1. my Grid and Taverna: Now and in the Future Dr. K. Wolstencroft University of Manchester

2. Background my Grid middleware components to support in silico experiments in biology Originally designed to support bioinformatics chemoinformatics health informatics medical imaging integrative biology

3. History EPSRC funded UK eScience Program Pilot Project

4. my Grid in OMII-UK OGSA-DAI my Grid OMII Stack March 2006 10 Developers Dedicated design, implementation, testing and support team – moving towards production quality software

5. Lots of Resources NAR 2006 – over 850 databases

6. The User Community Bioinformatics is an open Community Open access to data Open access to resources Open access to tools Open access to applications Global in silico biological research

7. The User Community Problems Everything is Distributed –Data, Resources and Scientists Heterogeneous data Very few standards –I/O formats, data representation, annotation –Everything is a string! Integration of data and interoperability of resources is difficult

8. ID MURA_BACSU STANDARD; PRT; 429 AA. DE PROBABLE UDP-N-ACETYLGLUCOSAMINE 1-CARBOXYVINYLTRANSFERASE DE (EC 2.5.1.7) (ENOYLPYRUVATE TRANSFERASE) (UDP-N-ACETYLGLUCOSAMINE DE ENOLPYRUVYL TRANSFERASE) (EPT). GN MURA OR MURZ. OS BACILLUS SUBTILIS. OC BACTERIA; FIRMICUTES; BACILLUS/CLOSTRIDIUM GROUP; BACILLACEAE; OC BACILLUS. KW PEPTIDOGLYCAN SYNTHESIS; CELL WALL; TRANSFERASE. FT ACT_SITE 116 116 BINDS PEP (BY SIMILARITY). FT CONFLICT 374 374 S -> A (IN REF. 3). SQ SEQUENCE 429 AA; 46016 MW; 02018C5C CRC32; MEKLNIAGGD SLNGTVHISG AKNSAVALIP ATILANSEVT IEGLPEISDI ETLRDLLKEI GGNVHFENGE MVVDPTSMIS MPLPNGKVKK LRASYYLMGA MLGRFKQAVI GLPGGCHLGP RPIDQHIKGF EALGAEVTNE QGAIYLRAER LRGARIYLDV VSVGATINIM LAAVLAEGKT IIENAAKEPE IIDVATLLTS MGAKIKGAGT NVIRIDGVKE LHGCKHTIIP DRIEAGTFMI

9. my Grid Approach - Workflows General technique for describing and enacting a process describes what you want to do, not how you want to do it Simple language specifies how bioinformatics processes fit together – processes are web services -High level workflow diagram separated from any lower level coding – therefore, you don’t have to be a coder to build workflows Repeat Masker Web service GenScan Web Service Blast Web Service Sequence Predicted Genes out

10. Freefluo Workflow enactor Scufl + Workflow Object Model Processor Plain Web Service Soap lab Processor Local App Processor Enactor Taverna Workbench Processor Bio MOBY Processor Seq Hound Processor Bio MART SCUFL Application data flow layer Scufl graph + service introspection Execution flow layer List management; implicit iteration mechanism; MIME & semantic type decoration; fault management; service alternates Processor invocation layer Workflow Execution

11. Taverna Workflow Components Scufl Simple Conceptual Unified Flow Language Taverna Writing, running workflows & examining results SOAPLAB Makes applications available Freefluo Workflow engine to run workflows Freefluo SOAPLAB Web Service Any Application Web Service e.g. DDBJ BLAST

12. What Services we Support

13. User Interaction Handling Interaction Service and corresponding Taverna processor allows a workflow to call out to an expert human user Used to embed the Artemis annotation editor within an otherwise automated genome annotation pipeline Collaboration with the University of Bergen Ref: Poster, Nettab 2005 R for numerical analysis (microarray informatics amongst others)

14. What shall I do when a service fails? Most services are owned by other people No control over service failure Some are research level Workflows are only as good as the services they connect! To help - Taverna can: Notify failures Instigate retries Set criticality Substitute services

15. myGrid Users ~20000 downloads Users in US, Singapore, UK, Europe, Australia Systems biology Proteomics Gene/protein annotation Microarray data analysis Medical image analysis

16. Trypanosomiasis Study Resistance to trypanosomiasis in cattle in Kenya Andy Brass, Paul Fisher – University of Manchester Form of Sleeping sickness in cattle – Known as n’gana Caused by Trypanosoma brucei

17. Study involves Microarray data QTL SNPs Metabolic pathway analysis Need to access microarray data, genomic sequence information, pathway databases AND integrate the results

19. Workflow Reuse Addisons Disease SNP design Protein annotation Microarray analysis myGrid Workflow Repository http://workflows.mygrid.org.uk/repository

20. Scufl Workflows + Taverna Workflow Workbench OGSA-Distributed Query Processing Results management LSID mIR e-Science coordination e-Science mediator e-Science process patterns e-Science events Notification service Components designed to work together my Grid information model Metadata & provenance management using semantics KAVE Service management Publication and Discovery using semantics Feta Pedro Ontology Portal & Application tools

21. Data Management Workflows can generate vast amount of data - how can we manage and track it? Data AND metadata AND experiment provenance LSIDs - to identify objects Semantic Web technologies (RDF, Ontologies) –To store knowledge provenance Taverna workflow workbench & plugins –Ensure automated recording

22. KAVE Data and metadata management Life Science Identifiers (LSIDs) Information Model File management Support for custom database building Provenance metadata capture using RDF SRB integration OGSA-DAI integration urn:data: f2 urn:data1 urn:data2 urn:compareinvocation3 urn:data1 2 Blast_report [input] [output] [input] [distantlyDerivedFrom] SwissProt_seq [instanceOf] Sequence_hit [hasHits] urn:hit2 …. urn:hit1 … urn:hit50 ….. [instanceOf] [similar_sequence_to] Data generated by services/workfl ows Concepts [ ] [performsTask] Find similar sequence [contains] Services urn:data:3 urn:hit8…. urn:hit5… urn:hit10 ….. [contains] [instanceOf] urn:BlastNInvocation3 urn:invocation 5 urn:data: f1 [output] New sequence Missed sequence [hasName ] literals DatumCollection [type] LSDatum [type] Properties [instanceOf] [output] [directlyDerivedFrom ]

23. Provenance Browsing in Taverna New in Taverna 1.4

24. Feta Semantic Discovery Over 3000 services! Find services by their function Questions we can ask: Find me all the services that perform a multiple sequence alignment And accepts protein sequences in FASTA format as input

25. Upper level ontology Task ontology Informatics ontology Molecular Biology ontology Bioinformatics ontology Web Service ontology Specialises Contributes to sequence biological_sequence protein_sequence nucleotide_sequence DNA_sequence protein_structure_feature BLASTp service Similarity Search Service BLAST service InterProScan service my Grid Ontology

26. Feta Architecture Feta Engine Service Semantic Discovery Taverna Workbench Feta GUI Client DL Reasoner Ontology Editor Ontologist User Classification - In RDF(S) - Build my Grid Domain Ontology Obtain descriptions Obtain Classification 3 3 4 Feta Descriptions Feta Descriptions Feta Descriptions

27. Annotations Feta has been available for ~1 year Not yet in the release Need critical mass of services before release Annotation experiments with users and domain experts Domain expert annotations much better – –hiring a full-time annotation – see the myGrid website for details

28. Gene annotation pipeline workflow Integration and visualisation of GD annotation workflow results Provenance Record Custom Data Model Input Result Results Integration Smarter workflow design incorporating visualisation VBI collaboration

29. Utopia SeqVista Visualisation

30. New Plans for Taverna 2.0

31. Evolving challenges Long running data intensive workflows Manipulation of confidential or otherwise protected information Use with classical grid systems Interaction with users during workflows

32. Development Development of Taverna 2.0 –reworking of the processor model to include duel execution semantics incorporating data and control flow –enhanced support for long-running workflows fully distributed workflow enactment and authoring User steering – large scale data transfer

33. Enhanced Processor Model Modular dispatcher mechanism –Dynamic service binding –Recursive invocation –Data filter implementation –Retry, failover, back-off behaviours Transparent third party data transfers High throughput stream handling with implicit iteration semantics

34. 3 rd Party Data Transfers Allows ‘in place’ referencing of data –Large data sets no longer round-trip between workflow engine and data provider –Allows restricted access to sensitive data Automatic de-reference when a reference type is linked to a value type within a workflow. –Connecting a grid service to a web service

35. Streaming Data Allow execution of downstream workflow stages on partially complete results from upstream. Service 1Service 2Service 3 Non streaming (Taverna 1), entire iteration must complete at each stage Streamed data, Service 2 starts operating on partial results from Service 1

36. Recursive Invocation Dispatcher allowing recursive invocation to be plugged into per operation semantics. Gather Result Set Test For completion Modify Input Set Invoke operation Return Result Receive Input

37. Future Direction Enhancements to the Workflow Core Enhancements to user interface and experience Expanded use of semantic web technologies Code remains open source and always will

38. Latest News See plans for Taverna 2.0 on myGrid wiki Taverna development is user-driven –Please keep in touch and tell us what you would like to see by the myGrid mailing lists: Taverna Users, Taverna Hackers Bioinformatics curator for service annotation Details on the myGrid website

39. Acknowledgements The myGrid group – Past and Present OMII-uk Carole Goble Pinar Alper Tom Oiin Antoon Goderis Matthew Gamble Daniele Turi