The New e-Science (Bangalore Edition)

Slide 1: Bangalore Edition

Slide 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.

Slide 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

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

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

Slide 6: Between 19th October and 23rd November 2007 I attended six international meetings related to e-Science Grid 2007 Scientific and Scholarly Workflows e-Social Science 2007 W3C Open Grid Forum Microsoft e-Science This is what I found

Slide 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

Slide 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

Slide 9: 3 Collaborative and participatory • The social process of science revisited in the digital age • Collaborative tools – blogs and Wikis • e-Science now focuses on publishing as well as consuming • Scholarly lifecycle perspective

Slide 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

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

Slide 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

Slide 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

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

Slide 15: Signs of the Times 1. Everyday researchers doing everyday research 2. A data-centric perspective, like researchers 3. Collaborative and participatory 4. Benefitting from the scale of digital science activity to support science 5. Increasingly open 6. Better not Perfect 7. Empowering researchers 8. About pervasive computing

Slide 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 “Standing on the questions shoulders of giants” • “The next level”

Slide 18: The Grid Problem 1. Everyday researchers doing everyday research BUT heroic Grid infrastructure not being adopted 2. A data-centric perspective, like researchers BUT Grid gives APIs to computation not data 3. Collaborative and participatory BUT Grid has deeply rooted service provider mindset 4. Better not Perfect BUT Grid aims to provide well-engineered perfect solution 5. Giving autonomy to researchers BUT Grid imposes institutional control (at this time) 6. About pervasive computing BUT Grid is about portals,not the next generation of users

Slide 19: Malcolm Atkinson The Arrow Problem e-Science Applications Pipeline Research CS Research EE Mass e-Science e-Science Research Use by Technology bespoke Researchers Creators tailoring & Integrators Socio-economic & e-Science Commercial 100s of 1000s of 10s of Innovation embedded research integrators consultants users 5 years 5 years 5 years

Slide 20: Web Browser Mobile phone iPod Car Equipment PDA Scientists Software Companies Subject applications workflows Workflow ICT experts Computer ecosystem nesc tools Scientists mashups Software open source services Engineers Ruby on Rails Web Services RESTful APIs cmd lines ssh http P2P

Slide 21: For a flourishing ecosystem... • It’s about empowerment as well as provision • People power • 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(?)

Slide 22: 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

Slide 23: Signs 2.0the Times Web of patterns 1. Everyday researchers doing everyday research The Long Tail 2. Data is the Next “Intel Inside” researchers A data-centric perspective, like 3. Users add value participatory Collaborative and Network effects by defaultof digital science 4. Benefitting from the scale activity to support science 5. Some Rights open Increasingly Reserved The Perpetual Beta 6. Better not Perfect Cooperate, don’t Contol 7. Empowering researchers Software above the level of the single device 8. About pervasive computing

Slide 24: use Web 2.0 here? Grid

Slide 25: use Grid Web 2.0 here?

Slide 26: use Web 2.0 here Grid

Slide 27: Service-Oriented Knowledge Utility The architecture comprises services 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 Services are knowledge- immediately useable assisted (‘semantic’) to service with established facilitate automation and functionality, advanced functionality, performance and the knowledge aspect dependability, illustrating reinforced by the the emphasis on user emphasis on delivering needs and issues such high level services to the as trust user

Slide 28: 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 – Let’s find out...!

Slide 29: myexperiment.org

Slide 30: E. Science laboris  Workflows are the new rock and roll  Machinery for coordinating the execution of (scientific) services and linking together (scientific) resources  The era of Service Oriented Applications  Repetitive and mundane boring stuff made easier

Slide 31: 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.

Slide 32: Taverna downloads per day 40 2003 2004 2005 2006 2007

Slide 33: e-Services in the Cloud • Independent third party world- wide service providers of applications, tools and data sets. In the Cloud. – 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 service without coding. So even more services from the cloud and enterprise.

Slide 34: Triana Kepler Ptolemy II BPEL

Slide 35: myExperiment.org is… is... myExperiment.org  “Facebook for Scientists”  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

Slide 38: Google Gadget

Slide 39: Ownership and Attribution Challenge: Policy and Permissions without Tears

Slide 40: 24/5/2007 | myExperiment | Slide 40

Slide 41: Snapshot map of resources with their relationships and versions HTML XML users tags blobs groups workflows friendships descriptions ` Enactor

Slide 42: Virtual Learning The social process Environment of science 2.0 Undergraduate Students Digital scientists Libraries Graduate Students Reprints Peer- experimentation Reviewed Technical Journal & Preprints Reports Conference & Metadata Papers Local Web Data, Metadata Repositories Certified Provenance Experimental Workflows Results & Analyses Ontologies

Slide 43: Take Homes 2.0 • e-Science is about doing new science • 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 on top of Grid and other services • Workflows make e-Science easier, and Web 2 makes workflows easier 

Slide 44: Contact David De Roure dder@ecs.soton.ac.uk Carole Goble carole.goble@manchester.ac.uk Thanks Geoffrey Fox, Savas Parastatides, myExperiment team & myGrid team