Fast regridding of large, complex geospatial datasets

In the earth sciences, data are commonly cast on complex grids in order to model irregular domains such as coastlines, or to evenly distribute grid points over the globe. It is common for a scientist to wish to re-cast such data onto a grid that is more amenable to manipulation, visualization, or comparison with other data sources. The complexity of the grids presents a significant technical difficulty to the regridding process. In particular, the regridding of complex grids may suffer from severe performance issues, in the worst case scaling with the product of the sizes of the source and destination grids. We present a mechanism for the fast regridding of such datasets, based upon the construction of a spatial index that allows fast searching of the source grid. We discover that the most efficient spatial index under test (in terms of memory usage and query time) is a simple look-up table. A kd-tree implementation was found to be faster to build and to give similar query performance at the expense of a larger memory footprint. Using our approach, we demonstrate that regridding of complex data may proceed at speeds sufficient to permit regridding on-the-fly in an interactive visualization application, or in a Web Map Service implementation. For large datasets with complex grids the new mechanism is shown to significantly outperform algorithms used in many scientific visualization packages

From Social Simulation to Integrative System Design

As the recent financial crisis showed, today there is a strong need to gain "ecological perspective" of all relevant interactions in socio-economic-techno-environmental systems. For this, we suggested to set-up a network of Centers for integrative systems design, which shall be able to run all potentially relevant scenarios, identify causality chains, explore feedback and cascading effects for a number of model variants, and determine the reliability of their implications (given the validity of the underlying models). They will be able to detect possible negative side effect of policy decisions, before they occur. The Centers belonging to this network of Integrative Systems Design Centers would be focused on a particular field, but they would be part of an attempt to eventually cover all relevant areas of society and economy and integrate them within a "Living Earth Simulator". The results of all research activities of such Centers would be turned into informative input for political Decision Arenas. For example, Crisis Observatories (for financial instabilities, shortages of resources, environmental change, conflict, spreading of diseases, etc.) would be connected with such Decision Arenas for the purpose of visualization, in order to make complex interdependencies understandable to scientists, decision-makers, and the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c

An innovative collaborative high-performance platform for simulation

This paper presents an innovative collaborative visualization platform for the simulation-based design applications. Following the scope and the main objectives, the general architecture based on the internet standard technologies is explained. Based on a multi-domain approach, several demonstrators are involved crossing interests of industrial and academic communities. Related to the field of process engineering, we adapt and deploy a web-based architecture research application on the targeted platform

ENABLING TECHNIQUES FOR EXPRESSIVE FLOW FIELD VISUALIZATION AND EXPLORATION

Flow visualization plays an important role in many scientific and engineering disciplines such as climate modeling, turbulent combustion, and automobile design. The most common method for flow visualization is to display integral flow lines such as streamlines computed from particle tracing. Effective streamline visualization should capture flow patterns and display them with appropriate density, so that critical flow information can be visually acquired. In this dissertation, we present several approaches that facilitate expressive flow field visualization and exploration. First, we design a unified information-theoretic framework to model streamline selection and viewpoint selection as symmetric problems. Two interrelated information channels are constructed between a pool of candidate streamlines and a set of sample viewpoints. Based on these information channels, we define streamline information and viewpoint information to select best streamlines and viewpoints, respectively. Second, we present a focus+context framework to magnify small features and reduce occlusion around them while compacting the context region in a full view. This framework parititions the volume into blocks and deforms them to guide streamline repositioning. The desired deformation is formulated into energy terms and achieved by minimizing the energy function. Third, measuring the similarity of integral curves is fundamental to many tasks such as feature detection, pattern querying, streamline clustering and hierarchical exploration. We introduce FlowString that extracts shape invariant features from streamlines to form an alphabet of characters, and encodes each streamline into a string. The similarity of two streamline segments then becomes a specially designed edit distance between two strings. Leveraging the suffix tree, FlowString provides a string-based method for exploratory streamline analysis and visualization. A universal alphabet is learned from multiple data sets to capture basic flow patterns that exist in a variety of flow fields. This allows easy comparison and efficient query across data sets. Fourth, for exploration of vascular data sets, which contain a series of vector fields together with multiple scalar fields, we design a web-based approach for users to investigate the relationship among different properties guided by histograms. The vessel structure is mapped from the 3D volume space to a 2D graph, which allow more efficient interaction and effective visualization on websites. A segmentation scheme is proposed to divide the vessel structure based on a user specified property to further explore the distribution of that property over space