5. 6/6/2007| | Slide 3 The Semantic Grid Report 2001 e-Science is about global collaboration in key areas of science and the next generation of infrastructure that will enable it John Taylor 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. Us
6. Missing Link Grid Infrastructure 6/6/2007| | Slide 4 Scientists Need something here
7. Why Semantic Web? 6/6/2007| | Slide 5 Grid Computing The Semantic Web The Semantic Grid Web Services Huge potential for Science making data reusable, interlinked making connections between decoupled content generating new intelligence Automation requires machine-processable descriptions Grid community talking about metadata and knowledge
10. 6/6/2007| | Slide 8 Semantic Grid = Grid + Semantic Web for e-Science SemanticWeb SemanticGrid Scale of Interoperability ClassicalWeb ClassicalGrid Scale of data and computation Based on an idea by Norman Paton
11. 6/6/2007| | Slide 9 Free the data! Free the services! Semantic Grid Grid The Semantic Web is an extension of the current Web in which information and services are given well-defined meaning, better enabling computers and people to work in cooperation Grid www.semanticgrid.org
15. 6/6/2007| | Slide 13 The key observation! “Publication at Source” describes the need to capture data and its context from the outset and maintain a complete end-to-end connection between the laboratory bench and the intellectual chemical knowledge that is published as a result of the investigation e-Science = Record and Reuse. Reuse needs provenance The details of the origins of data are just as important to understanding as their actual values
19. CombeChem Principles It’s a Semantic DataGrid Think Holistic – we’re working in the context of the Scholarly Knowledge Cycle In the Wild – Integrating 3rd party data sources Power of Provenance Publish don’t warehouse Users add value A little Semantics goes a long way 6/6/2007| | Slide 17
38. Servicesbindingaware and capable of processingOptimization Security Data Execution Management Semantic Services Resource management Information Management Infrastructure Services 23
39. Service-Oriented Knowledge Utility NGG3 The architecture comprisesservices which may be instantiated and assembled dynamically, hence the structure, behaviour and location of software is changing at run-time A utility is a directly and immediately useable service with established functionality, performance and dependability, illustrating the emphasis on user needs and issues such as trust Services are knowledge-assisted (‘semantic’) to facilitate automation and advanced functionality, the knowledge aspect reinforced by the emphasis on delivering high level services to the user
40. 25 NGG3 Next Generation Grids Report 2005 Future for European Grids: GRIDs and Service Oriented Knowledge Utilities – Vision and Research Directions 2010 and Beyond, December 2006 End-User – Business/Enterprise –Manufacturing/Industrial Driving Scenarios Service-Oriented Knowledge Utility Human Factors and Societal Issues Pervasiveness Context Awareness Research Topics Adaptability Scalability Dependability Semantic Technologies Trust and Security in VOs Lifecycle Management Raising the Level of Abstraction NGG1&NGG2 vision and research challenges
41. 6/6/2007| | Slide 26 Transformative Application - to enhance discovery & learning Provisioning -Creation, deploymentand operation of advanced CI R&D to enhance technical and social dimensions of future CI systems Dan Atkins
43. 26/2/2007 | myExperiment | Slide 28 Bioinformatics is not Chemistry There are many pieces, from many boxes, but no box, and no lid with a complete picture of what the puzzle is supposed to be. Planning? No. Metadata an afterthought Carole Goble
44. Key collective activities in e-science informal and formalcommunication meetings interpretation of data/events archiving/recovering information following through decisions/coordinating activities producing documents& other artifacts http://www.aktors.org/coakting/ 6/6/2007| | Slide 29
45. 6/6/2007| | Slide 30 Add notational and hypermedia structure to discussions & documents Make meetings persistent and replayable Add indices to events in meetings so the meetings themselves become indexed documents How can we weave together distributed discourse and documents? Mike Daw
52. Collaboration Principles e-Science as sense-making Supporting formal and informal scientific process Collaboration over artefacts Scaling up from project to community 6/6/2007| | Slide 37
57. Web 2.0 Design Patterns The Long Tail Data is the Next Intel Inside Users Add Value Network Effects by Default Some Rights Reserved The Perpetual Beta Cooperate, Don't Control Software Above the Level of a Single Device http://www.oreillynet.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web-20.html 26/2/2007 | myExperiment | Slide 42
60. 6/6/2007| | Slide 45 Overengineering of standards Assumption that users will come Divorces computation from content provision Service provider mentality users seen as consumers not producers So it’s a long haul When Grids go bad
61. 6/6/2007| | Slide 46 The Grid Problem The Web 2.0 community decided Web Services are too complicated so they use HTTP instead. The Grid community decided Web Services aren’t complicated enough so they invented OGSA.
62. You are a member of the S M NTIC W B CLUB
63. 6/6/2007| | Slide 48 Entry cost high Value over XML not apparent in the small Value over relational databases not apparent Learning curve for concepts and tools Need to bootstrap to get value No immediate ROI So it’s a long haul When Web goes bad
64. Missing Link Grid Infrastructure 6/6/2007| | Slide 49 Scientists Really simple interfaces to computation, storage, content and annotation
68. 6/6/2007| | Slide 51 VRE2 Approach users User Needs Analysis Community Engagement Contextual Analysis Change analysis Programme Evaluation Pilots Other Programmes & Initiatives System analysis Testing e-Research Interoperability Integration Design Building developers
69.
70. 6/6/2007| | Slide 53 Semantic Grid – metadata management and automation through annotation The Grid community can learn from Web 2.0 in terms of how developers and users engage with the new capabilities simplicity of interface for developers bring new functionality to the users rather than expecting them to come to it Web 2.0 is compatible with Grid in that it requires robust services underlying it If we were writing the report now...Semantic Grid 2.0 ?! Messages
71. 6/6/2007| | Slide 54 semanticgrid.org David De Roure dder@ecs.soton.ac.uk Carole Goble Geoffrey Fox Marlon Pierce Semantic Grid Research Group See the Call for Participation for the OGF21 Grid and Web 2.0 Workshop OGF21 Seattle, October 15-19, 2007
72. 6/6/2007| | Slide 55 Credits, Links and Contacts Slides Stephen Downie Liz Lyon Geoffrey Fox Jeremy Frey Carole Goble Angela Piccini David De Roure dder@ecs.soton.ac.uk Carole Goble carole.goble@manchester.ac.uk
![6/6/2007| | Slide 2 Overview The search for the missing link ,[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)