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Gridforum David De Roure Newe Science 20080402


Published on Annual Business Day 2008

Published in: Business, Technology
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Gridforum David De Roure Newe Science 20080402

  1. 1. Eindhoven Edition
  2. 2. <ul><li>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. </li></ul>e-Science is about global collaboration in key areas of science, and the next generation of infrastructure that will enable it.
  3. 3. How do we know when e-Science has succeeded? Not just accelerated but new A. When everyone is using the Grid B. When there are routine scientific advances that would not have happened otherwise
  4. 4. How do we move from heroic scientists doing heroic science with heroic infrastructure to everyday scientists doing science they couldn’t do before? humanists archaeologists geographers musicologists ... researchers! research It’s the democratisation of e-Research 
  5. 5. scientists Digital Libraries Graduate Students Undergraduate Students experimentation Data, Metadata Provenance Workflows Ontologies The social process of science Local Web Repositories Virtual Learning Environment Technical Reports Reprints Peer-Reviewed Journal & Conference Papers Preprints & Metadata Certified Experimental Results & Analyses
  6. 6. <ul><li>Between 19 th October and 23 rd November 2007 I attended six international meetings related to e-Science </li></ul><ul><li>Grid 2007 Scientific and Scholarly Workflows e-Social Science 2007 W3C </li></ul><ul><li>Open Grid Forum Microsoft e-Science </li></ul><ul><li>This is what I found </li></ul>
  7. 7. <ul><li>Not just a specialist few doing heroic science with heroic infrastructure </li></ul><ul><li>Chemists are blogging the lab </li></ul><ul><li>Everyone is mashing up </li></ul><ul><li>Everday hardware – multicore machines and mobile devices </li></ul>Everyday researchers doing everyday research 1
  8. 8. <ul><li>Data is large, rich, complex and real-time </li></ul><ul><li>There is new value in data, through new digital artefacts and through metadata e.g. context, provenance, workflows </li></ul><ul><li>This isn’t “anti-computation” –design interaction around data </li></ul>A data-centric perspective, like researchers 2
  9. 9. <ul><li>The social process of science revisited in the digital age </li></ul><ul><li>Collaborative tools – blogs and Wikis </li></ul><ul><li>e-Science now focuses on publishing as well as consuming </li></ul><ul><li>Scholarly lifecycle perspective </li></ul>Collaborative and participatory 3
  10. 10. <ul><li>This is new and powerful! </li></ul><ul><li>Community intelligence </li></ul><ul><li>Review </li></ul><ul><li>Usage informing recommendation </li></ul><ul><li>e.g. OpenWetWare </li></ul><ul><li>e.g. myExperiment </li></ul>Benefitting from the scale of digital science activity to support science 4
  11. 11. <ul><li>Preprints servers and institutional repositories </li></ul><ul><li>Open journals </li></ul><ul><li>Open access to data </li></ul><ul><li>Science Commons </li></ul><ul><li>Object Reuse & Exchange </li></ul>Increasingly open 5
  12. 12. <ul><li>The technologies people are using are not perfect </li></ul><ul><li>They are better </li></ul><ul><li>They are easy to use </li></ul><ul><li>They are chosen by scientists </li></ul>Better not Perfect 6
  13. 13. <ul><li>The success stories come from the researchers who have learned to use ICT </li></ul><ul><li>Domain ICT experts are delivering the solutions </li></ul><ul><li>Anything that takes away autonomy will be resisted </li></ul>Empowering researchers 7
  14. 14. <ul><li>e-Science is about the intersection of the digital and physical worlds </li></ul><ul><li>Sensor networks </li></ul><ul><li>Mobile handheld devices </li></ul>About pervasive computing 8
  15. 15. <ul><li>Everyday researchers doing everyday research </li></ul><ul><li>A data-centric perspective, like researchers </li></ul><ul><li>Collaborative and participatory </li></ul><ul><li>Benefitting from the scale of digital science activity to support science </li></ul><ul><li>Increasingly open </li></ul><ul><li>Better not Perfect </li></ul><ul><li>Empowering researchers </li></ul><ul><li>About pervasive computing </li></ul>Signs of the Times
  16. 16. <ul><li>e-Science is now enabling researchers to do some completely new stuff! </li></ul><ul><li>As the individual pieces become easy to use, researchers can bring them together in new ways and ask new questions </li></ul><ul><li>“ The next level” </li></ul>Onward and Upward “ Standing on the shoulders of giants” (Everyday researchers are giants too)
  17. 17. Note to Reader. The next slides are not intended to be anti-grid. Everyone working on Grid is doing great work.
  18. 18. <ul><li>Everyday researchers doing everyday research </li></ul><ul><ul><li>BUT heroic Grid infrastructure not being adopted </li></ul></ul><ul><li>A data-centric perspective, like researchers </li></ul><ul><ul><li>BUT Grid gives APIs to computation not data </li></ul></ul><ul><li>Collaborative and participatory </li></ul><ul><ul><li>BUT Grid has deeply rooted service provider mindset </li></ul></ul><ul><li>Better not Perfect </li></ul><ul><ul><li>BUT Grid aims to provide well-engineered perfect solution </li></ul></ul><ul><li>Giving autonomy to researchers </li></ul><ul><ul><li>BUT Grid has feel of institutional control (at this time) </li></ul></ul><ul><li>About pervasive computing </li></ul><ul><ul><li>BUT Grid is about portals, not the next generation of users </li></ul></ul>The Grid Problem
  19. 19. e-Science Pipeline e-Science Technology Creators & Integrators Applications Research EE Research Socio-economic & Commercial Innovation e-Science bespoke tailoring Mass Use by Researchers 5 years 5 years 5 years CS Research e-Science 10s of integrators 100s of embedded consultants 1000s of research users The Arrow Problem Malcolm Atkinson NB This isn’t wrong!
  20. 20. <ul><li>Don’t think rollout of technologies... </li></ul>Think roll-in of researchers... Mass Use by Researchers Knowledge co-production vs Service Delivery! Mass Use by Researchers
  21. 21. Web Services RESTful APIs cmd lines ssh http Web Browser Mobile phone iPod Car Equipment PDA P2P OeRC mashups workflows services applications Subject ICT experts Computer Scientists Software Companies Workflow tools Ruby on Rails ecosystem Scientists open source Software Engineers nesc
  22. 22. <ul><li>It’s about empowerment as well as provision </li></ul><ul><li>People power – the new instrument of scale! </li></ul><ul><li>Hence usability: </li></ul><ul><ul><li>Simple/familiar interfaces for users </li></ul></ul><ul><ul><li>Simple/familiar interfaces for developers </li></ul></ul><ul><ul><li>No need for a summer school! </li></ul></ul><ul><li>Step into user space and look back </li></ul><ul><li>Computer Scientists as facilitators and problem solvers(?) </li></ul>For a flourishing ecosystem...
  23. 23. <ul><li>Wikis </li></ul><ul><li>Mashups </li></ul><ul><li>REST APIs </li></ul><ul><li>Google Maps </li></ul><ul><li>Technologies: </li></ul><ul><ul><li>AJAX, JSON, Ruby on Rails, ... </li></ul></ul><ul><li>Social networking </li></ul><ul><li>Web as a distributed application platform </li></ul><ul><ul><li>Amazon S3 and EC2 </li></ul></ul>But what about Web 2.0?!
  24. 24. <ul><li>Everyday researchers doing everyday research </li></ul><ul><li>A data-centric perspective, like researchers </li></ul><ul><li>Collaborative and participatory </li></ul><ul><li>Benefitting from the scale of digital science activity </li></ul><ul><li>Increasingly open </li></ul><ul><li>Better not Perfect </li></ul><ul><li>Empowering researchers </li></ul><ul><li>About pervasive computing </li></ul>Signs of the Times 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 the single device Web 2.0 patterns
  25. 26. use Web 2.0 here? Grid
  26. 27. use Web 2.0 here? Grid
  27. 28. use Web 2.0 here Grid Grid cloud HPC
  28. 29. 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 The architecture comprises services which may be instantiated and assembled dynamically, hence the structure, behaviour and location of software is changing at run-time Service-Oriented Knowledge Utility
  29. 30. 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. 31. 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. 32. <ul><li>Web 2.0 is not high performance </li></ul><ul><ul><li>It improves the performance of science and people! </li></ul></ul><ul><li>Web 2.0 is not a properly engineered solution </li></ul><ul><ul><li>Scientists want better, not perfect. And agility. </li></ul></ul><ul><li>Web 2.0 is not secure </li></ul><ul><ul><li>People do lots of “secure” things on the Web </li></ul></ul><ul><li>Web 2.0 is a fad that will pass </li></ul><ul><ul><li>It’s inevitable and it’s already happened! </li></ul></ul><ul><li>Web 2.0 works for teenagers but it won’t for scientists </li></ul><ul><ul><li>See OpenWetWare </li></ul></ul><ul><li>Web 2.0 lets the oiks in and this is a bad thing </li></ul><ul><ul><li>Now we can do peer review even better! </li></ul></ul>Myths
  32. 33. N 2 N N
  33. 34. One Middleware 2N N N
  34. 35. Middleware ? N N Middleware Middleware Middleware Middleware Middleware Polynomial involving N1, N2 and M
  35. 36.
  36. 37. <ul><li>Workflows are the new rock and roll </li></ul><ul><li>Machinery for coordinating the execution of (scientific) services and linking together (scientific) resources </li></ul><ul><li>The era of Service Oriented Applications </li></ul><ul><li>Repetitive and mundane boring stuff made easier </li></ul>E. Science laboris Carole Goble
  37. 38. <ul><li>Paul writes workflows for identifying biological pathways implicated in resistance to Trypanosomiasis in cattle </li></ul><ul><li>Paul meets Jo. Jo is investigating Whipworm in mouse. </li></ul><ul><li>Jo reuses one of Paul’s workflow without change . </li></ul><ul><li>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. </li></ul><ul><li>Previously a manual two year study by Jo had failed to do this. </li></ul>Recycling, Reuse, Repurposing
  38. 39. 40 Taverna downloads per day 2007 2006 2005 2004 2003
  39. 40. <ul><li>Run on your laptop – no sysadmin required </li></ul><ul><li>Access independent third party world-wide service providers of applications, tools and datasets </li></ul><ul><ul><li>850 databases, 166 web servers Nucleic Acids Research Jan 2006 </li></ul></ul><ul><li>My local applications, tools and datasets. In the Enterprise. In the laboratory. </li></ul><ul><li>Easily incorporate new services without coding </li></ul>The Superclient
  40. 41. Kepler Triana BPEL Ptolemy II
  41. 42. is… <ul><li>“ Facebook for Scientists”...but different to Facebook! </li></ul><ul><li>A community social network. </li></ul><ul><li>A gateway to other publishing environments </li></ul><ul><li>A federated repository </li></ul><ul><li>A platform for launching workflows </li></ul><ul><li>Publishing self-describing Encapsulated myExperiment Objects </li></ul><ul><li>Mindful publication </li></ul><ul><li>Started March 2007 </li></ul><ul><li>Closed beta since July 2007 </li></ul><ul><li>Open beta November 2007 </li></ul> is...
  42. 44. Google Gadget
  43. 45. Ownership and Attribution
  44. 46. 24/5/2007 | myExperiment | Slide
  45. 47. ` Enactor HTML XML Snapshot map of resources with their relationships and versions users descriptions groups friendships tags blobs workflows
  46. 48. scientists Graduate Students Undergraduate Students experimentation Data, Metadata Provenance Workflows Ontologies Digital Libraries The social process of science 2.0 Local Web Repositories Virtual Learning Environment Technical Reports Reprints Peer-Reviewed Journal & Conference Papers Preprints & Metadata Certified Experimental Results & Analyses
  47. 49. <ul><li>e-Research is about doing new research </li></ul><ul><li>Grid is just one part of the solution </li></ul><ul><li>Users are not just consumers of infrastructure. Empower them. </li></ul><ul><li>Web 2.0 is a set of design patterns </li></ul><ul><li>Think Web 2.0 coupling Grid and other services </li></ul><ul><li>Workflows make e-Science easier, and Web 2 makes workflows easier  </li></ul>Take Homes 2.0
  48. 50. <ul><li>Contact </li></ul><ul><li>David De Roure </li></ul><ul><li> </li></ul><ul><li>Carole Goble </li></ul><ul><li>[email_address] </li></ul><ul><li>Thanks </li></ul><ul><li>Malcolm Atkinson, Geoffrey Fox, Jeremy Frey, Savas Parastatides, The myGrid Family </li></ul>
  49. 51. Provenance Harvesting myExperiment metadata bus ORE Encapsulated myExperiment Object (EMO) Metadata RDF Store
  50. 52. <ul><li>ReM=Resource Map, A=aggregation, AR=Aggregated Resource </li></ul>OAI-ORE Object Exchange and Reuse
  51. 53. Anatomy of an EMO EMO Metadata creator, modified, rights URIs into myExperiment(s) with types and comments workflow, data, description URIs to external resources, with alternates, types, comments, versions Optional annotations of URIs and their relationships
  52. 54. Linked Data
  53. 55. <ul><li>TAVERNA FUNCTIONAL LANGUAGE SHOCK! </li></ul>RESEARCH DAILY British Scientists revealed today that Taverna is in fact a functional language. In a police statement, Taverna creator Tom Oinn said “it’s a fair cop guv”... Advertisement New Improved Closurize and Concentrate TM Add Lambda Calculus to your Lambda Network! Satisfaction guaranteed in several different colours
  54. 56. Original workflow High-level design of quality filter Compilation to quality workflow Integration New quality filter Quality-aware workflow Declarative specification <ul><li>Declarative spec is formal (XML) </li></ul><ul><li>Compilation is automated </li></ul><ul><li>QW follows predictable pattern </li></ul><ul><ul><li> integration also automated </li></ul></ul>Quality Workflows Paolo Missier
  55. 57. Malcolm Atkinson