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.

建立未来可持续智慧城市的最大挑战之一是技能管理和开发。开发市政人员的数字技能对于所有职业概况，尤其是对于那些积极参与智慧城市数字服务的开发和运营的职业而言，都是至关重要的。在这种情况下，本白皮书提出了一种基于语义的，基于云的增强型IT方法，该方法将学习路径与智能城市中作为管理人员和技术雇员的人员的能力管理相集成。所提出的方法将基于规则的专家系统与语义丰富的基础结构相结合，以便将技能差距诊断映射到所需的学习对象，从而有助于发展智能城市专业人员的适当能力。学习平台的语义基础结构由封装适当知识的本体和用于对员工培训过程的各个步骤进行建模的规则库组成。为了实现能力管理的效率，语义模型已转换为关系数据库模式，系统进一步将其用于执行有用的查询。本文介绍了所提出方法的关键建模工件以及已实现的CMUTE系统的体系结构。系统进一步利用它来执行有用的查询。本文介绍了所提出方法的关键建模工件以及已实现的CMUTE系统的体系结构。系统进一步利用它来执行有用的查询。本文介绍了所提出方法的关键建模工件以及已实现的CMUTE系统的体系结构。