This thesis aimed to research further integration of external software in the open-source software OpenSpace. The work was divided into the four sub-objectives: support for distributed systems, color mapping support, an extension of the message protocol for velocity data, and saving and loading visualization states created with external software. A prerequisite for continuing the progress made in this field by Johanna Granström and Aniisa Bihi in 2020 was redesigning SIMP. They created the SIMP protocol to support real-time communication between external software and OpenSpace. In the redesign work of SIMP in this thesis, new message types were added and some were deprecated. The key new message type is the Data message, which replaces all message types that added or modified visualized datasets in OpenSpace. Furthermore, some optimizations were made to the message parsing algorithm, which resulted in a speed-up of the communication between external software and OpenSpace. In turn, this led to an improved user experience. However, the main improvement to the existing software integration was to add support for software integration in OpenSpace on a distributed system setup. This was accomplished by using the data synchronization step of the rendering process of SGCT, a utility library used by OpenSpace. Furthermore, SIMP was extended to support colormap and velocity data. These two new data types were also accompanied by an extension of the points cloud renderable created by Bihi and Granström for rendering the data sent from external software. Lastly, support was added to OpenSpace to save the current state of software integration visualizations and load the same state later without manually going through the steps of recreating the visualization state. This led to an asset file generator being implemented for the software integration so that users can save visualization states and use them later or share them with other OpenSpace users. The thesis resulted in successful solutions of all aforementioned sub-objectives, which will further enable researchers to quickly present their findings in the immersive tool that OpenSpace is and facilitate collaborative research even more than before.