Abstract-While workflow technology has gained momentum in the last decade as a means for specifying and enacting computational experiments in modern science, reusing and repurposing existing workflows to build new scientific experiments is still a daunting task. This is partly due to the difficulty that scientists experience when attempting to understand existing workflows, which contain several data preparation and adaptation steps in addition to the scientifically significant analysis steps. One way to tackle the understandability problem is through providing abstractions that give a high-level view of activities undertaken within workflows. As a first step towards abstractions, we report in this paper on the results of a manual analysis performed over a set of real-world scientific workflows from Taverna and Wings systems. Our analysis has resulted in a set of scientific workflow motifs that outline i) the kinds of data intensive activities that are observed in workflows (data oriented motifs), and ii) the different manners in which activities are implemented within workflows (workflow oriented motifs). These motifs can be useful to inform workflow designers on the good and bad practices for workflow development, to inform the design of automated tools for the generation of workflow abstractions, etc.

Abstract. Semantic Web Services offer the possibility of highly flexible web service architectures, where new services can be quickly discovered, orchestrated and composed into workflows. Most existing work has, however, focused on complex service descriptions for automated composition. In this paper, we describe the requirements from the bioinformatics domain which demand technically simpler descriptions, involving the user community at all levels. We describe our data model and lightweight semantic discovery architecture. We explain how this fits in the larger architecture of the my Grid project, which overall enables interoperability and composition across, disparate, autonomous, third-party services. Our contention is that such light-weight service discovery provides a good fit for user requirements of bioinformatics and possibly other domains.

Abstract-While workflow technology has gained momentum in the last decade as a means for specifying and enacting computational experiments in modern science, reusing and repurposing existing workflows to build new scientific experiments is still a daunting task. This is partly due to the difficulty that scientists experience when attempting to understand existing workflows, which contain several data preparation and adaptation steps in addition to the scientifically significant analysis steps. One way to tackle the understandability problem is through providing abstractions that give a high-level view of activities undertaken within workflows. As a first step towards abstractions, we report in this paper on the results of a manual analysis performed over a set of real-world scientific workflows from Taverna and Wings systems. Our analysis has resulted in a set of scientific workflow motifs that outline i) the kinds of data intensive activities that are observed in workflows (data oriented motifs), and ii) the different manners in which activities are implemented within workflows (workflow oriented motifs). These motifs can be useful to inform workflow designers on the good and bad practices for workflow development, to inform the design of automated tools for the generation of workflow abstractions, etc.

(my)Grid supports in silico experiments in the life sciences, enabling the design and enactment of workflows as well as providing components to assist service discovery, data and metadata management. The (my)Grid ontology is one component in a larger semantic discovery framework for the identification of the highly distributed and heterogeneous bioinformatics services in the public domain. From an initial model of formal OWL-DL semantics throughout, we now adopt a spectrum of expressivity and reasoning for different tasks in service annotation and discovery. Here, we discuss the development and use of the (my)Grid ontology and our experiences in semantic service discovery.

The Grid's vision, of sharing diverse resources in a flexible, coordinated and secure manner through dynamic formation and disbanding of virtual communities, strongly depends on metadata. Currently, Grid metadata is generated and used in an ad hoc fashion, much of it buried in the Grid middleware's code libraries and database schemas. This ad hoc expression and use of metadata causes chronic dependency on human intervention during the operation of Grid machinery, leading to systems which are brittle when faced with frequent syntactic changes in resource coordination and sharing protocols. The Semantic Grid is an extension of the Grid in which rich resource metadata is exposed and handled explicitly, and shared and managed via Grid protocols. The layering of an explicit semantic infrastructure over the Grid Infrastructure potentially leads to increased interoperability and greater flexibility. In recent years, several projects have embraced the Semantic Grid vision. However, the Semantic Grid lacks a Reference Architecture or any kind of systematic framework for designing Semantic Grid components or applications. The Open Grid Service Architecture (OGSA) aims to define a core set of capabilities and behaviours for Grid systems. We propose a Reference Architecture that extends OGSA to support the explicit handling of semantics, and defines the associated knowledge services to support a spectrum of service capabilities. Guided by a set of design principles, Semantic-OGSA (S-OGSA) defines a model, the capabilities and the mechanisms for the Semantic Grid. We conclude by highlighting the commonalities and differences that the proposed architecture has with respect to other Grid frameworks.