Back to Search Start Over

A Semantic Mixed Reality Framework for Shared Cultural Experiences Ecosystems.

Authors :
Vassilakis, Costas
Kotis, Konstantinos
Spiliotopoulo, Dimitris
Margaris, Dionisis
Kasapakis, Vlasios
Anagnostopoulos, Christos-Nikolaos
Santipantakis, Georgios
Vouros, George A.
Kotsilieris, Theodore
Petukhova, Volha
Malchanau, Andrei
Lykourentzou, Ioanna
Helin, Kaj Michael
Revenko, Artem
Gligoric, Nenad
Pokric, Boris
Source :
Big Data & Cognitive Computing; Jun2020, Vol. 4 Issue 2, p1-22, 22p
Publication Year :
2020

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
25042289
Volume :
4
Issue :
2
Database :
Complementary Index
Journal :
Big Data & Cognitive Computing
Publication Type :
Academic Journal
Accession number :
144942524
Full Text :
https://doi.org/10.3390/bdcc4020006