SUMMARYIn this paper, we discuss a real-world application scenario that uses three distinct types of workflow within the Triana problem-solving environment: serial scientific workflow for the data processing of gravitational wave signals; job submission workflows that execute Triana services on a testbed; and monitoring workflows that examine and modify the behaviour of the executing application. We briefly describe the Triana distribution mechanisms and the underlying architectures that we can support. Our middleware independent abstraction layer, called the Grid Application Prototype (GAP), enables us to advertise, discover and communicate with Web and peer-to-peer (P2P) services. We show how gravitational wave search algorithms have been implemented to distribute both the search computation and data across the European GridLab testbed, using a combination of Web services, Globus interaction and P2P infrastructures.
In this paper, we describe the graphical abstractions for Grids and services that have been implemented within the Triana problem solving environment. We provide an overview of the ways in which Triana interacts with services (e.g., Web and P2P services) and then how we interact with core Grid components, such as resource managers and data management systems through the extensive use of the GridLab GAT interface. We describe in detail the GAT philosophy and implementation and then show how the various GAT primitives can be represented in an intuitive fashion within a Triana workflow. This approach, which we refer to as the Visual GAT, differs substantially from other approaches because we do not tie our implementation to any specific underlying Grid middleware technologies; rather, we base our implementation on application level requirements and model such primitives from a user's perspective by hiding as much complexity as possible without undermining the core capabilities required. We provide a use case to demonstrate the Visual GAT implementation and show how legacy applications can seamlessly be distributed and integrated in a dynamic fashion within complex data-driven workflow scenarios.
There is a pressing need for the archiving and curation of raw X-ray diffraction data. This information is critical for validation, methods development and improvement of archived structures. However, the relatively large size of these data sets has presented challenges for storage in a single worldwide repository such as the Protein Data Bank archive. This problem can be avoided by using a federated approach, where each institution utilizes its institutional repository for storage, with a discovery service overlaid. Institutional repositories are relatively stable and adequately funded, ensuring persistence. Here, a simple repository solution is described, utilizing Fedora open-source database software and data-annotation and deposition tools that can be deployed at any site cheaply and easily. Data sets and associated metadata from federated repositories are given a unique and persistent handle, providing a simple mechanism for search and retrieval via web interfaces. In addition to ensuring that valuable data is not lost, the provision of raw data has several uses for the crystallographic community. Most importantly, structure determination can only be truly repeated or verified when the raw data are available. Moreover, the availability of raw data is extremely useful for the development of improved methods of image analysis and data processing.
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