A fundamental goal in visualization research is the quest for insight into the science behind the art of effective visual communication. In this talk I will present some of my research into methods for facilitating a rapid, comprehensive understanding of the complex spatial relationships between multiple superimposed structures in 3D datasets. In the first part of my talk, I will focus on issues in the perception and representation of surface shape. I will describe the perceptual motivation, artistic inspiration, and practical implementation of techniques for using opaquely rendered valley and sharp ridge lines to create a viewpoint-independent 3D ‘sketch’ of a transparent object that highlights its essential shape features, and for generating and applying principal direction stroke textures to intuitively convey the 3D shape of smoothly curving surfaces that are not well-characterized by ridge or valley lines. I will discuss the design and implementation of a controlled observer experiment intended to assess the practical benefit of adding discrete, opaque texture to a transparent surface, and will summarize and discuss the implications of the experimental results. In the second part of my talk, I will focus on issues in the effective visualization of 3D flow. I will show how line integral convolution techniques can be used to illustrate 3D flow through a volume, and how the introduction of visibility-impeding ‘halos’ can clarify the depth order relationships among densely clustered, overlapping streamlines by subtly emphasizing the depth discontinuities in any arbitary 2D projection of the flow. I will describe how information about the direction of the flow can be efficiently incorporated into the 3D representation, and how color can be applied to convey information about related scalar quantities over the flow. The talk will conclude with a brief discussion of future directions for work.