Data visualization, the main topic of this dissertation, is the science concerned with the design and creation of visual representations intended to convey information and facilitate understanding. In a scientific context, the data to be visualized are typically research results, which can originate from any discipline. The main challenges in data visualization are to find visual representations which (1) are as accurate as possible, (2) can be understood quickly and well by viewers, and (3) can be produced automatically and efficiently. The latter is especially important when large or dynamic data sets are involved. This dissertation is focused on addressing these challenges for a particular application domain: the visualization of archaeological data. We identify general properties that often characterize archaeological data and discuss a variety of visualization methods suitable for data with these properties. For existing methods from the area of mathematics and computer science, we explain how they can be applied – either directly or with some adaptations – in the context of archaeology. We also introduce new approaches, tailored to various archaeological applications. Case studies and real archaeological data sets are used to demonstrate the use of these approaches in practical applications. However, because of our focus on general data properties rather than specific data sets, the methods presented in this dissertation are in fact widely applicable beyond the field of archaeology as well.