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D avid De Roure

The New e-Science. D avid De Roure. Eindhoven Edition. e-Science is about global collaboration in key areas of science, and the next generation of infrastructure that will enable it.

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D avid De Roure

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  1. The Newe-Science David De Roure Eindhoven Edition

  2. e-Science is about global collaboration in key areas of science, and the next generation of infrastructure that will enable it. Due to the complexity of the software and the backend infrastructural requirements, e-Science projects usually involve large teams managed and developed by research laboratories, large universities or governments.

  3. How do we know when e-Science has succeeded? A. When everyone is using the Grid B. When there are routine scientific advances that would not have happened otherwise Not just accelerated but new

  4. How do we move from heroic scientists doing heroic science with heroic infrastructure to everyday scientists doing science they couldn’t do before? research humanists archaeologists geographers musicologists ... researchers! It’s the democratisation of e-Research 

  5. Virtual Learning Environment Reprints Peer-Reviewed Journal & Conference Papers Technical Reports LocalWeb Preprints & Metadata Repositories Certified Experimental Results & Analyses The social process of science Undergraduate Students Digital Libraries scientists Graduate Students experimentation Data, Metadata Provenance WorkflowsOntologies

  6. Between 19th October and23rd November 2007 I attended sixinternational meetings related to e-Science Grid 2007Scientific and Scholarly Workflowse-Social Science 2007W3C Open Grid ForumMicrosoft e-Science This is what I found

  7. 1 Everyday researchers doing everyday research • Not just a specialist few doing heroic science with heroic infrastructure • Chemists are blogging the lab • Everyone is mashing up • Everday hardware – multicore machines and mobile devices

  8. 2 A data-centric perspective, like researchers • Data is large, rich, complex and real-time • There is new value in data, through new digital artefacts and through metadata e.g. context, provenance, workflows • This isn’t “anti-computation” –design interaction around data

  9. 3 Collaborative and participatory • The social process of science revisited in the digital age • Collaborative tools – blogsand Wikis • e-Science now focuseson publishing as well as consuming • Scholarly lifecycle perspective

  10. 4 Benefitting from the scale of digital science activity to support science • This is new and powerful! • Community intelligence • Review • Usage informing recommendation • e.g. OpenWetWare • e.g. myExperiment

  11. 5 Increasingly open • Preprints servers and institutional repositories • Open journals • Open access to data • Science Commons • Object Reuse & Exchange

  12. 6 Better not Perfect • The technologies people are using are not perfect • They are better • They are easy to use • They are chosen by scientists

  13. 7 Empowering researchers • The success stories come from the researchers who have learned to use ICT • Domain ICT experts are delivering the solutions • Anything that takes away autonomy will be resisted

  14. 8 About pervasive computing • e-Science is about the intersection of the digital and physical worlds • Sensor networks • Mobile handheld devices

  15. Signs of the Times • Everyday researchers doing everyday research • A data-centric perspective, like researchers • Collaborative and participatory • Benefitting from the scale of digital science activity to support science • Increasingly open • Better not Perfect • Empowering researchers • About pervasive computing

  16. Onward and Upward • e-Science is now enabling researchers to do some completely new stuff! • As the individual pieces become easy to use, researchers can bring them together in new ways and ask new questions • “The next level” “Standing on theshoulders of giants” (Everyday researchers are giants too) www.w3.org/2007/Talks/www2007-AnsweringScientificQuestions-Ruttenberg.pdf

  17. Note to Reader. The next slides are not intended to be anti-grid. Everyone working on Grid is doing great work.

  18. The Grid Problem • Everyday researchers doing everyday research BUT heroic Grid infrastructure not being adopted • A data-centric perspective, like researchers BUT Grid gives APIs to computation not data • Collaborative and participatory BUT Grid has deeply rooted service provider mindset • Better not Perfect BUT Grid aims to provide well-engineered perfect solution • Giving autonomy to researchers BUT Grid has feel of institutional control (at this time) • About pervasive computing BUT Grid is about portals, not the next generation of users

  19. Malcolm Atkinson e-Science Pipeline The Arrow Problem Applications Research NB This isn’t wrong! CS Research EE Research Mass Use by Researchers e-Science Technology Creators & Integrators e-Science bespoketailoring Socio-economic& CommercialInnovation e-Science 100s ofembeddedconsultants 1000s ofresearchusers 10s ofintegrators 5 years 5 years 5 years

  20. Mass Use by Researchers Don’t think rollout of technologies... Think roll-in of researchers... Mass Use by Researchers Knowledge co-production vs Service Delivery!

  21. Web Browser Mobile phone iPod Car Equipment PDA Scientists Software Companies applications SubjectICT experts OeRC workflows Workflowtools nesc ecosystem Computer Scientists mashups SoftwareEngineers open source services Ruby on Rails Web Services RESTful APIs cmd lines ssh http P2P

  22. For a flourishing ecosystem... • It’s about empowerment as well as provision • People power – the new instrument of scale! • Hence usability: • Simple/familiar interfaces for users • Simple/familiar interfaces for developers • No need for a summer school! • Step into user space and look back • Computer Scientists as facilitators and problem solvers(?)

  23. But what about Web 2.0?! • Wikis • Mashups • REST APIs • Google Maps • Technologies: • AJAX, JSON, Ruby on Rails, ... • Social networking • Web as a distributed application platform • Amazon S3 and EC2

  24. www.oreilly.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web-20.htmlwww.oreilly.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web-20.html Signs of the Times Web 2.0 patterns The Long Tail Data is the Next Intel Inside • Everyday researchers doing everyday research • A data-centric perspective, like researchers • Collaborative and participatory • Benefitting from the scale of digital science activity • Increasingly open • Better not Perfect • Empowering researchers • About pervasive computing Users add value Network effects by default Some Rights Reserved The Perpetual Beta Cooperate, don’t Control Software above the level of the single device

  25. use Web 2.0 here? Grid

  26. use Web 2.0 here? Grid

  27. use Web 2.0 here HPC Grid Grid cloud

  28. Service-Oriented Knowledge Utility 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 semanticgrid.org/NGG3

  29. If you peel back the label and its says “Grid” or “OGSA” underneath… its not a cloud. If you need to send a 40 page requirements document to the vendor then… it is not cloud. If you can’t buy it on your personal credit card… it is not a cloud If they are trying to sell you hardware… its not a cloud. If there is no API… its not a cloud. If you need to rearchitect your systems for it… Its not a cloud. If it takes more than ten minutes to provision… its not a cloud. If you can’t deprovision in less than ten minutes… its not a cloud. If you know where the machines are… its not a cloud. If there is a consultant in the room… its not a cloud. If you need to specify the number of machines you want upfront… its not a cloud. If it only runs one operating system… its not a cloud. If you can’t connect to it from your own machine… its not a cloud. If you need to install software to use it… its not a cloud. If you own all the hardware… its not a cloud. James Governor

  30. Multicore chips will offer so much performance that we need not cobble together heterogeneous resources but rather can deploy simple powerful systems Geoffrey Fox

  31. Myths • Web 2.0 is not high performance • It improves the performance of science and people! • Web 2.0 is not a properly engineered solution • Scientists want better, not perfect. And agility. • Web 2.0 is not secure • People do lots of “secure” things on the Web • Web 2.0 is a fad that will pass • It’s inevitable and it’s already happened! • Web 2.0 works for teenagers but it won’t for scientists • See OpenWetWare • Web 2.0 lets the oiks in and this is a bad thing • Now we can do peer review even better!

  32. N N2 N

  33. N 2N One Middleware N

  34. N Middleware Middleware ? Middleware Middleware Polynomial involving N1,N2 and M Middleware Middleware N

  35. www.myexperiment.org

  36. E. Science laboris • Workflows are the new rock and roll • Machinery for coordinatingthe execution of (scientific) services and linking together (scientific) resources • The era of Service Oriented Applications • Repetitive and mundane boring stuff made easier Carole Goble

  37. Recycling, Reuse, Repurposing • Paul writes workflows for identifying biological pathways implicated in resistance to Trypanosomiasis in cattle • Paul meets Jo. Jo is investigating Whipworm in mouse. • Jo reuses one of Paul’s workflow without change. • Jo identifies the biological pathways involved in sex dependence in the mouse model, believed to be involved in the ability of mice to expel the parasite. • Previously a manual two year study by Jo had failed to do this.

  38. Taverna downloads per day 40 2003 2004 2005 2006 2007 taverna.sourceforge.net

  39. Run on your laptop – no sysadmin required Access independent third party world-wide service providers of applications, tools and datasets 850 databases, 166 web servers Nucleic Acids Research Jan 2006 My local applications, tools and datasets. In the Enterprise. In the laboratory. Easily incorporate new services without coding The Superclient

  40. Kepler Ptolemy II Triana BPEL

  41. myExperiment.org is… myExperiment.org is... • “Facebook for Scientists”...but different to Facebook! • A community social network. • A gateway to other publishing environments • A federated repository • A platform for launching workflows • Publishing self-describing Encapsulated myExperiment Objects • Mindful publication • Started March 2007 • Closed beta since July 2007 • Open beta November 2007

  42. Google Gadget

  43. Ownership and Attribution

  44. Snapshot map of resources with their relationships and versions EMO manifest EMOAPI HTML XML Social NetAPI Ownership Sharing API Workflow API SearchAPI TAG API users tags blobs groups workflows EPrints DSpace Fedora S3 SRB friendships descriptions ` Enactor API Enactor

  45. Virtual Learning Environment Reprints Peer-Reviewed Journal & Conference Papers Technical Reports LocalWeb Preprints & Metadata Repositories Certified Experimental Results & Analyses The social process of science 2.0 Undergraduate Students Digital Libraries scientists Graduate Students experimentation Data, Metadata Provenance WorkflowsOntologies

  46. Take Homes 2.0 • e-Research is about doing new research • Grid is just one part of the solution • Users are not just consumers of infrastructure. Empower them. • Web 2.0 is a set of design patterns • Think Web 2.0 coupling Grid and other services • Workflows make e-Science easier, and Web 2 makes workflows easier 

  47. Contact David De Roure dder@ecs.soton.ac.uk Carole Goble carole.goble@manchester.ac.uk Thanks Malcolm Atkinson, Geoffrey Fox,Jeremy Frey, Savas Parastatides, The myGrid Family

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