Digital twin (DT) technology has been entrusted with the tasks of modeling and monitoring of the product, process and production system. Moreover, the development of semantic modeling and digital perception provides the feasibility for the application of DT in the manufacturing industry. However, the application of DT technology in assembly workshop modeling and management is immature for the discreteness of assembly process, diversity of assembly resource and complexity of dataflow in the assembly task execution. A method of ontology-based modeling and evolution of DT for the assembly workshop is proposed to deal with this situation. Firstly, the ontology-based modeling method is given for the assembly resource and process. By instantiating in the ontology, resources and processes can be involved in the modeling and evolution of the DT workshop. Secondly, the DT assembly workshop framework is introduced with the detailed discussions of dataflow mapping, DT evolution, storage and tracing of historical data generated during the operation of the workshop. In addition, a case study is illustrated to show the entire process of construction and evolution of DT modeled on an experimental field, indicating the feasibility and validity of the method proposed.