The World Avatar

A knowledge-graph-based digital twin of the world

A knowledge graph is a network of data expressed as a directed graph, where the nodes of the graph are concepts or their instances (data items) and the edges of the graph are links between related concepts or instances. Knowledge graphs are often built using the principles of Linked Data. They provide a powerful means to host, query and traverse data, and to find and retrieve related information.

The World Avatar project, which is the flag-ship project in the C4T programme of CARES at the University of Cambridge, aims to create a digital ‘avatar’ of the real world. The digital world is composed of a dynamic knowledge graph that contains concepts and data that describe the world, and an ecosystem of autonomous computational agents that simulate the behaviour of the world and that update the concepts and data so that the digital world remains current in time. In this manner, it is proposed that it is possible to create digital twins that are able to describe the behavior of complex systems, and by doing so provide the ability to make data-driven decisions about how to optimise the systems.

A central tenet of the World Avatar is the requirement to share data so that all the computational agents experience a self-consistent view of the world, and the requirement that data and computational agents must be interoperable across different technical and social domains. This interoperability, defined in the sense of the ability of tools and systems to understand and use the functionalities of other tools, is considered to be one of the key aspects of Industry 4.0 and will become increasingly important as the complexity and choice of tools inevitably increases. For example, considerations raised by recent reports concerning the possible role of hydrogen in the future UK energy landscape span the electrical power system, the gas grid, the potential of biomass, solar and wind energy, the transport system, heating of commercial and domestic buildings, in addition to considerations relating to the acceptance and adoption of new technologies by the public.

The World Avatar represents information in a dynamic knowledge graph using technologies from the Semantic Web stack. Unlike a traditional database, the World Avatar contains an ecosystem of autonomous computational agents that continuously update it.

Structure of the World Avatar

The main components of the dynamic knowledge graph are illustrated in the above figure. The dynamic knowledge graph contains concepts and instances that are linked to form a directed graph. The agents are described ontologically as part of the knowledge graph, and are able to perform actions on both concepts and instances. This confers versatility because it combines a design that enables agents to update and restructure the knowledge graph, with a structure that allows agents to discover and compose other agents simply by reading from and writing to the knowledge graph.

Recent Associated Preprints

301: British Imbalance Market Paradox: Variable Renewable Energy Penetration in Energy Markets

John Atherton, Markus Hofmeister, Sebastian Mosbach, Jethro Akroyd, and Markus Kraft, Technical Report 301, c4e-Preprint Series, Cambridge, 2023.

300: Knowledge Engineering in Chemistry: From Expert Systems to Agents of Creation

Aleksandar Kondinski, Jiaru Bai, Sebastian Mosbach, Jethro Akroyd, and Markus Kraft, Technical Report 300, c4e-Preprint Series, Cambridge, 2022.

297: Semantic 3D City Interfaces - intelligent interactions on Dynamic Geospatial Knowledge Graphs

Arkadiusz Chadzynski, Shiying Li, Ayda Grisiute, Jefferson Chua, Jingya Yan, Huay Yi Tai, Emily Lloyd, Mehal Agarwal, Markus Hofmeister, Jethro Akroyd, Pieter Herthogs, and Markus Kraft, Technical Report 297, c4e-Preprint Series, Cambridge, 2022.

296: The slow engagement of planning scholars with BIM-GIS-Semantic integration: A literature review

Hou Yee Quek, Franziska Sielker, Jethro Akroyd, and Markus Kraft, Technical Report 296, c4e-Preprint Series, Cambridge, 2022.

Funding

This research was partly funded by the National Research Foundation (NRF), Prime Minister's Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme.