This thesis describes the work of two students in collaboration with OpenSpace and the Community Coordinated Modelling Center (CCMC). The need expressed by both parties is a way to more accessibly visualize space weather data from the CCMC in OpenSpace. Firstly, space weather data is preprocessed for downloading and visualizing, a process that involves reducing the size of the data whilst keeping important features. Secondly, a pipeline is created for dynamically fetching the time varying data from the web during runtime of OpenSpace. A sliding window technique is employed to manage the downloading of the data. The results show a complete and working system for downloading data during runtime. Measurements of the performance of running the space weather visualizations by dynamically downloading versus running them locally, show that the new system impacts the frame time marginally. The results also show a visualization of space weather data with enhanced features, which facilitate the exploration of the data, and creates a more comprehensible representation of the data. Data is originally kept in a tabular FITS file format, and file sizes after data reduction and feature extractionare approximately 3% of the original file sizes.