MetaKG: From Data Collection to User Interaction
Saeed Hamood Alsamhi, Ammar Hawbani, Mohan Timilsina, Edward Curry · 2025
The emergence of the Metaverse as a new platform for human interaction could revolutionize several sectors. This paper provides a new “Metaverse Knowledge Graph” (MateKG) framework to enhance user interaction, data management, and knowledge representation in the virtual environment. The building and interacting MetaKGs is proposed to allow for efficient and successful data management, organization, and exploitation. The novel framework comprises several layers: infrastructure, data gathering, Knowledge Graph (KG), user interaction, evaluation and enhancement, and applications. We discuss several approaches, storage options, ontology designs for KG creation, and data-collecting sources. We look at customization strategies, accessibility concerns for the user interaction layer, and user interface design. Furthermore, we showcase case studies and MetaKG applications in e-commerce, smart cities, healthcare, and entertainment. We provide a starting point for creating reliable and efficient MetaKGs that serve a range of applications and domains.