A Decentralized Linked Data Social Network is a type of social network that allows users to store their data on a server of their choice while maintaining the interactivity between human beings and digital services expected in modern social platforms. One of the main challenges in such networks is the speed of the query process required to deliver the desired information to users. As a result, several approaches and algorithms have been developed and evaluated. This is where benchmarking plays a crucial role. Benchmarks provide a realistic and reproducible environment with a variety of scenarios, including the most challenging ones. This allows researchers and developers to compare different approaches and assess their real-world performance. Our lab has developed a benchmark called SolidBench, inspired by the LDBC SNB social network datasets. While this benchmark is useful, it does not capture an essential aspect of decentralized linked data social networks: interoperability between services. In the context of data storage and querying, enabling interoperability requires handling Heterogeneous Data Models. These models allow users to store similar conceptual information using different schemas and vocabularies. A real-world example would be users interacting with multiple blogging platforms, where each platform describes a post differently—e.g., as a "tweet" on Twitter or a "note" on another platform. Additionally, different platforms might enable distinct functionalities such as "like" systems, tags, comments, and references. Currently, in SolidBench, each type of information adheres to a single schema. This limitation prevents it from accurately simulating an environment that supports interoperability through Heterogeneous Data Models.