Knowledge management in the context of smart cities with a computational approach is critically important. It aids in managing the complexities of technology, leveraging the potential of data, enhancing security and privacy, supporting system integration, improving decision-making, and facilitating technological innovation to create smarter, more efficient, and sustainable urban environments. This study proposes a participatory smart city management framework through a knowledge management model. The framework is designed to engage stakeholders (users) in active interaction and participation, incorporate data and information related to smart city management into a knowledge database, and present this data and information as knowledge visualizations derived from smart city management implementation. The research focuses on developing a model for managing data and information that encompasses the collection, storage, and management of relevant data for various aspects of urban life. The Knowledge Management System (KMS) is envisioned as a platform specifically designed to manage knowledge within the context of a smart city. Data Analysis involves employing data analysis techniques and artificial intelligence to process collected data into valuable insights for decision-making. It can be used to identify patterns, trends, anomalies, and correlations within the data, as well as to predict behaviors or events in the future. Collaborative Platforms are also highlighted as key components, enabling cooperation among various stakeholders, including government agencies, businesses, academia, and civil society. These platforms facilitate the exchange of knowledge, ideas, and experiences among stakeholders, fostering the creation of more innovative and effective solutions.