as to combine existing agents to form composite agents to perform more complex tasks (Zhou et al, 2019).…”

“…Restructuring the knowledge graph by adding instances, for example to explore the consequences of design choices (Devanand et al, 2019; Eibeck et al, 2020), or by adding concepts and relationships between concepts and instances, for example using ontology matching to improve the coverage of the knowledge graph.…”

“…The World Avatar, and the digital twins based on it, include the idea of a “base world” that describes the real world and that is kept current in time by computational agents that input data from the real world into the knowledge graph and that simulate the behavior of the world, and of “parallel worlds” that support what-if scenario analysis (Eibeck et al, 2020). The parallel worlds capability allows exploring consequences of alternative design and policy choices to support decision making in complex environments.…”

“…In this approach, autonomous computational agents interact to perform tasks including updating the knowledge graph to ensure that it remains current in time, simulating the behavior of systems and sending responses back to the physical world. It has been shown how this architecture can be used to implement digital twins that provide information about the state of the world, provide intelligent control using computational agents to model the behavior of complex systems and provide support for intelligent design via what-if scenario analysis (Eibeck et al, 2020; Akroyd et al, 2021). The World Avatar approach employs Semantic Web technologies (Berners-Lee et al, 2001; W3C, 2015) to provide a uniform method to query and host distributed data.…”

Automated Calibration of a Poly(oxymethylene) Dimethyl Ether Oxidation Mechanism Using the Knowledge Graph Technology

“…The JPS has been applied to the utilization of waste energy, 23 network optimization of the ecoindustrial park, 24 and simulations of a carbon tax for scenario analysis in policy making. 25 …”