There seems to be a general consensus on the crucial role metadata can play for enhancing the functionalities of scientific workflows systems, e.g., workflow and service discovery, composition and provenance browsing, among others. However, in most cases their management is under-specified, if not left unaddressed at all. A step in this direction, the main contribution of the work presented in this paper is an overview of metadata and their management in the Taverna workflow system. In Taverna, we consider metadata to be a first class citizen in the system, in the sense that we fully cover their life cycle from their creation, through their use and curation until their eventual removal. We present the main steps of this cycle and present the models used for metadata specification. In doing so, we distinguish two classes of metadata: metadata that describe workflow related entities, such as services, workflows and sub- workflows, and metadata that describe workflow executions, also known as workflow provenance.

UNLABELLED: Taverna is an application that eases the integration of tools and databases for life science research by the construction of workflows. The Taverna Interaction Service extends the functionality of Taverna by defining human interaction within a workflow and acting as a mediation layer between the automated workflow engine and one or more users. AVAILABILITY: Taverna, the Interaction Service plug-in and web application are available as open source and can be downloaded from http://taverna.sourceforge.net/

UNLABELLED: Many data manipulation processes involve the use of programming libraries. These processes may beneficially be automated due to their repeated use. A convenient type of automation is in the form of workflows that also allow such processes to be shared amongst the community. The Taverna workflow system has been extended to enable it to use and invoke Java classes and methods as tasks within Taverna workflows. These classes and methods are selected for use during workflow construction by a Java Doclet application called the API Consumer. This selection is stored as an XML file which enables Taverna to present the subset of the API for use in the composition of workflows. The ability of Taverna to invoke Java classes and methods is demonstrated by a workflow in which we use libSBML to map gene expression data onto a metabolic pathway represented as a SBML model. AVAILABILITY: Taverna and the API Consumer application can be freely downloaded from http://taverna.sourceforge.net

BACKGROUND: There has been a dramatic increase in the amount of quantitative data derived from the measurement of changes at different levels of biological complexity during the post-genomic era. However, there are a number of issues associated with the use of computational tools employed for the analysis of such data. For example, computational tools such as R and MATLAB require prior knowledge of their programming languages in order to implement statistical analyses on data. Combining two or more tools in an analysis may also be problematic since data may have to be manually copied and pasted between separate user interfaces for each tool. Furthermore, this transfer of data may require a reconciliation step in order for there to be interoperability between computational tools. RESULTS: Developments in the Taverna workflow system have enabled pipelines to be constructed and enacted for generic and ad hoc analyses of quantitative data. Here, we present an example of such a workflow involving the statistical identification of differentially-expressed genes from microarray data followed by the annotation of their relationships to cellular processes. This workflow makes use of customised maxdBrowse web services, a system that allows Taverna to query and retrieve gene expression data from the maxdLoad2 microarray database. These data are then analysed by R to identify differentially-expressed genes using the Taverna RShell processor which has been developed for invoking this tool when it has been deployed as a service using the RServe library. In addition, the workflow uses Beanshell scripts to reconcile mismatches of data between services as well as to implement a form of user interaction for selecting subsets of microarray data for analysis as part of the workflow execution. A new plugin system in the Taverna software architecture is demonstrated by the use of renderers for displaying PDF files and CSV formatted data within the Taverna workbench. CONCLUSION: Taverna can be used by data analysis experts as a generic tool for composing ad hoc analyses of quantitative data by combining the use of scripts written in the R programming language with tools exposed as services in workflows. When these workflows are shared with colleagues and the wider scientific community, they provide an approach for other scientists wanting to use tools such as R without having to learn the corresponding programming language to analyse their own data.

Workflows systems are steadily finding their way into the work practices of scientists. This is particularly true in the in silico science of bioinformatics, where biological data can be processed by Web services. In this paper we investigate the potential of evolving the users' interaction with workflow environments so that it more closely relates to the mode in which their day to day work is carried out. We present the Data Playground, an environment designed to encourage the uptake of workflow systems in bioinformatics through more intuitive interaction by focusing the user on their data rather than on the processes. We implement a prototype plug-in for the Taverna workflow environment and show how this can promote the creation of workflow fragments by automatically converting the users' interactions with data and Web services into a more conventional workflow specification.

This paper presents the formal syntax and the operational semantics of Taverna, a workflow management system with a large user base among the e-Science community. Such formal foundation, which has so far been lacking, opens the way to the translation between Taverna workflows and other process models. In particular, the ability to automatically compile a simple domain-specific process description into Taverna facilitates its adoption by e-scientists who are not expert workflow developers. We demonstrate this potential through a practical use case.

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.

The Taverna e-Science Workbench is a central component of myGrid, a loosely coupled suite of middleware services designed to support in silico experiments in biology. Taverna enables the construction and enactment of complex workflows over resources on local and remote machines, allowing the automation of otherwise labour-intensive multi-step bioinformatics tasks. As the Taverna user community has grown, so has the demand for new features and additions. This paper outlines the functional requirements that have become apparent over the last year of working with domain scientists, along with the solutions implemented in both the Taverna workbench and the Freefluo enactment engine to address concerns relating to workflow construction and enactment, respectively

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.

Abstract Motivation: The SWISS-PROT group at the EBI has developed the Proteome Analysis Database utilizing existing resources and providing comprehensive and integrated comparative analysis of the predicted protein coding sequencesof the complete genomes of bacteria, archaea and eukaryotes. The Proteome Analysis Database is accompanied by a program that has been designed to carry out interactive InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database. Availability: http://www.ebi.ac.uk/proteome/comparisons.html Contact: [email protected]; [email protected] * To whom all correspondence should be addressed.

MOTIVATION: InterPro is a new integrated documentation resource for protein families, domains and functional sites, developed initially as a means of rationalising the complementary efforts of the PROSITE, PRINTS, Pfam and ProDom database projects. RESULTS: Merged annotations from PRINTS, PROSITE and Pfam form the InterPro core. Each combined InterPro entry includes functional descriptions and literature references, and links are made back to the relevant parent database(s), allowing users to see at a glance whether a particular family or domain has associated patterns, profiles, fingerprints, etc. Merged and individual entries (i.e. those that have no counterpart in the companion resources) are assigned unique accession numbers. Release 1.2 of InterPro (June 2000) contains over 3000 entries, representing families, domains, repeats and sites of post-translational modification (PTMs) encoded by 6581 different regular expressions, profiles, fingerprints and Hidden Markov Models (HMMs). Each InterPro entry lists all the matches against SWISS-PROT and TrEMBL (more than 1000000 hits from 264333 different proteins out of 384572 in SWISS-PROT and TrEMBL).