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MAEviz is a broadly extensible, open source platform for earthquake hazard risk management. MAEviz is a model cyberenvironment that provides practical capabilities for researchers through decision-makers to model earthquake events, develop risk reduction strategies, and implement mitigation plans to minimize the impact of earthquake disasters while also providing a pathway for researchers to quickly add new algorithms and data to assure that decisions are based on state-of-the-art engineering understanding. While MAEviz is capable of interacting with remote data and computational sources, it is also fully capable of running analyses locally so research scientists and decision-makers can generate information when a catastrophic event occurs and provide first-responders result information. This article describes MAEviz's overall layered architecture, its foundation in the widely used Eclipse Rich Client Platform (RCP), and use of open-source middleware and geographic information system (GIS) components. MAE...

Sophisticated data-distribution schemes and recent developments in sensors and instruments that can monitor the lower kilometers of the atmosphere at high levels of resolution have rapidly expanded the quantity of information available to mesoscale meteorology. The myLEAD personalized information-management tool helps geoscience users make sense of this vastly expanded information space. MyLEAD extends the general globus metadata catalog service and leverages a well-known general and extensible schema. Its orientation makes it an active player in large-scale distributed computation environments characterized by interacting grid and Web services.

Faceted browsing is a common technique for exploring collections where the data can be grouped into a number of pre-defined categories, most often generated from textual metadata. Historically, faceted browsing has been applied to a single data type such as text or image data. However, typical collections contain multiple data types, such as information from web pages that contain text, images, and video. Additionally, when browsing a collection of images and video, facets are often created based on the metadata which may be incomplete, inaccurate, or missing altogether instead of the actual visual content contained within those images and video. In this work we address these limitations by presenting MultiFacet, a faceted browsing interface that supports multiple data types. MultiFacet constructs facets for images and video in a collection from the visual content using computer vision techniques. These visual facets can then be browsed in conjunction with text facets within a single interface to reveal relationships and phenomena within multimedia collections. Additionally, we present a use case based on real-world data, demonstrating the utility of this approach towards browsing a large multimedia data collection.

MAEviz is an open-source project that helps reduce the time from discovery gap that exists between researchers, practitioners, and decision makers by integrating the latest research findings, most accurate data, and new methodologies into a single software product. It was developed as a platform to perform seismic risk assessment based on the mid-america earthquake (MAE) center research in the consequence-based risk management (CRM) framework. MAEviz is built upon an open source, extensible software platform developed at NCSA using the eclipse rich client platform (RCP). The example shown in the poster is network-based seismic retrofit (NBSR) analysis. The analysis solves a typical problem faced by decision makers that, given a fixed budget, which combination of bridges and retrofit methods would minimize the societal cost of an earthquake. It clearly shows how new science can be put quickly into the hands of the decision makers, thus bridging the gap between research and practical application. MAEviz is shown to be a powerful tool that can currently be used to assist decision makers in preparing for and mitigating the consequences of seismic hazards. Moreover, the extensible architecture of MAEviz allows it to be easily adapted to integrate newly discovered science and data, both in the area of seismic risk assessment, as well as other future research areas.

MAEviz is an open-source project that helps reduce the time from discovery gap that exists between researchers, practitioners, and decision makers by integrating the latest research findings, most accurate data, and new methodologies into a single software product. MAEviz was developed as a platform to perform seismic risk assessment based on the Mid-America Earthquake (MAE) Center research in the consequence-based risk management (CRM) framework. The CRM paradigm provides a philosophical and practical framework for the assessment of the dynamic inter-disciplinary relationship between causes, effects, and effect mitigation for major events and disaster management. MAEviz provides the medium where "what if models and risk reduction strategies can be evaluated by both researchers and decision makers in an effort to avoid a catastrophic impact on society in the event of an earthquake.

MAEviz is a state-of-the-art earthquake risk assessment environment built to quickly bring new research results into production analyses. It is built upon an extensible Open Services Gateway Initiative (OSGi) based GIS application platform and leverages distributed content management, workflow, and virtual-organization based design concepts. MAEviz has been developed as a collaboration between the National Center for Supercomputing Applications and the Mid-America Earthquake (MAE) Center community and it implements the MAE Consequence-based Risk Management (CRM) methodology. The open source MAEviz provide a modern GIS application interface with sophisticated visualization and reporting capabilities that also incorporates mechanisms to integrate distributed data sources, develop reusable analyses and view data provenance, coordinate work in distributed teams. As an Eclipse Rich Client Platform (RCP) application, MAEviz is composed of multiple plugins and extensions that wrap various open source libraries such as Geotools, the Visualization Toolkit (VTK), and Jasper reports as well as middleware components developed at NCSA. This architecture enables MAEviz to rapidly be extended with new scientific analyses and allows reuse of the base GIS environment capabilities. This demonstration paper provides an overview of MAEviz' capabilities and architecture and presents it as an exemplar of a new generation of "cyberenvironments" that enable multi-disciplinary collaboration and foster direct connections between researchers, practitioners and decision makers. MAEviz is designed to bridge the gap between scientific discovery and practical use by integrating the latest research findings, most accurate data and state-of-the-art methodologies into an extensible open source software system.

The challenges of building an effective grid-based problem solving environment that truly extends and embraces a computational scientist’s traditional tools are multifold. It is far too easy to build simple stovepipes that allow fixed use patterns, that don’t extend a scientist’s desktop, and fail to encompass the full range of patterns that a scientist needs to find such a problem-solving environment as a liberating and enabling tool. In the LEAD project, we have focused on the most challenging users of numerical weather prediction, namely, the atmospheric science researchers, who are prone to use their own tools, their own modified versions of community codes such as the Weather Research and Forecasting (WRF) model, and are typically comfortable with elaborate shell scripts to perform the work they find to be necessary to succeed, to drive our development efforts. Our response to these challenges includes a multi-level workflow engine, to handle both the challenges of ensemble description and execution, as well as the detailed patterns of workflow on each computational resource; services to support the peculiarities of each platform being used to do the modeling (such as on TeraGrid), and the use of an RDF triple store and message bus together as the backbone of our notification, logging, and metadata infrastructure. The design of our problem-solving environment elements attempts to come to grips with lack of control of elements surrounding and supporting the environment; we achieve this through multiple mechanisms including using the OSGI plug-in architecture, as well as the use of RDF triples as our finest-grain descriptive element. This combination, we believe, is an important stepping stone to building a cyber environment, which aims to provide flexibility and ease of use far beyond the current range of typical problem solving environments.

Process management is an extremely important concept in both business and scientific communities. Several workflow management tools have been proposed in recent years offering advanced functionality in various domains. In the business world, workflow vendors offer commercial and customized solutions targeting specific users. In the scientific world, several open-source workflow management tools are freely available. However they are directed toward service aggregation rather than distributed process management. Little consideration is given to the needs of the client in terms of mapping the process flow of the client. In the grid community it is essential that the grid users have such a tool available enabling them to orchestrate complex work-flows on the fly without substantial help from the service providers. At the same time it is important that the grid user not be burdened with the intricacies of the workflow system. With the perspective of the grid user in mind, an extensible client-side workflow management system, called GridAnt, has been developed. This paper discusses the design principles, functionality, and application of the proposed GridAnt workflow manager.

This paper presents an architecture to meet the needs for authentication and authorization in Grid based component systems. While Grid Security Infrastructure (GSI) [1] is accepted as the standard for authentication on the Grid, distributed authorization is still an open problem being investigated by various groups [2],[3],[4]. Our design provides authentication and fine-grained authorization at the interface, method and parameter levels. We discuss the ways in which internal and external authorization services can be used in a component framework. The design is flexible to allow the use of various existing policy languages and authorization systems. Our prototype is based on XCAT, an implementation of the Common Component Architecture (CCA) specification.