Abstract In this paper we outline a framework for managing information quality (IQ) in an e‐Science context. In contrast to previous approaches that take a very abstract view of IQ properties, we allow scientists to define the quality characteristics that are of importance to them in their particular domain. For example, ‘accuracy’ may be defined in terms of the conformance of experimental data to a particular standard. User‐scientists specify their IQ preferences against a formal ontology, so that the definitions are machine‐manipulable, allowing the environment to classify and organize domain‐specific quality characteristics within an overall quality management framework. As an illustration of our approach, we present an example Web service that computes IQ annotations for experiment datasets in transcriptomics. Copyright © 2007 John Wiley & Sons, Ltd.

Data-intensive e-science applications often rely on third-party data found in public repositories, whose quality is largely unknown. Although scientists are aware that this uncertainty may lead to incorrect scientific conclusions, in the absence of a quantitative characterization of data quality properties they find it difficult to formulate precise data acceptability criteria. We present an Information Quality management workbench, called Qurator, that supports data experts in the specification of personal quality models, and lets them derive effective criteria for data acceptability. The demo of our working prototype will illustrate our approach on a real e-science workflow for a bioinformatics application.

Modern software development practices show that there is significant diversity in the product, process and geographical location of software development due to economical, technical and logistical constraints. Such diverse development demands flexibility in the software engineering methodology. In this paper, we propose the cellular development methodology (CDM), an architecture-driven approach to flexible software development. CDM derives the development process and its architecture from the software architecture of product. The software development process is structured and customised as a network of cooperating cells. Our contribution is a cellular approach to software development based on the software architecture of the end product whereby a network of configurable cells yield customisable, potentially distributed software development processes which in turn produce software that is highly tailored to user requirements.

Abstract Life sciences research is based on individuals, often with diverse skills, assembled into research groups. These groups use their specialist expertise to address scientific problems. The in silico experiments undertaken by these research groups can be represented as workflows involving the co‐ordinated use of analysis programs and information repositories that may be globally distributed. With regards to Grid computing, the requirements relate to the sharing of analysis and information resources rather than sharing computational power. The myGrid project has developed the Taverna Workbench for the composition and execution of workflows for the life sciences community. This experience paper describes lessons learnt during the development of Taverna. A common theme is the importance of understanding how workflows fit into the scientists' experimental context. The lessons reflect an evolving understanding of life scientists' requirements on a workflow environment, which is relevant to other areas of data intensive and exploratory science. Copyright © 2005 John Wiley & Sons, Ltd.

Software that cannot evolve is condemned to atrophy: it cannot accommodate the constant revision and re-negotiation of its business goals nor intercept the potential of new technology. To accommodate change in software systems, we have defined an active software architecture to be: dynamic in that the structure and cardinality of the components and interactions are changeable during execution; updatable in that components can be replaced; decomposable in that an executing system may be (partially) stopped and split up into its components and interactions; and reflective in that the specification of components and interactions may be evolved during execution. Here we describe the facilities of the ArchWare architecture description language (ADL) for specifying active architectures. The contribution of the work is the unique combination of concepts including: a /spl pi/-calculus based communication and expression language for specifying executable architectures; hyper-code as an underlying representation of system execution that can be used for introspection; a decomposition operator to incrementally break up executing systems; and structural reflection for creating new components and binding them into running systems.

MOTIVATION: In silico experiments in bioinformatics involve the co-ordinated use of computational tools and information repositories. A growing number of these resources are being made available with programmatic access in the form of Web services. Bioinformatics scientists will need to orchestrate these Web services in workflows as part of their analyses. RESULTS: The Taverna project has developed a tool for the composition and enactment of bioinformatics workflows for the life sciences community. The tool includes a workbench application which provides a graphical user interface for the composition of workflows. These workflows are written in a new language called the simple conceptual unified flow language (Scufl), where by each step within a workflow represents one atomic task. Two examples are used to illustrate the ease by which in silico experiments can be represented as Scufl workflows using the workbench application.

My Grid is an e-Science Grid project that aims to help biologists and bioinformaticians to perform workflow-based in silico experiments, and help them to automate the management of such workflows through personalisation, notification of change and publication of experiments. In this paper, we describe the architecture of my Grid and how it will be used by the scientist. We then show how my Grid can benefit from agents technologies. We have identified three key uses of agent technologies in my Grid: user agents, able to customize and personalise data, agent communication languages offering a generic and portable communication medium, and negotiation allowing multiple distributed entities to reach service level agreements.

The growing quantity and distribution of bioinformatics resources means that finding and utilizing them requires a great deal of expert knowledge, especially as many resources need to be tied together into a workflow to accomplish a useful goal. We want to formally capture at least some of this knowledge within a virtual workbench and middleware framework to assist a wider range of biologists in utilizing these resources. Different activities require different representations of knowledge. Finding or substituting a service within a workflow is often best supported by a classification. Marshalling and configuring services is best accomplished using a formal description. Both representations are highly interdependent and maintaining consistency between the two by hand is difficult. We report on a description logic approach using the web ontology language DAML+OIL that uses property based service descriptions. The ontology is founded on DAML-S to dynamically create service classifications. These classifications are then used to support semantic service matching and discovery in a large grid based middleware project [Formula: see text]. We describe the extensions necessary to DAML-S in order to support bioinformatics service description; the utility of DAML+OIL in creating dynamic classifications based on formal descriptions; and the implementation of a DAML+OIL ontology service to support partial user-driven service matching and composition.

In this paper we report on the 8th European Workshop on Software Process Technology held in Witten (Germany) in June 2001. We also report on the outcome of a working session about the future directions of research in software process technology that will be addressed in the next workshop of this series.

The changing needs of modern application systems demand new and radical software architectures to support them. The attraction of persistent systems is that they define precisely the extent to which they are open, thereby allowing the dynamically changing resource requirements of applications to be tracked accurately within the persistent environment. Thus, an ever-growing body of work is being established to study the nature of running applications, and to use the information gleaned, to improve the run-time execution of these applications. Here we propose a new architectural approach to constructing persistent systems that accommodates, and thus is compliant to, the needs of particular applications. By separating policy from mechanism in all components, the architecture may be tailored to the policy needs of the application. (Policy may be regarded as strategy for achieving a goal, such as a cache eviction algorithm, whereas mechanism is the method by which the objective is achieved, such as the physical movement of the cache lines. As we see later, policy and mechanism are composable to form new mechanism.) We first propose a generic architecture for compliance, and then show how it may be instantiated. Finally, we describe an example of how the architecture operates in a manner that is compliant to a target application. We postulate, since we have not yet measured, that the benefits of compliant architectures will be a reduction in complexity, with corresponding gains in flexibility, portability, understandability in terms of failure semantics, and performance. Copyright © 2000 John Wiley & Sons, Ltd.

The cost-effective and reliable evolution of systems is a significant software engineering challenge. Our approach is based on a combination of product modelling, process modelling and software metrics. We describe an empirical laboratory study following the evolution of three releases of a publicly available exemplar system. Analysis of the metrics which were collected improves our understanding of how a system evolves. Process metrics can provide information about how the product is put together, and product metrics suggest explanations for the development processes observed.