Taverna: a Workbench for the Design and Execution of Scientific Workflows
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Understanding Semantic Aware Grid Middleware for E-Science
Computing and Informatics, Vol. 27, 2008, 93–118 UNDERSTANDING SEMANTIC AWARE GRID MIDDLEWARE FOR E-SCIENCE Pinar Alper, Carole Goble School of Computer Science, University of Manchester, Manchester, UK e-mail: penpecip, carole @cs.man.ac.uk { } Oscar Corcho School of Computer Science, University of Manchester, Manchester, UK & Facultad de Inform´atica, Universidad Polit´ecnica de Madrid Boadilla del Monte, ES e-mail: [email protected] Revised manuscript received 11 January 2007 Abstract. In this paper we analyze several semantic-aware Grid middleware ser- vices used in e-Science applications. We describe them according to a common analysis framework, so as to find their commonalities and their distinguishing fea- tures. As a result of this analysis we categorize these services into three groups: information services, data access services and decision support services. We make comparisons and provide additional conclusions that are useful to understand bet- ter how these services have been developed and deployed, and how similar ser- vices would be developed in the future, mainly in the context of e-Science applica- tions. Keywords: Semantic grid, middleware, e-science 1 INTRODUCTION The Science 2020 report [40] stresses the importance of understanding and manag- ing the semantics of data used in scientific applications as one of the key enablers of 94 P. Alper, C. Goble, O. Corcho future e-Science. This involves aspects like understanding metadata, ensuring data quality and accuracy, dealing with data provenance (where and how it was pro- duced), etc. The report also stresses the fact that metadata is not simply for human consumption, but primarily used by tools that perform data integration and exploit web services and workflows that transform the data, compute new derived data, etc. -
Description Logics Emerge from Ivory Towers Deborah L
Description Logics Emerge from Ivory Towers Deborah L. McGuinness Stanford University, Stanford, CA, 94305 [email protected] Abstract: Description logic (DL) has existed as a field for a few decades yet somewhat recently have appeared to transform from an area of academic interest to an area of broad interest. This paper provides a brief historical perspective of description logic developments that have impacted their usability beyond just in universities and research labs and provides one perspective on the topic. Description logics (previously called terminological logics and KL-ONE-like systems) started with a motivation of providing a formal foundation for semantic networks. The first implemented DL system – KL-ONE – grew out of Brachman’s thesis [Brachman, 1977]. This work was influenced by the work on frame systems but was focused on providing a foundation for building term meanings in a semantically meaningful and unambiguous manner. It rejected the notion of maintaining an ever growing (seemingly adhoc) vocabulary of link and node names seen in semantic networks and instead embraced the notion of a fixed set of domain-independent “epistemological primitives” that could be used to construct complex, structured object descriptions. It included constructs such as “defines-an-attribute-of” as a built-in construct and expected terms like “has-employee” to be higher-level terms built up from the epistemological primitives. Higher level terms such as “has-employee” and “has-part-time-employee” could be related automatically based on term definitions instead of requiring a user to place links between them. In its original incarnation, this led to maintaining the motivation of semantic networks of providing broad expressive capabilities (since people wanted to be able to represent natural language applications) coupled with the motivation of providing a foundation of building blocks that could be used in a principled and well-defined manner. -
Open PHACTS: Semantic Interoperability for Drug Discovery
REVIEWS Drug Discovery Today Volume 17, Numbers 21/22 November 2012 Reviews KEYNOTE REVIEW Open PHACTS: semantic interoperability for drug discovery 1 2 3 Antony J. Williams Antony J. Williams , Lee Harland , Paul Groth , graduated with a PhD in 4 5,6 chemistry as an NMR Stephen Pettifer , Christine Chichester , spectroscopist. Antony 7 6,7 8 Williams is currently VP, Egon L. Willighagen , Chris T. Evelo , Niklas Blomberg , Strategic development for 9 4 6 ChemSpider at the Royal Gerhard Ecker , Carole Goble and Barend Mons Society of Chemistry. He has written chapters for many 1 Royal Society of Chemistry, ChemSpider, US Office, 904 Tamaras Circle, Wake Forest, NC 27587, USA books and authored >140 2 Connected Discovery Ltd., 27 Old Gloucester Street, London, WC1N 3AX, UK peer reviewed papers and 3 book chapters on NMR, predictive ADME methods, VU University Amsterdam, Room T-365, De Boelelaan 1081a, 1081 HV Amsterdam, The Netherlands 4 internet-based tools, crowdsourcing and database School of Computer Science, The University of Manchester, Oxford Road, Manchester M13 9PL, UK 5 curation. He is an active blogger and participant in the Swiss Institute of Bioinformatics, CMU, Rue Michel-Servet 1, 1211 Geneva 4, Switzerland Internet chemistry network as @ChemConnector. 6 Netherlands Bioinformatics Center, P. O. Box 9101, 6500 HB Nijmegen, and Leiden University Medical Center, The Netherlands Lee Harland 7 is the Founder & Chief Department of Bioinformatics – BiGCaT, Maastricht University, The Netherlands 8 Technical Officer of Respiratory & Inflammation iMed, AstraZeneca R&D Mo¨lndal, S-431 83 Mo¨lndal, Sweden 9 ConnectedDiscovery, a University of Vienna, Department of Medicinal Chemistry, Althanstraße 14, 1090 Wien, Austria company established to promote and manage precompetitive collaboration Open PHACTS is a public–private partnership between academia, within the life science industry. -
Kaleidoquery: a Visual Query Language for Object Databases
Kaleidoquery: A Visual Query Language for Object Databases Norman Murray, Norman Paton and Carole Goble Department of Computer Science University of Manchester Oxford Road, Manchester, M13 9PL, UK E-mail: murrayn, norm, carole ¡ @cs.man.ac.uk ABSTRACT duction to one of the query environments that has been im- In this paper we describe Kaleidoquery, a visual query lan- plemented for the language, concluding with a discussion of guage for object databases with the same expressive power related work and a summary. as OQL. We will describe the design philosophy behind the filter flow nature of Kaleidoquery and present each of the LANGUAGE DESCRIPTION language’s constructs, giving examples and relating them to Graph based query languages tend to use a representation of OQL. The Kaleidoquery language is described independent the database schema as the starting point for querying the of any implementation details, but a brief description of a database. The user selects parts of the schema and constructs 3D interface currently under construction for Kaleidoquery a query from these by combining them with query operators. is presented. The queries in this implementation of the lan- A problem with graph based queries is that they depict the guage are translated into OQL and then passed to the object database schema using entity-relationship diagrams or some database O ¢ for evaluation. other notation that, while readable for a database designer, exploits an abstract symbolic notation that may at first prove KEYWORDS: Visual query language, OQL, object data- cumbersome to the casual user of a database and require bases, three-dimensional interface. -
The Fourth Paradigm
ABOUT THE FOURTH PARADIGM This book presents the first broad look at the rapidly emerging field of data- THE FOUR intensive science, with the goal of influencing the worldwide scientific and com- puting research communities and inspiring the next generation of scientists. Increasingly, scientific breakthroughs will be powered by advanced computing capabilities that help researchers manipulate and explore massive datasets. The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud- computing technologies. This collection of essays expands on the vision of pio- T neering computer scientist Jim Gray for a new, fourth paradigm of discovery based H PARADIGM on data-intensive science and offers insights into how it can be fully realized. “The impact of Jim Gray’s thinking is continuing to get people to think in a new way about how data and software are redefining what it means to do science.” —Bill GaTES “I often tell people working in eScience that they aren’t in this field because they are visionaries or super-intelligent—it’s because they care about science The and they are alive now. It is about technology changing the world, and science taking advantage of it, to do more and do better.” —RhyS FRANCIS, AUSTRALIAN eRESEARCH INFRASTRUCTURE COUNCIL F OURTH “One of the greatest challenges for 21st-century science is how we respond to this new era of data-intensive -
The Design and Realisation of the Myexperiment Virtual Research Environment for Social Sharing of Workflows
The Design and Realisation of the myExperiment Virtual Research Environment for Social Sharing of Workflows David De Roure a Carole Goble b Robert Stevens b aUniversity of Southampton, UK bThe University of Manchester, UK Abstract In this paper we suggest that the full scientific potential of workflows will be achieved through mechanisms for sharing and collaboration, empowering scientists to spread their experimental protocols and to benefit from those of others. To facilitate this process we have designed and built the myExperiment Virtual Research Environ- ment for collaboration and sharing of workflows and experiments. In contrast to systems which simply make workflows available, myExperiment provides mecha- nisms to support the sharing of workflows within and across multiple communities. It achieves this by adopting a social web approach which is tailored to the par- ticular needs of the scientist. We present the motivation, design and realisation of myExperiment. Key words: Scientific Workflow, Workflow Management, Virtual Research Environment, Collaborative Computing, Taverna Workflow Workbench 1 Introduction Scientific workflows are attracting considerable attention in the community. Increasingly they support scientists in advancing research through in silico ex- perimentation, while the workflow systems themselves are the subject of ongo- ing research and development (1). The National Science Foundation Workshop on the Challenges of Scientific Workflows identified the potential for scientific advance as workflow systems address more sophisticated requirements and as workflows are created through collaborative design processes involving many scientists across disciplines (2). Rather than looking at the application or ma- chinery of workflow systems, it is this dimension of collaboration and sharing that is the focus of this paper. -
Data Curation+Process Curation^Data Integration+Science
BRIEFINGS IN BIOINFORMATICS. VOL 9. NO 6. 506^517 doi:10.1093/bib/bbn034 Advance Access publication December 6, 2008 Data curation 1 process curation^data integration 1 science Carole Goble, Robert Stevens, Duncan Hull, Katy Wolstencroft and Rodrigo Lopez Submitted: 16th May 2008; Received (in revised form): 25th July 2008 Abstract In bioinformatics, we are familiar with the idea of curated data as a prerequisite for data integration. We neglect, often to our cost, the curation and cataloguing of the processes that we use to integrate and analyse our data. Downloaded from https://academic.oup.com/bib/article/9/6/506/223646 by guest on 27 September 2021 Programmatic access to services, for data and processes, means that compositions of services can be made that represent the in silico experiments or processes that bioinformaticians perform. Data integration through workflows depends on being able to know what services exist and where to find those services. The large number of services and the operations they perform, their arbitrary naming and lack of documentation, however, mean that they can be difficult to use. The workflows themselves are composite processes that could be pooled and reused but only if they too can be found and understood. Thus appropriate curation, including semantic mark-up, would enable processes to be found, maintained and consequently used more easily.This broader view on semantic annotation is vital for full data integration that is necessary for the modern scientific analyses in biology.This article will brief the community on the current state of the art and the current challenges for process curation, both within and without the Life Sciences. -
Acrobat Distiller, Job 5
Information Management for Genome Level Bioinformatics - Paton, Goble Information Management for Genome Level Bioinformatics Norman Paton and Carole Goble Department of Computer Science University of Manchester Manchester, UK <norm, carole>@cs.man.ac.uk Structure of Tutorial Introduction - why it matters. Genome level data. Genomic databases. Modelling challenges. Integrating biological databases. Analysing genomic data. Summary and challenges. 213 Information Management for Genome Level Bioinformatics - Paton, Goble Information Management for Genome Level Bioinformatics Norman Paton and Carole Goble Department of Computer Science University of Manchester Manchester, UK <norm, carole>@cs.man.ac.uk Structure of Tutorial Introduction - why it matters. Genome level data. Modelling challenges. Genomic databases. Integrating biological databases. Analysing genomic data. Summary and challenges. 214 Information Management for Genome Level Bioinformatics - Paton, Goble What is the Genome? All the genetic material in the chromosomes of a particular organism. What is Genomics? The systematic application of (high throughput) molecular biology techniques to examine the whole genetic content of cells. Understand the meaning of the genomic information and how and when this information is expressed. 215 Information Management for Genome Level Bioinformatics - Paton, Goble What is Bioinformatics? “The application and development of computing and mathematics to the management, analysis and understanding of the rapidly expanding amount -
Social Networking Site for Researchers Aims to Make Academic Papers a Thing of the Past 16 July 2009
Social networking site for researchers aims to make academic papers a thing of the past 16 July 2009 myExperiment, the social networking site for and traditional ideas of repositories,’ said Professor scientists, has set out to challenge traditional ideas Carole Goble. ‘myExperiment paves the way for of academic publishing as it enters a new phase of the next generation of researchers to do new funding. research using new research methods.’ The site has just received a further £250,000 In its first year, the myExperiment.org website has funding from the Joint Information Systems attracted thousands of users worldwide and Committee (JISC) as part of the JISC Information established the largest public collection of its kind. Environment programme to improve scholarly communication in contemporary research practice. More information: www.myexperiment.org According to Professor David De Roure at the Source: University of Southampton University of Southampton’s School of Electronics and Computer Science, who has developed the site jointly with Professor Carole Goble at the University of Manchester, researchers will in the future be sharing new forms of “Research Objects” rather than academic publications. Research Objects contain everything needed to understand and reuse a piece of research, including workflows, data, research outputs and provenance information. They provide a systematic and unbiased approach to research, essential when researchers are faced with a deluge of data. ‘We are introducing new approaches to make research more reproducible, reusable and reliable,’ Professor De Roure said. ‘Research Objects are self-contained pieces of reproducible research which we will share in the future like papers are shared today.’ The myExperiment Enhancement project will integrate myExperiment with the established EPrints research repository in Southampton and Manchester’s new e-Scholar institutional repository. -
Data Management in Systems Biology I
Data management in systems biology I – Overview and bibliography Gerhard Mayer, University of Stuttgart, Institute of Biochemical Engineering (IBVT), Allmandring 31, D-70569 Stuttgart Abstract Large systems biology projects can encompass several workgroups often located in different countries. An overview about existing data standards in systems biology and the management, storage, exchange and integration of the generated data in large distributed research projects is given, the pros and cons of the different approaches are illustrated from a practical point of view, the existing software – open source as well as commercial - and the relevant literature is extensively overviewed, so that the reader should be enabled to decide which data management approach is the best suited for his special needs. An emphasis is laid on the use of workflow systems and of TAB-based formats. The data in this format can be viewed and edited easily using spreadsheet programs which are familiar to the working experimental biologists. The use of workflows for the standardized access to data in either own or publicly available databanks and the standardization of operation procedures is presented. The use of ontologies and semantic web technologies for data management will be discussed in a further paper. Keywords: MIBBI; data standards; data management; data integration; databases; TAB-based formats; workflows; Open Data INTRODUCTION the foundation of a new journal about biological The large amount of data produced by biological databases [24], the foundation of the ISB research projects grows at a fast rate. The 2009 (International Society for Biocuration) and special edition of the annual Nucleic Acids Research conferences like DILS (Data Integration in the Life database issue mentions 1170 databases [1]; alone Sciences) [25]. -
Distributed Computing Environments and Workflows for Systems
Going with the Flow Distributed Computing for Systems Biology Using Taverna Prof Carole Goble The University of Manchester, UK http://www.mygrid.org.uk http://www.omii.ac.uk Data pipelines in bioinformatics Genscan Resources /Services EMBL BLAST Clustal-W Multiple Query Protein sequences Clustal-W sequence alignment 2 Example in silico experiment: Investigate© the evolutionary relationships between proteins [Peter Li] z Manual creation z Semi-automation using bespoke software 12181 acatttctac caacagtgga tgaggttgtt ggtctatgtt ctcaccaaat ttggtgttgt 12241 cagtctttta aattttaacc tttagagaag agtcatacag tcaatagcct tttttagctt z Issues: 12301 gaccatccta atagatacac agtggtgtct cactgtgatt ttaatttgca ttttcctgct 12361 gactaattat gttgagcttg ttaccattta gacaacttca ttagagaagt gtctaatatt 12421 taggtgactt gcctgttttt ttttaattgg gatcttaatt tttttaaatt attgatttgt 12481 aggagctatt tatatattct ggatacaagt tctttatcag atacacagtt tgtgactatt z Volatility of data12541 ttcttataag in tctgtggtttlife ttatattaatsciences gtttttattg atgactgttt tttacaattg 12601 tggttaagta tacatgacat aaaacggatt atcttaacca ttttaaaatg taaaattcga 12661 tggcattaag tacatccaca atattgtgca actatcacca ctatcatact ccaaaagggc 12721 atccaatacc cattaagctg tcactcccca atctcccatt ttcccacccc tgacaatcaa z Data and metadata12781 taacccattt tctgtctcta storage tggatttgcc tgttctggat attcatatta atagaatcaa z Integration of heterogeneous biological data z Visualisation of models z Brittleness 3 © 12181 acatttctac caacagtgga tgaggttgtt ggtctatgtt ctcaccaaat ttggtgttgt 12241 cagtctttta aattttaacc tttagagaag agtcatacag tcaatagcct -
Mygrid: a Collection of Web Pages
Home The myGrid team produce and use a suite of tools designed to “help e-Scientists get on with science and get on with scientists”. The tools support the creation of e-laboratories and have been used in domains as diverse as systems biology, social science, music, astronomy, multimedia and chemistry. The tools have been adopted by a large number of projects and institutions. The team has developed tools and infrastructure to allow: • the design, editing and execution of workflows in Taverna • the sharing of workflows and related data by myExperiment • the cataloguing and annotation of services in BioCatalogue and Feta • the creation of user-friendly rich clients such as UTOPIA These tools help to form the basis for the team’s work on e-Labs. Taverna Workbench 2.1.2 available for download The myGrid team have released Taverna Workbench 2.1.2. It supports secure access to data on the web, secure web services and secured private workflows. Taverna 2.1.2 includes • Copy/paste, shortcuts, undo/redo, drag and drop • Animated workflow diagram • Remembers added/removed services • Secure Web services support • Secure access to resources on the web • Up-to-date R support • Intermediate values during workflow runs • myExperiment integration • Excel and csv spreadsheet support Hosted at the School of Computer Science, University of Manchester, UK. Copyright 2008 - All Rights Reserved Sponsored by Microsoft, EPSRC, BBSRC, ESRC and JISC From www.mygrid.org.uk/ 1 27 May 2010 Outreach >Outreach The myGrid consortium put a lot of effort into reaching out to users. The team do not just “preach to the converted” but seek new users by offering Tutorials and giving talks, papers and posters in a very wide variety of places.