The Big Questions

Nature of the universe Consciousness

Life & deathFuture of the planet

eSS 2007 Service-Oriented Science: Globus Software in Action 2

How Do We Answer Them?

<0 1700 1950 1990

Empirical

Data

Theory

Simulation

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The Same is True of Smaller Questions

Designing new chemical catalysts

Selling advertising

Creating entertainment

Finding parking

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Information Technology and Science

“Paul Erdös claimed that a mathematician is a machine for turning coffee into theorems. The scientist is arguably a machine for turning data into insight.”

— Service-Oriented Science, I. Foster, Science, 308, p. 814.

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What are the Products of Science? Papers

“We learned this, and here’s how.” Data and Datasets

“We collected this data. Download it, write an analysis program, and see what you can learn from it.”

Web Portals “We constructed this scientific model. Use our data or bring your own, supply

some parameters, and see how it behaves.” Requires manual operation.

Web Services “Here’s our climate model. Integrate it with your models for [ocean

currents/weather/crop forecasts] and see what happens.” “Here’s our indexed data from the latest experiment run. Run your filters

against it and see if you can find anything interesting.” “Here’s our genome analysis engine. Upload your proteins and see what they

will do in a cell.”

Increasing degrees of

collaboration

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Grid:An Enabler of eScience

Must we buy (or travel to) a power source?

Or can we ship power to where we want to work?

Enable on-demand access to, and integration of,diverse resources & services, regardless of location

The dubious electrical power grid analogy

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1st Generation Grids Focus on aggregation of many resources for

massively (data-)parallel applications

EGEE

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Second-Generation Grids

Empower many more users by enabling on-demand access to services

Science gateways (TeraGrid)

Service oriented science

Or, “Science 2.0”

“Service-Oriented Science”, Science, 2005

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“Web 2.0” Software as services

Data- & computation-richnetwork services

Services as platforms Easy composition of services to create new

capabilities (“mashups”)—that themselves may be made accessible as new services

Enabled by massive infrastructure buildout Google projected to spend $1.5B on computers,

networks, and real estate in 2006 Many others are spending substantially

Paid for by advertising

Declan Butler,Nature

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Automating Science

Human access to data is nice Automated access by software tools is

revolutionary “In the time that a human user takes to locate one

useful piece of information within a Web site, a program may access and integrate data from many sources and identify relationships that a human might never discover unaided.” - Foster

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Science 2.0:E.g., Virtual Observatories

Data ArchivesData Archives

User

Analysis toolsAnalysis tools

Gateway

Figure: S. G. Djorgovski

Discovery toolsDiscovery tools

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Service-Oriented Science

People create services (data or functions) …

which I discover (& decide whether to use) …

& compose to create a new function ...

& 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

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Are Scientists Really Developing Web Services?

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Cancer Bioinformatics Grid

Common system architecture (caGrid) provides the service interface “plumbing” and the service hosting capability Web services

Community participants supply useful services Data access, analysis, modeling, filtering,

authoring, etc. https://cabig.nci.nih.gov/

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

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The Introduce Authoring Tool Define service Create skeleton Discover types Add operations Configure security Modify service

Introduce: Hastings, Saltz, et al., Ohio State University

Generates GT4-compatible WebServices

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The Importance of “Hosting”and “Management”

Tell me aboutthis star Tell me about

these 20K stars

Support 1000sof users

E.g., Sloan DigitalSky Survey, ~10 TB;others much bigger

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Skyserver Sessions(Thanks to Alex Szalay)

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Hosting & Management:Application Hosting Services

ResourceProvider

ApplnCode

ApplnCode

Application client

AHS

management Hosting Service

Author ization

ResourceProvider

Provisioning

Persistence

Users

Admins

PDP

Policymanagement

Application deployment

ApplicationPrep Tool(s)

ApplnCode

Applicationproviders

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Who Will Host Your Services?

Your institution (campus resources) (Inter)national systems

TeraGrid, Open Science Grid, UK Nat’l Grid Service, ChinaGrid, NaukaGrid, etc.

Science domain systems caBIG, NEES, Earth System Grid, Orion*,

LEAD, NEON*, LHC Computing Grid, etc. Commercial systems

Amazon, Google, etc.

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Examples ofProduction Scientific Grids

APAC (Australia) China Grid China National Grid DGrid (Germany) EGEE NAREGI (Japan) Open Science Grid Taiwan Grid TeraGrid ThaiGrid UK Nat’l Grid Service

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Application-Infrastructure Gap

Dynamicand/or

DistributedApplications

A

1

B

1

99

Shared Distributed Infrastructure

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Bridging the Application-Resource Gap

IBM

IBM

Uniform interfaces,security mechanisms,Web service transport,

monitoring

Computers StorageSpecialized resource

UserApplication

IBM

IBM

GRAM GridFTPHost EnvUser Svc

DAIS

Database

ToolTool

Workflow

Credent.

Host EnvUser Svc

Registry

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Grid Infrastructure

Distributed management Of physical resources Of software services Of communities and their policies

Unified treatment Build on Web services framework Use WS-RF, WS-Notification (or WS-

Transfer/Man) to represent/access state Common management

abstractions & interfaces