This article is concerned with the data structures, properties of query languages, and visualization facilities required for the generic representation of richly annotated, heterogeneous linguistic corpora. We propose that above and beyond a general graph-based data model, which is becoming increasingly popular in many complex annotation formats, a well-defined concept of multiple, potentially conflicting segmentation layers must be introduced to deal with different sources and applications of corpus data flexibly. We also propose a generic solution for specialized corpus visualizations in a Web interface using annotation-triggered style sheets, which leverage the power of modern browsers and CSS for multiple and highly customizable views of primary data. We offer an implementation and evaluation of our architecture in ANNIS3, an open-source browser-based architecture for corpus search and visualization. We present three case studies to test the coverage of the system, encompassing core linguistic and digital humanities use-cases including richly annotated newspaper treebanks, multilingual diplomatic and normalized manuscript materials edited in TEI, and analysis of multimodal recordings of spoken language.