Remote Scientific Visualization for Large Datasets (original) (raw)

EnVision: A Web-Based Tool for Scientific Visualization

2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, 2009

Scientific visualization is the process of transforming raw numeric data into a visual form, and is a key element of computational science. While many tools exist, they are unnecessarily difficult to use. This complexity increases time to insight and inhibits casual inquiry. The complexity derives from the need to support arbitrarily formatted data and many visualization algorithms. EnVision addresses both sources of complexity. Its design is predicated on two key insights. First, though the number of data file formats is unbounded, the structure of any one can be described using a small number of parameters. Second, the set of visualization algorithms applicable to a given type of data is small, and the subset used within a specific scientific discipline is smaller. EnVision utilizes domain-specific knowledge and user-directed semi-automation to dramatically simplify data importation and visualization algorithm selection. Its web-based interface facilitates access to remote hardware resources and provides a collaborative visualization environment.

An enhanced web-service for scientific data visualization

This paper summarizes the progress achieved through the build of a scientific data visualization web service; a client-server system that is designed to acquire visualization requests from users connected to a web browser, perform the visualization process and provide them with the visualization results. Interacting with the visualization results is another issue that has to be taken into account. Providing results using VRML gives the opportunity to navigate the visualization and makes the visualization as an analysis tool rather than just a tool for the presentation of results. The different trade offs and optimization parameters associated with the VRML output are discussed through the presentation of an optimized framework aiming to provide interactive, fast, portable and easy to use services. The framework is tested against different visualization techniques to ensure its adaptability to each of them. An average reduction factor of 88 % is achieved to the final VRML resultant file and an average speed up percentage of 10 % is achieved to the execution time of the visualization process.

Collaborative scientific data visualization

Concurrency Practice and Experience, 1997

We have designed a collaborative scientific visualization package that will aid researchers from distant, diverse locations to work together in developing scientific codes, providing them with a system to analyze their scientific data. We have utilized Java to develop this infrastructure. Two important areas which we have concentrated on developing are 1) a collaborative framework from which the scientific data is interpreted and utilized, and 2) a framework, which is customizable to the suit the needs of a particular task and/or scientific group.

Modern Scientific Visualizations on the Web

Informatics

Modern scientific visualization is web-based and uses emerging technology such as WebGL (Web Graphics Library) and WebGPU for three-dimensional computer graphics and WebXR for augmented and virtual reality devices. These technologies, paired with the accessibility of websites, potentially offer a user experience beyond traditional standalone visualization systems. We review the state-of-the-art of web-based scientific visualization and present an overview of existing methods categorized by application domain. As part of this analysis, we introduce the Scientific Visualization Future Readiness Score (SciVis FRS) to rank visualizations for a technology-driven disruptive tomorrow. We then summarize challenges, current state of the publication trend, future directions, and opportunities for this exciting research field.

Querying and Visualizing Gridded Datasets for e-Science

2005

We demonstrate a web service and client application for querying and visualizing datasets defined over arbitrary topological grids. Such gridded datasets are produced by Earth science simulations, 2D and 3D visualization software, and image processing systems. Existing systems for manipulating gridded datasets capture only simple grids or do not support remote access. We exercise a novel data model by using it to build a web-enabled visualization system. We show that complex visualizations, including animations, can be expressed using our data model and associated algebra. Further, we demonstrate a standards-based, service-oriented architecture for processing the algebra expressions and returning results over the web.

A Grid Middleware Extension for Scientific Visualization

2002

Grid computing infrastructures denote interconnections of massively parallel and distributed computing resources for ubiquitous, integrated, and collaborative usage. While the majority of existing grid software constitutes high-performance and high-throughput batch processing, more and more applications require interactivity and visualization. The latter is supported through the Grid Visualization Kernel (GVK), a middleware extension for fast and efficient interconnection of distant simulation servers and visualization clients. The integration of GVK is provided by specific interface modules for commonly available visualization toolkits, while the actual interconnection is transparently established between arbitrary points on the grid.

A unified toolkit for information and scientific visualization

Visualization and Data Analysis 2009, 2009

We present an expansion of the popular open source Visualization Toolkit (VTK) to support the ingestion, processing, and display of informatics data. The result is a flexible, component-based pipeline framework for the integration and deployment of algorithms in the scientific and informatics fields. This project, code named "Titan", is one of the first efforts to address the unification of information and scientific visualization in a systematic fashion. The result includes a wide range of informatics-oriented functionality: database access, graph algorithms, graph layouts, views, charts, UI components and more. Further, the data distribution, parallel processing and client/server capabilities of VTK provide an excellent platform for scalable analysis.

Remote visualization of large datasets with MIDAS and ParaViewWeb

Proceedings of the 16th International Conference on 3D Web Technology - Web3D '11, 2011

In the recent years, the scientific community has been focusing on the management and dissemination of datasets. Challenged by the rapid growth in the number and size of scientific data and supported by new governmental policies, data sharing has become a necessary step in scientific discovery. In parallel, publishing companies have shifted their business to provide not only publications but also associated datasets to their readers. In fact, the publishing industry has been investigating ways to disseminate datasets and more importantly, to present this data to readers in a meaningful manner. In this paper, we present a combination of two leading technologies which allows for online exploration and visualization of scientific datasets. We have combined a digital archiving system, MIDAS, with an online parallel visualization framework, ParaViewWeb. The system has been deployed at several organizations and has been proven to facilitate knowledge dissemination across scientific teams.