The primary goal for collecting and analyzing temporal data differs between individuals and their domain of expertise e.g., forecasting might be the goal in meteorology, anomaly detection might be the goal in finance. While the goal differs, one common denominator is the need for exploratory analysis of the temporal data, as this can aid the search for useful information. However, as temporal data can be challenging to understand and visualize, selecting appropriate visual representations for the domain and data at hand becomes a challenge. Moreover, many visual representations can show a single variable that changes over time, displaying multiple variables in a clear and easily accessible way is much harder, and inference-making and pattern recognition often require visualization of multiple variables. Additionally, as visualization aims to gain insight, it becomes crucial to investigate whether the representations used help users gain this insight. Furthermore, to create effective and efficient visual analysis tools, it is vital to understand the structure of the data, how this data can be represented, and have a clear understanding of the user needs. Developing useful visual representations can be challenging, but through close collaboration and involvement of end-users in the entire process, useful results can be accomplished. 

This thesis aims to investigate the usability of different visual representations for different types of multivariate temporal data, users, and tasks. Five user studies have been conducted to investigate different representation spaces, layouts, and interaction methods for investigating representations’ ability to facilitate users when analyzing and exploring such temporal datasets. The first study investigated and evaluated the experience of different radial design ideas for finding and comparison tasks when presenting hourly data based on an analog clock metaphor. The second study investigated 2D and 3D parallel coordinates for pattern finding. In the third study, the usability of three linear visual representations for presenting indoor climate data was investigated with domain experts. The fourth study continued on the third study and developed and evaluated a visual analytics tool with different visual representations and interaction techniques with domain experts. Finally, in the fifth study, another visual analytics tool presenting visual representations of temporal data was developed and evaluated with domain experts working and conducting experiments in Antarctica. 

The research conducted within the scope of this thesis concludes that it is vital to understand the characteristics of the temporal data and user needs for selecting the optimal representations. Without this knowledge, it becomes much harder to choose visual representations to help users gain insight from the data. It is also crucial to evaluate the perception and usability of the chosen visual representations.