New visual analytics approaches for volume data time series in materials science

Supervisors: Prof. Martin Müller (HZG), Prof. Stephan Olbrich (UHH)

To support material science applications, we will develop and integrate application-specific data stream and file interfaces as well as processing and visualization algorithms, and optimize them for scalability and usability, based on an existing in-situ parallel data streaming and extraction framework. It is planned to combine and tightly couple of 3d image based data extraction methods with 3d geometry based analytics, in order to develop and integrate innovative hybrid methods, e. g. for segmentation purposes. These should reduce or avoid intermediate data and take advantage of complexity reduction (O(N3) volume/voxel => O(N2) surface/polygons), in order to efficiently and auto¬mati-cally generate abstractions of the characteristics of materials and its changes over time. To enable and support interdisciplinary usage and openness for scientific and public scenarios, efficient parallel compression and decompression will be integrated as part of the extraction of the resulting 3d geometric and/or symbolic representations, and a thin multi-platform client software will be provided for open access and remote 3d viewing.