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Ian Foster
Computation Institute
Argonne National Lab & University of Chicago
Services for Science
2
Thanks!
DOE Office of Science
NSF Office of Cyberinfrastructure
National Institutes of Health
Colleagues at Argonne, U.C...
3
Scientific
Communication, ~1600
Brahe Kepler
4
1980
5
Scientific Communication, ~2000
Data ArchivesData Archives
User
Analysis toolsAnalysis tools
Gateway
Figure: S. G. Djorg...
6
Application Scenario
Location A
Microarray, Protein,
Image data
Location B
Microarray, Protein,
Image data
Location C
Mi...
7
caBIG: sharing of infrastructure, applications, and
data.
Data
Integration!
Services
& Cancer Biology
Globus
8
Service-Oriented Science
People create services (data, code, instr.) …
which I discover (& decide whether to use) …
& co...
9
Creating Services
People create services (data, code, instr.) …
which I discover (& decide whether to use) …
& compose t...
10
Anatomy of a Service
op1 opN (meta)data
Implementation(s)
Clients
Registry
Management
Clients
…
Service
Service
Attribu...
11
Creating Services (~2005)
“This full-day tutorial provides an
introduction to programming Java
services with the latest...
12
Appln
Service
Create
Index
service
Store
Repository
Service
Advertize
Discover
Invoke;
get results
Introduce
Container
...
Demonstration:
Creating Services
Introduce + gRAVI
Shannon Hastings
Scott Oster
David Ervin
Stephen Langella
Kyle Chard
Ra...
14Center for Enabling Distributed Petascale Science
Workflow Automation at DOE Facilities
Automation
Reproducibility
Secur...
15
Discovering Services
People create services (data or functions) …
which I discover (& decide whether to use) …
& compos...
16
 The ultimate arbiter?
 Types, ontologies
 Can I use it?
 Billions of services
Discovering Services
Assume success
...
17
Discovery (1):
Registries
Globus
18
Discovery (2):
Standardized Vocabularies
Core Services
Grid
Service
Uses Terminology
Described In
Cancer Data
Standards...
19
20
Discovery (3): Tagging
& Social Networking
GLOSS:
Generalized
Labels Over Scientific
data Sources
(Foster, Nestorov)
21
Discovery (3): Tagging
& Social Networking
David de Roure,
Carole Goble,
et al.
22
Composing Services
People create services (data or functions) …
which I discover (& decide whether to use) …
& compose ...
23
Composing Services:
E.g., BPEL Workflow System
Data Service
@ uchicago.edu
Analytic service
@ osu.edu
Analytic service
...
24
Composing Services:
Taverna
caGrid Scavenger with
semantic/metadata-
based caGrid service query
A sample
caGrid
workflo...
25
Composing
Services
Globus
Demonstration:
Composing Services
Taverna + GT4
Taverna team
Wei Tan
Ravi Madduri
27
Publishing Services
People create services (data or functions) …
which I discover (& decide whether to use) …
& compose...
28
Publishing Services
Description  Syntax, semantics
State  Availability, load, …
Policies  Who, what, when, …
Hosting...
29
Authorization: SAML & XACML
VOMS Shibboleth LDAP PERMIS…
GT4 Client
GT4 Server
PDP
Attributes
Authorization
Decision
PI...
30
Hosting Services
People create services (data or functions) …
which I discover (& decide whether to use) …
& compose to...
31
The Two Dimensions
of Service-Oriented Science
Decompose across network
Clients integrate dynamically
Select & compose ...
32
The geWorkbench/caGrid/TeraGrid
Interface
33
Putting It Together for the Example Scenario
Location A
Microarray, Protein,
Image data
Location B
Microarray, Protein,...
34
Lessons Learned
A convenient higher-level abstraction
Suitable for a subset of scientific use cases
Infrastructure need...
35
Services for Science
A new approach to communicating
A (not-so new) approach to structuring systems
They’re real
Excell...
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Services for Science v2 (APAN26)

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Talk given at APAN26 in beautiful Queenstown, New Zealand. Updates my INGRID talk with new material on caBIG--including some nice slides provided by Ravi Madduri.

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Services for Science v2 (APAN26)

  1. 1. Ian Foster Computation Institute Argonne National Lab & University of Chicago Services for Science
  2. 2. 2 Thanks! DOE Office of Science NSF Office of Cyberinfrastructure National Institutes of Health Colleagues at Argonne, U.Chicago, USC/ISI, OSU, Manchester, and elsewhere
  3. 3. 3 Scientific Communication, ~1600 Brahe Kepler
  4. 4. 4 1980
  5. 5. 5 Scientific Communication, ~2000 Data ArchivesData Archives User Analysis toolsAnalysis tools Gateway Figure: S. G. Djorgovski Discovery toolsDiscovery tools Service-Oriented Science
  6. 6. 6 Application Scenario Location A Microarray, Protein, Image data Location B Microarray, Protein, Image data Location C Microarray, Protein, Image data Location C Image Analysis Location D Image Analysis Microarray and protein databases at other institutions Different database systems, data representations, security Different program invocation, remote access, data transfer
  7. 7. 7 caBIG: sharing of infrastructure, applications, and data. Data Integration! Services & Cancer Biology Globus
  8. 8. 8 Service-Oriented Science People create services (data, code, instr.) … 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
  9. 9. 9 Creating Services People create services (data, code, instr.) … 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
  10. 10. 10 Anatomy of a Service op1 opN (meta)data Implementation(s) Clients Registry Management Clients … Service Service Attribute Authority Attribute Authority Persistence
  11. 11. 11 Creating Services (~2005) “This full-day tutorial provides an introduction to programming Java services with the latest version of the Globus Toolkit version 4 (GT4). The tutorial teaches how to build a Java Service that makes use of GT4 mechanisms for state management, security, registry and related topics.”
  12. 12. 12 Appln Service Create Index service Store Repository Service Advertize Discover Invoke; get results Introduce Container Transfer GAR Deploy Ohio State University and Argonne/U.Chicago Creating Services in 2008 Introduce and gRAVI Introduce Define service Create skeleton Discover types Add operations Configure security Grid Remote Application Virtualization Infrastructure Wrap executables Globus
  13. 13. Demonstration: Creating Services Introduce + gRAVI Shannon Hastings Scott Oster David Ervin Stephen Langella Kyle Chard Ravi Madduri
  14. 14. 14Center for Enabling Distributed Petascale Science Workflow Automation at DOE Facilities Automation Reproducibility Security Reusability Storage Metadata Analysis Visualization Advanced Photon Source
  15. 15. 15 Discovering Services 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
  16. 16. 16  The ultimate arbiter?  Types, ontologies  Can I use it?  Billions of services Discovering Services Assume success Syntax, semantics Permissions Reputation A B
  17. 17. 17 Discovery (1): Registries Globus
  18. 18. 18 Discovery (2): Standardized Vocabularies Core Services Grid Service Uses Terminology Described In Cancer Data Standards Repository Enterprise Vocabulary Services References Objects Defined in Service Metadata Publishes Subscribes to and Aggregates Queries Service Metadata Aggregated In Registers To Discovery Client API Index Service Globus
  19. 19. 19
  20. 20. 20 Discovery (3): Tagging & Social Networking GLOSS: Generalized Labels Over Scientific data Sources (Foster, Nestorov)
  21. 21. 21 Discovery (3): Tagging & Social Networking David de Roure, Carole Goble, et al.
  22. 22. 22 Composing Services 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
  23. 23. 23 Composing Services: E.g., BPEL Workflow System Data Service @ uchicago.edu Analytic service @ osu.edu Analytic service @ duke.edu <BPEL Workflow Doc> <Workflow Inputs> <Workflow Results> BPEL Engine link caBiG: https://cabig.nci.nih.gov/; BPEL work: Ravi Madduri et al. link link link See also Kepler & Taverna Globus
  24. 24. 24 Composing Services: Taverna caGrid Scavenger with semantic/metadata- based caGrid service query A sample caGrid workflow Globus
  25. 25. 25 Composing Services Globus
  26. 26. Demonstration: Composing Services Taverna + GT4 Taverna team Wei Tan Ravi Madduri
  27. 27. 27 Publishing Services 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
  28. 28. 28 Publishing Services Description  Syntax, semantics State  Availability, load, … Policies  Who, what, when, … Hosting  Location, scalability, …
  29. 29. 29 Authorization: SAML & XACML VOMS Shibboleth LDAP PERMIS… GT4 Client GT4 Server PDP Attributes Authorization Decision PIP PIP PIP SAML XACML Globus
  30. 30. 30 Hosting Services 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
  31. 31. 31 The Two Dimensions of Service-Oriented Science Decompose across network Clients integrate dynamically Select & compose services Select “best of breed” providers Publish result as new services Decouple resource & service providers Function Resource Data Archives Analysis tools Discovery toolsUsers Fig: S. G. Djorgovski
  32. 32. 32 The geWorkbench/caGrid/TeraGrid Interface
  33. 33. 33 Putting It Together for the Example Scenario Location A Microarray, Protein, Image data Location B Microarray, Protein, Image data Location C Microarray, Protein, Image data Location C Image Analysis Location D Image Analysis caGrid Service Interfaces caGrid Environ- ment Registered Object Definitions Advertise- ment Log on, Grid credentials Query and Analysis Workflow Discovery Microarray & protein databases at other institutions
  34. 34. 34 Lessons Learned A convenient higher-level abstraction Suitable for a subset of scientific use cases Infrastructure need to be sustainable Integrates well with hospital/cancer center/experimental facility IT infrastructure Workflows are attractive to users Scalability and provenance are important No vendor lock-in (if you are careful) User experience remains ambiguous Early adopters are enthusiastic (50+ services)
  35. 35. 35 Services for Science A new approach to communicating A (not-so new) approach to structuring systems They’re real Excellent infrastructure and tools (Globus, Introduce, gRAVI, Taverna, Swift, etc., etc.) Substantial numbers of services out there They’re challenging Sociology: incentives, rewards Infrastructure: hosting Provenance: justifying “results” Scaling: services, requests

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