Data Distribution Service (DDS) systems utilizing the publish-subscribe paradigm typically lack support for the automatic generation of variant topics from original data models. This limitation requires developers to manually expand systems, a process that is both time-consuming and prone to errors. This thesis addresses these challenges by defining potential data variants, developing their logic, and introducing a mechanism for their automatic generation. As a practical output of this thesis, we have developed a tool that uses XML configurations to automatically generate the necessary code The research was conducted within the openDDS framework, specifically focusing on support for OpenDDSharp, which is compatible with C#. This work uses a case study approach, supplemented by additional software development and a literature review. It expands upon previous work by adding improved capabilities for managing variants and includes the development of a new tool.