Abstract Customizing extended reality (XR) interfaces presents a significant challenge, especially for users with limited programming expertise. This paper introduces the method for adaptation of XR interfaces (MAXI-XR), a novel approach to simplify the customization process of XR user interfaces through knowledge technologies. MAXI-XR offers a user-friendly solution for interface design, supporting users with varying levels of technical skills. The basis of MAXI-XR is its Semantic Knowledge Base, which facilitates intelligent adaptations through advanced querying and reasoning, enabling the extraction of user-specific information for context-based XR interface adaptation. The functionality of MAXI-XR is demonstrated by its application in a VR stock market data visualization system. This system demonstrates MAXI-XR’s ability to adapt to complex and data-intensive environments according to user requirements, improving the interaction experience. Furthermore, the method’s scalability and ease of maintenance make it a versatile tool for a wide range of applications beyond stock market visualization, suggesting its potential for broader adoption in various XR domains.

Adaptation of Extended Reality (XR) interfaces to fit user needs and preferences presents a significant challenge. The available XR application development tools often require advanced programming skills, forming a barrier for non-specialists in XR technology and 3D modeling. The main contribution of this paper is a knowledge-based method for the adaptation of XR user interfaces, with a focus on the usage of semantic representation of the users’ profiles to tailor individual experiences within an XR environment to the users’ requirements. The primary aim is to optimize user satisfaction and performance by enabling the adaptation of XR content by non-IT specialists using common or domain knowledge. As a case study for utilizing user profile-based adaptation, the paper presents an adaptive XR stock exchange data visualization system.

XR environments are successfully used in various domains, such as medicine, education, training, and industry.Such environments contain domain knowledge expressed through content and users' behavior.However, current approaches to XR creation lack possibility of exploration of the knowledge included in the environments and expressed by the users' behavior.In this paper, we propose a method of knowledge exploration in XR environments, enabling the analysis of past and potential behavior of users and objects, with queries and automated reasoning.This solution aims to enhance knowledge dissemination using XR.

The paper describes an experiment aiming to determine how vibrotactile feedback implemented with the use of inexpensive VR gloves affects users’ perception of relief sculptures in a virtual museum environment. We developed a virtual museum system, which allows users to experience 3D models of bas-reliefs created by an artist based on well-known paintings of Pablo Picasso. In the experiment, we compared the perception of the art in a purely visual form and a combined visual-tactile form. We also checked to what extent users could identify a piece of art based purely on the tactile feedback and whether they could properly verify the match between the visual and the tactile modalities. We also recorded users’ opinions and impressions of the different artworks presentation methods.