Ian Foster Computation Institute Argonne National Lab & University of Chicago Education in the Science 2.0 Era

2 “Web 2.0” l Software as services u Data- & computation-rich network services l Services as platforms u Easy composition of services to create new capabilities (“mashups”)—that themselves may be made accessible as new services l Enabled by massive infrastructure buildout u Google projected to spend $1.5B on computers, networks, and real estate in 2006 u Dozens of others are spending substantially l Paid for by advertising Declan Butler, Nature

3 Science 2.0: E.g., Virtual Observatories Data Archives User Analysis tools Gateway Figure: S. G. Djorgovski Discovery tools

4 Science 2.0 People create services (data or functions) … which I discover and use … & maybe compose to create a new function... and then publish as a new service.  I find “someone else” to host services, so I don’t have to become an expert in operating services & computers!  I hope that this “someone else” can manage security, reliability, scalability, … !! “Service-Oriented Science”, Science, 2005

5 Education and Science 2.0 1) Services as subject u Teach how to discover, apply, build services u Produce a legacy of educational services 2) Services as content u Use services to teach specific content areas u Produce a legacy of educational materials 3) Services as enabler u Outsource the mundane & expensive, so educators can focus on education u Produce a legacy of infrastructure services

6 Services as Subject l Students learn how to discover & invoke services to address specific problems l Then how to build & publish new services l Opportunities for both individual creativity & for intra- and inter-college collaboration

7 Services as Content l Develop educational materials that leverage remote services, e.g.: u Virtual Observatory (astronomy) u caBIG (cancer biology) u Physics (Quarknet, I2U2) u NanoHub (nanotechnology) u TeraGrid “Science Gateways” l Sponsor development of new content services & associated educational materials u Offer to host the resulting services (see next item)

8 Interactive educational projects –Students use real data –Groundbreaking research in classroom –Full lesson plans for teachers SkyServer

9 Cancer Bioinformatics Grid Data uchicago.edu <BPEL Workflow Doc> BPEL Engine Analytic osu.edu Analytic duke.edu <Workflow Results> <Workflow Inputs> link caBiG: BPEL work: Ravi Madduri et al.

10 Earth System Grid l Climate simulation data u Per-collection control u Different user classes u Server-side processing l Implementation (GT) u Portal-based User Registration (PURSE) u PKI, SAML assertions u GridFTP, GRAM, SRM l >2000 users l >100 TB downloaded — DOE OASCR

11 Science Gateways: E.g., Biology Public PUMA Knowledge Base Information about proteins analyzed against ~2 million gene sequences Back Office Analysis on Grid Millions of BLAST, BLOCKS, etc., on OSG and TeraGrid Natalia Maltsev et al.,

12 Services as Enabler l E.g., significant obstacle to teaching parallel computing is a lack of parallel computers!  Create infrastructure that allows remote sites to host “virtual clusters” for many colleges  Any college can teach parallel computing l Similarly for other specialized resources u E.g., database systems, scientific software, network testbeds, … l Needs: u Hosting infrastructure for virtual resources u A library of configured virtual resources

13 Education and Science 2.0 1) Services as subject u Teach how to discover, apply, build services u Produce a legacy of educational services 2) Services as content u Use services to teach specific content areas u Produce a legacy of educational materials 3) Services as enabler u Outsource the mundane & expensive, so educators can focus on education u Produce a legacy of infrastructure services