| Title | Semantic Modeling for Supporting Planning Decision Making toward Smart Cities |
|---|---|
| ID_Doc | 42702 |
| Authors | Zhang, L; Liu, KJ |
| Title | Semantic Modeling for Supporting Planning Decision Making toward Smart Cities |
| Year | 2022 |
| Published | |
| Abstract | The world is urbanizing rapidly. By 2050, 68% of the world population will reside in urban areas, posing unprecedented pressures on the livability, equity, and sustainability of city systems. While the concept of smart city holds great promise to release these pressures, the planning decision making toward smart cities is challenging because of the enormous breadth of smart city dimensions. As a result, decision makers are often lost in where and how to make the best investments to address the most pressing issues at hand. In recent years, many smart city initiatives and programs have been implemented, which offers an important source of smart city knowledge for decision makers to learn from. To this end, this paper proposes a smart city ontology, as a shared conceptualization of smart city knowledge, to facilitate the sharing and reuse of the knowledge for informed planning decision making. At the highest level of abstraction, the ontology semantically models three key elements of smart city knowledge, including visions, challenges, and solutions. This paper focuses on presenting the proposed ontology and its evaluation. The evaluation results showed the promise of the proposed ontology in supporting smart city planning decision making. |
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