The reconstruction of isosurfaces from scalar volume data has positioned itself as a fundamental visualization technique in many different applications. But the dramatically increasing size of volumetric data sets often prohibits the handling of these models on affordable low-end single processor architectures. Distributed clientserver systems integrating high-bandwidth transmission channels and Web-based visualization tools are one alternative to attack this particular problem, but therefore new approaches to reduce the load of numerical processing and the number of generated primitives are required. In this paper we outline different scenarios for distributed isosurface reconstruction from large-scale volumetric data sets. We demonstrate how to directly generate stripped surface representations and we introduce adaptive and hierarchical concepts to minimize the number of vertices that have to be reconstructed, transmitted and rendered. Furthermore, we propose a novel computation scheme, which allows the user to flexibly exploit locally available resources. The proposed algorithms have been merged together in order to build a platform-independent Web-based application. Extensive use of VRML and Java OpenGL-bindings allows for the exploration of large-scale volume data quite efficiently.