Gary D. Black

Ecce - A Problem Solving Environment's Evolution Toward Grid Services and a Web Architecture

The Extensible Computational Chemistry Environment (Ecce), an innovative problem‐solving environment, was designed a decade ago, before the emergence of the Web and Grid computing services. In this paper, we briefly examine the original Ecce architecture and discuss how it is evolving to incorporate both Grid services and components of the Web to increase its range of services, reduce deployment and maintenance costs, and reach a wider audience. We show that Ecce operates in both Grid and non‐Grid environments, an important consideration given Ecces broad range of uses and user community, and discuss the strategies for loosely coupled components that make this possible. Both in‐progress work and conceptual plans for how Ecce will evolve are presented. Copyright

Velo: A Knowledge-Management Framework for Modeling and Simulation

Velo is a reusable, domain-independent knowledge-management infrastructure for modeling and simulation. Velo leverages, integrates, and extends Web-based open source collaborative and data-management technologies to create a scalable and flexible core platform tailored to specific scientific domains. As the examples here describe, Velo has been used in both the carbon sequestration and climate modeling domains.

The extensible computational chemistry environment: a problem solving environment for high performance theoretical chemistry

The Extensible Computational Chemistry Environment (Ecce) is a suite of distributed applications that are integrated as a comprehensive problem solving environment for computational chemistry. Ecce provides scientists with an easily used graphical user interface to the tasks of setting up complex molecular modeling calculations, distributed use of high performance computers, and scientific visualization and analysis. Ecces flexible, standards-based architecture is an extensible framework that represents a significant milestone in production systems, both in the field of computational chemistry and problem solving environment research. Its base problem solving architecture components and concepts are applicable to problem solving environments beyond the computational chemistry domain.

Velo: riding the knowledge management wave for simulation and modeling

Modern scientific enterprises are inherently knowledge-intensive. In general, scientific studies in domains such as geosciences, climate, and biology require the acquisition and manipulation of large amounts of experimental and field data in order to create inputs for large-scale computational simulations. The results of these simulations must then be analyzed, leading to refinements of inputs and models and additional simulations. Further, these results must be managed and archived to provide justifications for regulatory decisions and publications that are based on these models. In this paper we introduce our Velo framework that is designed as a reusable, domain independent knowledge management infrastructure for modeling and simulation. Velo leverages, integrates, and extends open source collaborative and content management technologies to create a scalable and flexible core platform that can be tailored to specific scientific domains. We describe the architecture of Velo for managing and associating the various types of data that are used and created in modeling and simulation projects, as well as the framework for integrating domain-specific tools. To demonstrate a realization of Velo, we describe the Geologic Sequestration Software Suite (GS3) that has been developed to support geologic sequestration modeling. This provides a concrete example of the inherent extensibility and utility of our approach.

GS3: A Knowledge Management Architecture for Collaborative Geologic Sequestration Modeling

Modern scientific enterprises are inherently knowledge-intensive. In general, scientific studies in domains such as geoscience, chemistry, physics and biology require the acquisition and manipulation of large amounts of experimental and field data in order to create inputs for large-scale computational simulations. The results of these simulations must then be analyzed, leading to refinements of inputs and models and further simulations. In this paper we describe our efforts in creating a knowledge management platform to support collaborative, wide-scale studies in the area of geologic sequestration modeling. The platform, known as GS3 (Geologic Sequestration Software Suite), exploits and integrates off-the-shelf software components including semantic wikis, content management systems and open source middleware to create the core architecture. We then extend the wiki environment to support the capture of provenance, the ability to incorporate various analysis tools, and the ability to launch simulations on supercomputers. The paper describes the key components of GS3 and demonstrates its use through illustrative examples. We conclude by assessing the suitability of our approach for geologic sequestration modeling and generalization to other scientific problem domains.

Process integration, data management, and visualization framework for subsurface sciences

Applying subsurface simulation codes to understand heterogeneous flow and transport problems is a complex process potentially involving multiple models, multiple scales, and spanning multiple scientific disciplines. A typical end-to-end process involves many tools, scripts and data sources usually shared only though informal channels. Additionally, the process contains many sub-processes that are repeated frequently and could be automated and shared. Finally, keeping records of the models, processes, and correlation between inputs and outputs is currently manual, time consuming and error prone. We are developing a software framework that integrates a workflow execution environment, shared data repository, and analysis and visualization tools to support development and use of new hybrid subsurface simulation codes. We are taking advantage of recent advances in scientific process automation using the Kepler system and advances in data services based on content management. Extensibility and flexibility are key underlying design considerations to support the constantly changing set of tools, scripts, and models available. We describe the architecture and components of this system with early examples of applying it to a continuum subsurface model.