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David De Roure University of Southampton

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  1. David De Roure University of Southampton e-Science and the

  2. Outline • e-Science and e-Research • Enabling Technologies • Grid • Semantic Web • Semantic Grid • Building Bridges IAAI Panel

  3. Vision: e-Science e-Science is about global collaboration in key areas of science and the next generation of [computing] infrastructure that will enable it. e-Science will change the dynamic of the way science is undertaken John Taylor, Director General of UK Research Councils IAAI Panel

  4. Vision: e-Science ‘[The Grid] intends to make access to computing power, scientific data repositories and experimental facilities as easy as the Web makes access to information.’ Tony Blair, 2002 IAAI Panel

  5. Joint Information Systems Committee Research Councils Particle Physics and Astronomy Engineering and Physical Sciences Natural Environment Economic and Social Medical Biotechnology and Biological Sciences CCLRC (Arts and Humanities) UK funding context Dept of Tradeand Industry Companies University R & D EuropeanCommission IAAI Panel

  6. First Phase: 2001 –2004 Application Projects £74M All areas of science and engineering Core Programme £15M Research infrastructure £20M Collaborative industrial projects Second Phase: 2003 –2006 Application Projects £96M All areas of science and engineering Core Programme £16M Research Infrastructure £10M DTI Technology Fund UK e-Science Funding • Across all areas • Application-led • Core program IAAI Panel

  7. e-Science Core Program Four major functions: • Assist development of essential, well-engineered, generic, Grid middleware • Provide necessary infrastructure support for UK e-Science Research Council projects • Collaborate with the international e-Science and Grid communities • Work with UK industry to develop industrial-strength Grid middleware IAAI Panel

  8. myGrid pilot project • Bioinformatics • Imminent ‘deluge’ of data • Highly heterogeneous • Highly complex and inter-related • Convergence of data and literature archives IAAI Panel

  9. CombeChem pilot project Video Simulation Properties Analysis StructuresDatabase Diffractometer X-Raye-Lab Propertiese-Lab Grid Middleware IAAI Panel

  10. UK e-Science Grid Edinburgh Glasgow DL Newcastle Belfast Manchester Cambridge Oxford Hinxton RAL Cardiff London Southampton IAAI Panel

  11. UK e-Science: Phase 2 Three major new activities: • National Grid Service and Grid Operation Centre • Open Middleware Infrastructure Institute for testing, software engineering and UK repository • Digital Curation Centre to look at long-term data preservation issues IAAI Panel

  12. Grid Operation Support Centre • Deploy production ‘National Grid Service’ based on four dedicated compute and data nodes plus two UK Supercomputers • Develop operational policies, security, … • Gain experience with genuine users • Develop Web Services based e-Science Grid • Work with EU EGEE project, the NSF Cyberinfrastructure Program and A-P Grid activities IAAI Panel

  13. Open Middleware Infrastructure Institute • Repository for UK-developed Open Source ‘e-Science/Cyber-infrastructure’ Middleware • Documentation, specification, QA and standards • Fund work to bring ‘research project’ software up to ‘production strength’ • Fund Middleware projects for identified ‘gaps’ • Work with US NSF, EU Projects and others • Supported by major IT companies • Southampton selected as the OMII site IAAI Panel

  14. Digital Curation Centre • In next 5 years e-Science projects will produce more scientific data than has been collected in the whole of human history • In 20 years can guarantee that the OS and spreadsheet program and the hardware used to store data will not exist • Research curation technologies and best practice • Need to liaise closely with individual research communities, data archives and libraries • Edinburgh with Glasgow, CLRC and UKOLN selected as site of DCC IAAI Panel

  15. Typical Science GridService such as Research Database or simulation Science Grids Bioinformatics Earth Science ……. Transformed by Grid Filterto form suitable for education Campus orEnterprise Administrative Grid Education Grid Publisher Grid Learning Management Grid Student/Parent … Community Grid Digital Library Grid Informal Education (Museum) Grid Teacher Educator Grids Education as a Grid of Grids (thanks to Geoffrey Fox) IAAI Panel

  16. Vision: e-Research • Researchers working in all disciplines are faced daily with a wide variety of tasks necessary to sustain and progress their research activity • These involve the analytical aspects of their work, access to resources, collaboration with fellow researchers, and project management and admin • These tasks rapidly increase in scale and complexity as collaborations grow larger, become more geographically distributed and involve a wider range of disciplines JISC • Not just new Science • e-Social Science • e-Humanities • e-Arts • e-Research • e-Business • e-Anything • … • And new disciplines! IAAI Panel

  17. Vision: HASTAC Humanities, Arts, Science and Technology Advanced Collaboratory HASTAC is an international, interdisciplinary consortium which seeks to create, develop, advance and utilize a broad range of leading computing and information systems while contributing to an understanding of the interconnections between the human sciences, natural sciences, arts, and technology in a complex global society IAAI Panel

  18. Vision: Joining up • These visions are all about joining resources and people together in new ways in order to create new things • Researchers can focus on the real research • The research process is accelerated • New research results are possible • New research areas are possible • NB s/research/business/ IAAI Panel

  19. Vision: The Grid Courtesy of Ian Foster IAAI Panel

  20. Vision: The Grid Grid computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and, in some cases, high-performance orientation...we [define] the "Grid problem”…as flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources - what we refer to as virtual organizations From "The Anatomy of the Grid: Enabling Scalable Virtual Organizations" by Foster, Kesselman and Tuecke IAAI Panel

  21. myGrid Combechem Challenges: Unanticipated Re-use • Wish to reuse • Data • Services • Software • Knowledge IAAI Panel

  22. Outline • The e-Vision and its challenges • Enabling Technologies • Grid • Semantic Web • Semantic Grid • Building Bridges IAAI Panel

  23. On demand transparently constructed multi-organisational federations of distributed services Distributed computing middleware Computational Integration Two infrastructure enablers Grid Computing Semantic Web • An automatically processable, machine understandable web • Distributed knowledge and information management • Information integration IAAI Panel

  24. IAAI Panel

  25. Five Myths busted! • Isn’t it just for Physics? • No – Grids for Life Science and Medicine will dominate Grid applications • Think of the range and scale of data and the community! • Isn’t it just High Performance computing? • No – it’s a generic mechanism for forming, managing and disbanding dynamic federations of services • Data integration, data access, data transport will dominate • Application integration is the key IAAI Panel

  26. Five Myths busted! • Isn’t it just a bag of protocols glued together? • No – the Open Grid Service Architecture gives a well specified middleware stack built on industry standard web services • Isn’t it just Globus toolkit? • No – that is one reference implementation. • Isn’t it just a bunch of academic physicists? • No –all the commercial vendors are making serious investment. IBM DB2 and Oracle 10g will be grid-compliant IAAI Panel

  27. Specific services: drug discovery pipeline, sky surveys Grid Applications Standard services: agreement, data access and integration, workflow, security, policy, brokering… Open Grid Service Architecture Standard interfaces and behaviours for distributed systems: naming, service state, lifetime management, notification Web Service Resource Framework Web Service-Notification Standard mechanisms for describing and invoking services: WSDL, SOAP, WS-Security etc Web Services Grid Services IAAI Panel

  28. IAAI Panel

  29. Origins of the Semantic Web The Semantic Web is an extension of the current Web in which information is given a well-defined meaning, better enabling computers and people to work in cooperation. It is the idea of having data on the Web defined and linked in a way that it can be used for more effective discovery, automation, integration and reuse across various applications. The Web can reach its full potential if it becomes a place where data can be processed by automated tools as well as people. W3C Activity Statement IAAI Panel

  30. Layers of Languages Attribution Explanation We are here! Rules & Inference Ontologies Metadata annotations Standard Syntax Identity IAAI Panel

  31. Resource Description Framework • Common model for metadata • A graph of triples • Query over and link together • RDQL, repositories, integration tools, presentation tools • The Network Effect Graphic courtesy of Tim Berners-Lee IAAI Panel

  32. OWL Web Ontology Language DARPA Agent Markup Language Ontology Inference Layer DAML OIL RDF EU/NSF Joint Ad hoc Committee The most popular ontology language in the world ever! DAML+OIL All influenced by RDF OWL Lite (thesaurus) OWL DL (reason-able) OWL Full (anything goes) A W3C Recommendation OWL IAAI Panel

  33. 5 More Myths Busted! • Isn’t it just AI and distributed agents (again)? • No – It is primarily metadata integration and querying • Don’t you need all that reasoning stuff? • No – A little bit of semantics goes a long way! (Hendler) • It only applies to the Web? • No – the technologies are being used for Enterprise integration, exposing data in a common model, common ontology languages, representing terminologies. • One big ontology of everything never works! • No – multiple ontologies; multiple everything! • One big Semantic Web! • No – lots of Semantic Web-lets, and expect it to break! IAAI Panel

  34. Outline • The e-Vision and its challenges • Enabling Technologies • Grid • Semantic Web • Semantic Grid • Building Bridges IAAI Panel

  35. The Semantic Grid Report 2001 • At this time, there are a number of grid applications being developed and there is a whole raft of computer technologies that provide fragments of the necessary functionality. • However there is currently a major gap between these endeavours and the vision of e-Science in which there is a high degree of easy-to-use and seamless automation and in which there are flexible collaborations and computations on a global scale. www.semanticgrid.org IAAI Panel

  36. Semantic Grid SemanticWeb SemanticGrid Scale of Interoperability ClassicalWeb ClassicalGrid Scale of data and computation Based on an idea by Norman Paton IAAI Panel

  37. Semantics in and on the Grid The Semantic Grid is an extension of the current Grid in which information and services are given well-defined meaning, better enabling computers and peopleto work in cooperation IAAI Panel

  38. Grid Computing The Semantic Grid The Semantic Web Web Services Underpinnings of e-Science Contrast with… IAAI Panel

  39. Knowledge Grid IAAI Panel

  40. Grid Computing trajectory Virtual organisations with dynamic access to unlimited resources There are SG technologies available today for immediate deployment cost For all Sharing of apps and know-how With controlled set of unknown clients Sharing standard scientific process and data, sharing of common infrastructure Between trusted partners CPU intensive workload Grid as a utility, data Grids, robust infrastructure Intra-company, intra community e.g. Life Science Grid CPU scavenging time IAAI Panel

  41. Semantics in e-Science Ontology-aided workflow construction • RDF-based service and data registries • RDF-based metadata for experimental components • RDF-based provenance graphs • OWL based controlled vocabularies for database content • OWL based integration RDF-based semantic mark up of results, logs, notes, data entries IAAI Panel

  42. Engineering Design IAAI Panel

  43. Ontologies for e-Science • User-oriented, scalable environment for domain experts to acquire, develop and use ontologies • Based on OilEd and Protégé 2000 • Transatlantic cooperation on the development of ontologies for e-Science Universities Manchester and Southampton, UK Stanford University, USA IAAI Panel

  44. Compendium Replay Collaboration tools awareness ofcolleagues’ ‘presence’ BuddySpace Access Grid Node virtual meetings mapping real time discussions/group sensemaking NetMeeting recovering information from meetings enacting decisions/coordinating activities synthesising artifacts I-X Tools IAAI Panel

  45. NASA Scenario 1. Astronauts debrief on EVA Compendium maps from trained compendium astronaut Remote Science Team (RST) on earth e.g. geologists Mars Video and Science Data Plan for next Day’s EVA 2. Virtual meeting of RST using CoAKTinG tools IAAI Panel

  46. Finding collaborators Using scaleable triple store and AKT ontology IAAI Panel

  47. GGF9 Semantic Grid Workshop • The Role of Concepts in myGrid Carole Goble • Planning and Metadata on the Computational Grid Jim Blythe • Semantic support for Grid-Enabled Design Search in Engineering Simon Cox • Knowledge Discovery and Ontology-based services on the Grid Mario Cannataro • Attaching semantic annotations to service descriptions Luc Moreau • Semantic Matching of Grid Resource Description Frameworks John Brooke • Interoperability challenges in Grid for Industrial Applications Mike Surridge • Semantic Grid and Pervasive Computing David De Roure IAAI Panel

  48. GGF11 Semantic Grid Workshop • Using the Semantic Grid to Build Bridges between Museums and Indigenous Communities Ronald Schroeter • Collaborative Tools in the Semantic Grid David De Roure • The Integration of Peer-to-peer and the Grid to Support Scientific Collaboration • OWL-Based Resource Discovery for Inter-Cluster Resource Borrowing Hideki YOSHIDA • Semantic Annotation of Computational Components Peter Vanderbilt • Interoperability and Transformability through Semantic Annotation of a Job Description Language Jeffrey Hau • Engineering semantics: Costs and Benefits Simon Cox • Designing Ontologies and Distributed Resource Discovery Services for an Earthquake Simulation Grid Marlon Pierce • Exploring Williams-Beuren Syndrome Using myGrid Carole Goble • Distributed Data Management and Integration Framework: The Mobius Project Shannon Hastings • eBank UK - Linking Research Data, Scholarly Communication and Learning David De Roure • Using the Semantic Grid to Build Bridges between Museums and Indigenous Communities Ronald Schroeter IAAI Panel

  49. E-Science Special Issue • IEEE Intelligent Issue Special Issue on E-Science, Jan-Feb 2004 • De Roure, Gil, Hendler • Challenges: • Realizing the network effect • Moving beyond centralized stores • Automated assembly • Collaboration tools IAAI Panel

  50. Self-Organizing Semantic Grid …Our self-organizing Semantic Grid is now a constantly evolving organism, with ongoing, autonomous processing rather than on-demand processing. This evolving, organic Grid can generate new processes and new knowledge. David De Roure, Trends and Controversies IEEE Intelligent Systems, August 2003 IAAI Panel