Software Agent-Centric Semantic Social Network for Cyber-Physical Interaction and Collaboration

Autor: Hai H. Wang, Nazmul Hussain, Christopher D. Buckingham, Xiaoyuan Zhang
Rok vydání: 2020
Předmět:
Zdroj: International Journal of Software Engineering and Knowledge Engineering. 30:859-893
ISSN: 1793-6403
0218-1940
DOI: 10.1142/s0218194020400100
Popis: Considerable research has recently focused on integrating cyber-physical systems in a social context. However, several challenges remain concerning appropriate methodologies, frameworks and techniques for supporting socio-cyber-physical collaboration. Existing systems do not recognize how cyber-physical resources can be socially connected so that they interact in collaborative decision-making like humans. Furthermore, the lack of semantic representations for heterogeneous cyber-social-collaborative networks limits integration, interoperability and knowledge discovery from their underlying data sources. Semantic Web ontology models can help to overcome this limitation by semantically describing and interconnecting cyber-physical objects and human participants in a social space. This research addresses the establishment of both cyber-physical and human relationships and their interactions within a social-collaborative network. We discuss how nonhuman resources can be represented as socially connected nodes and utilized by software agents. A software agent-centric Semantic Social-Collaborative Network (SSCN) is then presented that provides functionality to represent and manage cyber-physical resources in a social network. It is supported by an extended ontology model for semantically describing human and nonhuman resources and their social interactions. A software agent has been implemented to perform some actions on behalf of the nonhuman resources to achieve cyber-physical collaboration. It is demonstrated within a real-world decision support system, GRiST (www.egrist.org), used by mental-health services in the UK.
Databáze: OpenAIRE