A Semantic Mixed Reality Framework for Shared Cultural Experiences Ecosystems

Abstract

This paper presents SemMR, a semantic framework for modelling interactions between human and non-human entities and managing reusable and optimized cultural experiences, towards a shared cultural experience ecosystem that might seamlessly accommodate mixed reality experiences. The SemMR framework synthesizes and integrates interaction data into semantically rich reusable structures and facilitates the interaction between different types of entities in a symbiotic way, within a large, virtual, and fully experiential open world, promoting experience sharing at the user level, as well as data/application interoperability and low-effort implementation at the software engineering level. The proposed semantic framework introduces methods for low-effort implementation and the deployment of open and reusable cultural content, applications, and tools, around the concept of cultural experience as a semantic trajectory or simply, experience as a trajectory (eX-trajectory). The methods facilitate the collection and analysis of data regarding the behaviour of users and their interaction with other users and the environment, towards optimizing eX-trajectories via reconfiguration. The SemMR framework supports the synthesis, enhancement, and recommendation of highly complex reconfigurable eX-trajectories, while using semantically integrated disparate and heterogeneous related data. Overall, this work aims to semantically manage interactions and experiences through the eX-trajectory concept, towards delivering enriched cultural experiences.

Semantic Trajectory Analytics and Recommender Systems in Cultural Spaces

“…This rationale, along with the arrangement of the evaluation criteria (first half are related to ST, second half are related to RS), are the reasons for the effect in Table 1, i.e., quadrants I and III are comparatively empty. x x [13] x x x x [30] x x [31] x x [32] x x x x [33] x x…”

“…Although a significant amount of the published research is on semantic trajectories and trajectory analytics in a wide range of scientific fields, we did not include works applied to other domains, such as the works related to human road safety or autonomous vehicles. However, we have taken into consideration a selection of non-human trajectory-related studies that propose noteworthy approaches regarding the semantic annotation and management of trajectories [13,[26][27][28][29][30][31][32][33][34][35][36][37].…”

“…The work of AL-Dohuki et al [31] focuses on an approach to interact with trajectory data through visualisations, enriched with semantic information about the trajectories. The approach was designed and evaluated for taxi trajectories.…”

Intelligent Collaborative Authoring of Place-Based, Cross-Cultural and Media-Rich Experiences

“…In this concept paper, a novel research framework is introduced, integrating methods and tools for enhanced collaborative approaches to the participatory co-authoring of experiences, to foster social cohesion and to shape a Shared Experiences Ecosystem (SEE). The proposed ecosystem, initially presented in our related work within the context of designing a semantic mixed-reality framework for shared cultural experiences [1], will provide a virtual collaborative workspace for the contribution of both tangible and intangible cultural content and its enrichment via automated integration of external knowledge resources, in a crowdsourcing participative manner, utilizing semantically integrated tools. As a result, this research approach will attempt to foster the inclusive access of heterogeneous socio-cultural groups to shared experiences, increasing social cohesion in resilient local environments.…”