Cloud computing and semantic web technologies for ubiquitous management of smart cities-related competences

Abstract

One of the biggest challenges in building sustainable smart cities of the future is skill management and development. Developing the digital skills of the municipalities’ workforce is crucial for all occupational profiles and specifically for those that are actively involved in the development and operation of digital services for a smart city. In this context, the current paper presents a semantically enhanced cloud-based IT approach which integrates learning pathways with competence management of personnel working as management and technical employees in a smart city municipality. The proposed approach combines a rule-based expert system with a semantically rich infrastructure in order to map skill gap diagnosis to required learning objects and, thus, to contribute in developing appropriate competences of smart city professionals. The semantic infrastructure of the learning platform consists of an ontology which encapsulates the appropriate knowledge and a rule-base for modeling the steps of an employee training process. In order to achieve efficiency in competence management the semantic model has been transformed into a relational database schema, which is further utilized by the system for the execution of useful queries. The paper presents the key modeling artifacts of the proposed approach and the architecture of the implemented CMUTE system.