Donal Fellows

The Taverna workflow suite: designing and executing workflows of Web Services on the desktop, web or in the cloud

The Taverna workflow tool suite (http://www.taverna.org.uk) is designed to combine distributed Web Services and/or local tools into complex analysis pipelines. These pipelines can be executed on local desktop machines or through larger infrastructure (such as supercomputers, Grids or cloud environments), using the Taverna Server. In bioinformatics, Taverna workflows are typically used in the areas of high-throughput omics analyses (for example, proteomics or transcriptomics), or for evidence gathering methods involving text mining or data mining. Through Taverna, scientists have access to several thousand different tools and resources that are freely available from a large range of life science institutions. Once constructed, the workflows are reusable, executable bioinformatics protocols that can be shared, reused and repurposed. A repository of public workflows is available at http://www.myexperiment.org. This article provides an update to the Taverna tool suite, highlighting new features and developments in the workbench and the Taverna Server.

Semantic Matching of Grid Resource Descriptions

The ability to describe the Grid resources needed by applications is essential for developing seamless access to resources on the Grid. We consider the problem of resource description in the context of a resource broker being developed in the Grid Interoperability Project (GRIP) which is able to broker for resources described by several Grid middleware systems, GT2, GT3 and Unicore. We consider it necessary to utilise a semantic matching of these resource descriptions, firstly because there is currently no common standard, but more fundamentally because we wish to make the Grid transparent at the application level. We show how the semantic approach to resource description facilitates both these aims and present the GRIP broker as a working prototype of this approach.

Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data

In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

HELIO: Discovery and analysis of data in heliophysics

Heliophysics is the study of highly energetic events that originate on the sun and propogate through the solar system. Such events can cause critical and possibly fatal disruption of the electromagnetic systems on spacecraft and on ground based structures such as electric power grids, so there is a clear need to understand the events in their totality as they propogate through space and time. This poses a fascinating eScience challenge since the data is gathered by many observatories and communities that have hitherto not needed to work together. We describe how we are developing an eScience infrastructure to make the discovery and analysis of such complex events possible for the communities of heliophysics. The new systematic and data-centric science which will develop from this will be a child of both the space and information ages.

BioVeL: a virtual laboratory for data analysis and modelling in biodiversity science and ecology

BackgroundMaking forecasts about biodiversity and giving support to policy relies increasingly on large collections of data held electronically, and on substantial computational capability and capacity to analyse, model, simulate and predict using such data. However, the physically distributed nature of data resources and of expertise in advanced analytical tools creates many challenges for the modern scientist. Across the wider biological sciences, presenting such capabilities on the Internet (as “Web services”) and using scientific workflow systems to compose them for particular tasks is a practical way to carry out robust “in silico” science. However, use of this approach in biodiversity science and ecology has thus far been quite limited.ResultsBioVeL is a virtual laboratory for data analysis and modelling in biodiversity science and ecology, freely accessible via the Internet. BioVeL includes functions for accessing and analysing data through curated Web services; for performing complex in silico analysis through exposure of R programs, workflows, and batch processing functions; for on-line collaboration through sharing of workflows and workflow runs; for experiment documentation through reproducibility and repeatability; and for computational support via seamless connections to supporting computing infrastructures. We developed and improved more than 60 Web services with significant potential in many different kinds of data analysis and modelling tasks. We composed reusable workflows using these Web services, also incorporating R programs. Deploying these tools into an easy-to-use and accessible ‘virtual laboratory’, free via the Internet, we applied the workflows in several diverse case studies. We opened the virtual laboratory for public use and through a programme of external engagement we actively encouraged scientists and third party application and tool developers to try out the services and contribute to the activity.ConclusionsOur work shows we can deliver an operational, scalable and flexible Internet-based virtual laboratory to meet new demands for data processing and analysis in biodiversity science and ecology. In particular, we have successfully integrated existing and popular tools and practices from different scientific disciplines to be used in biodiversity and ecological research.

Workflows for Heliophysics

In this paper we describe how we have introduced workflows into the working practices of a community for whom the concept of workflows is very new, namely the heliophysics community. Heliophysics is a branch of astrophysics which studies the Sun and the interactions between the Sun and the planets, by tracking solar events as they travel throughout the Solar system. Heliophysics produces two major challenges for workflow technology. Firstly it is a systems science where research is currently developed by many different communities who need reliable data models and metadata to be able to work together. Thus it has major challenges in the semantics of workflows. Secondly, the problem of time is critical in heliophysics; the workflows must take account of the propagation of events outwards from the sun. They have to address the four dimensional nature of space and time in terms of the indexing of data. We discuss how we have built an environment for Heliophysics workflows building on and extending the Taverna workflow system and utilising the myExperiment site for sharing workflows. We also describe how we have integrated the workflows into the existing practices of the communities involved in Heliophysics by developing a web portal which can hide the technical details from the users, who can concentrate on the data from their scientific point of view rather than on the methods used to integrate and process the data. This work has been developed in the EU Framework 7 project HELIO, and is being disseminated to the worldwide Heliophysics community, since Heliophysics requires integration of effort on a global scale.

Efficient CTL* model checking for analysis of rainbow designs

We describe an efficient implementation of a CTL* model-checking algorithm based on alternating automata. We use this to check properties of an asynchronous micropipeline design described in the Rainbow framework, which operates at the micropipeline level and leads to compact models of the hardware. We also use alternating automata to characterise the expressive power and model-checking complexity for sub-logics of CTL*.

Abstract modelling of asynchronous micropipeline systems using Rainbow

We consider Sutherland’s Micropipeline methodology for asynchronous hardware systems and highlight problems of design representation. The Rainbow hardware design framework supports such description, simulation and analysis of micropipeline systems. It provides a set of sub-languages each offering a different description style. Components described in the different sub-languages can be fully integrated within a single design. The framework offers abstract design description and rapid simulation at a high level for early simulation and analysis.

SYNBIOCHEM - a SynBio foundry for the biosynthesis and sustainable production of fine and speciality chemicals

The Manchester Synthetic Biology Research Centre (SYNBIOCHEM) is a foundry for the biosynthesis and sustainable production of fine and speciality chemicals. The Centres integrated technology platforms provide a unique capability to facilitate predictable engineering of microbial bio-factories for chemicals production. An overview of these capabilities is described.

HELIO: Discovery and Analysis of Data in Heliophysics

Heliophysics is the study of highly energetic events that originate on the sun and propogate through the solar system. Such events can cause critical and possibly fatal disruption of the electromagnetic systems on spacecraft and on ground based structures such as electric power grids, so there is a clear need to understand the events in their totality as they propogate through space and time. This poses a fascinating eScience challenge since the data is gathered by many observatories and communities that have hitherto not needed to work together. We describe how we are developing an eScience infrastructure to make the discovery and analysis of such complex events possible for the communities of heliophysics. The new systematic and data-centric science which will develop from this will be a child of both the space and information ages.