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Collaborative eScience: Evolving Approaches
Charles Severance
NCeSS eCollaboration Workshop
June 28, 2006
This material is Copyright Creative Commons Attribution 2.5
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Outline
• A look back at the past 15 years • Putting the “collab” in Collaborative eScience• The current tools of Collaborative eScience
– Collaboration– Portals– Repository
• Some Refections• A “future” eScience Case Study
Some sections are hidden to fit into 30 minutes…
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The Founding Concepts
• Scientific Domain• Groups of People• Common User Interface• Data Sharing
– In the moment– Long-term
• Experimental Equipment• Compute• Visualization
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Over 15 Years of Collaborative eScience
20001991 - 1999 2001 2002 2003 2004 2005 2006 2007
UARC/SPARC
SakaiWorktools CHEF
OGCE Grid Portal
NEESGrid
Globus Tool Kit
NEESIT
SCIGate ?
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What was SPARC?
BeforeUARC..
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What was SPARC?
UARC/SPARC
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SPARC
2/2001 600 users 800 data sources
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SPARC Software (1991-2001)
• Written from scratch– No Middleware– No Portal Technology
• Three rewrites over 10 years– NextStep (Version 1)– Java Applets with server support (Version 2)– Browser based - kind of like a portal (Version 3)
• At the end, in 2001 - it was ready for another rewrite
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Keys to SPARC Success
• Ten years of solid funding– Team consistency – Long enough to make and recover from “mistakes”
• Long term relationship between IT folks and scientists - evolved over time - relationship was “grey”
• Software rewritten several times over life of project based on evolving user needs and experience with each version of the program
• Portion of effort was invested in evaluation of usability - feedback to developers
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After SPARC: Now What?
• Getting people together is an important part of collaborative eScience– WorkTools - Based on Lotus Notes– CHEF - Collaborative framework - Based on Java and
Jetspeed– Sakai - Collaboration and Learning Environment - Java
• Critical point: Collaborative software is only one component of eScience
• UM Focus: Building reusable user interface technologies for the people part of collaborative eScience
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NEESGrid
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Sakai
CHEF and NEES - hidden
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Sakai General Collaborative Tools
• Announcements • Assignments
• Blog
• Chat Room
• Threaded Discussion
• Drop Box
• Email Archive
• Message Of The Day
• News/RSS
• Preferences
• Resources
• Schedule
• Web Content
• Wiki
• Worksite Setup
• WebDAV
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Sakai: Product Placement
Collaboration and eResearch
TeachingandLearning
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NMI / OGCE www.ogce.org
NSF National Middleware InitiativeIndiana, UTexas, ANL, UM, NCSA
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Chalk Talk:School of Portals (2004)Chalk Talk:School of Portals (2004)
OGCE 1.1OGCE 1.1
XCATXCAT
NEES 3.0NEES 3.0
GridPortGridPort
NEES 1.1NEES 1.1
GridPort 3GridPort 3
SakaiSakai
uPortaluPortal
CHEFCHEF OGCE 1.2 ?OGCE 1.2 ?
OGCE 2OGCE 2JetspeedJetspeed
AllianceAlliance
GridPort 2GridPort 2
CompetitionCompetition CollaborationCollaboration ConvergenceConvergence
GridSphereGridSphere
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Chalk Talk:School of eScience Portals (2006)Chalk Talk:School of eScience Portals (2006)
OGCE 1.1OGCE 1.1
XCATXCAT
GridPortGridPort
NEES 1.1NEES 1.1
GridPort 3GridPort 3
SakaiSakai
uPortaluPortal
CHEFCHEF
OGCE 2OGCE 2JetspeedJetspeed
AllianceAlliance
GridPort 2GridPort 2
CompetitionCompetition CollaborationCollaboration ConvergenceConvergence
GridSphereGridSphere
SciGate ?SciGate ?
SciDocSciDoc
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Atlas
Portal Gateway Desktop Gateway
Applicationsand Users
ITER CMS
GatewayTechnologies
Services andComponents
Resources
SR
B
PetascaleCompute
Cla
ren
s
Ide
ntit
y
Se
curit
y
Op
al
Me
taD
ata
PetascaleData
SciGateProduction
Integration andAdministration
Sa
kai
Glo
bu
s
Blu
eG
en
e
OR
NL
…
ManagementComponents
Co
ntr
ol
Exp
erim
en
t
Sim
ula
tion
Kn
ow
led
ge
Sto
re
…Pro
cess
…
…
Configure: Atlas Portal Experiment Process Control Knowledge Store Sakai SRB Opal Clarens Metadata
Configure: ITER Portal Experiment Process Control Knowledge Store Sakai SRB Opal Clarens Metadata
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Some Reflections
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Some Reflections
• Computer Scientists like to “stay in their box”• Many of the technology solutions work well in
their “initial domain”• Once an eScience team “adopts” a technology
(often step 1) their further progress (and focus) is limited by the technology.
• Agility is very important in the early phases of eScience
• Builders of components *must* make their component as interoperable as possible
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Sakai and Web 2.0Web 2.0 is about making sure data is available in some form beyond just displayed in the Sakai Tool Set. – Formats
• RSS• Resource Description Framework (RDF)• HTML
– Protocols• RSS / getData / SOAP / REST
– Consuming Applications• Portals• Google• delic.io.us
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Sakai Data Interoperability
... interoperability and data portability are key elements...
AuthoringAuthoringEnvironmentEnvironment
PersonalPersonalEnvironmentEnvironment
PortalPortalEnvironmentEnvironment
CollaboarationCollaboarationEnvironmentEnvironment
ContentContentManagementManagement
LMS SystemsLMS Systems
DataDataRepositoryRepository
IdentityACL
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HT
ML
H
TM
LR
ES
T
WebDavSOAP
iCal
SPARQL
RSSCalDav
Collaborationand
Learning
WebDavSOAP Collaborationand
Learning
Current Sakai
Future Sakai
Sakai “Swiss Army Knife”
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Interoperability at the UIRSS, ATOM, RDF,
SOAP, REST, HTML
The SOAUI
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Reflecting on Middleware and Virtual Organizations
(slides not hidden)
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CollaborativeTools
SharedCompute
DataSources
DataRepository
PortalTechnology
KnowledgeTools
Where is the Middleware?
“..composing and orchestrating many technologies…”
“..interoperability is key…”
IdentityACL
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Middleware
CollaborativeTools
SharedCompute
DataSources
DataRepository
PortalTechnology
KnowledgeTools
IdentityACL
Is Middleware The Universal Connector?
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SharedCompute
DataSources
DataRepository
PortalTechnology
KnowledgeTools
IdentityACL
The Universal Connectors
tcp/ip http/https
web services
CollaborativeTools
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CollaborativeTools
SharedCompute
DataSources
DataRepository
PortalTechnology
KnowledgeTools
Is Middleware “inside” each application?
IdentityACL
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CollaborativeTools
SharedCompute
DataSources
DataRepository
PortalTechnology
KnowledgeTools
Middleware is simply another component - used as needed
Middleware
IdentityACL
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CollaborativeTools
SharedCompute
DataSources
DataRepository
PortalTechnology
KnowledgeTools
Identity and Access Control: A very important function of Middleware
Middleware
IdentityACL
Lets Talk about This
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Chalk Talk:Identity and Access ControlChalk Talk:Identity and Access Control
CASCAS
ShibbolethShibboleth
KerberosKerberos
GlobusGlobus
CompetitionCompetition CollaborationCollaboration ConvergenceConvergence
LDAPLDAP
PubCookiePubCookie
K.X509K.X509
MyProxyMyProxy
????
GridShibGridShib
CosignCosign
???
IdentityACL
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Identity and ACL: Goal State
• One server - one software distribution• Virtual Organization Software• Supports all protocols
– Globus Certificate Authority– Shibboleth– LDAP– MyProxy– Kerberos
• Who will do this? Who will fund this? Who can get these competitors to cooperate?
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AUTHN/AUTHZ Meetings
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My eScience Fantasy
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The pre-requisites
• My net worth is $5B (I give myself grants)• I encounter some tech-savvy scientists in a field who
are using technology to do world-class research…• They have never been visited by any other computer
scientist…• They are working in groups of 1-30 geographically
distributed around the world• They all work on a beach with Internet2 connections
and wide-open wireless and favourable exchange rates
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A
B
D
E
Vol 4Vol 3
Vol 2Vol 1F
C
Compute
Data Models
Tutorials
Experiments
Remote Observation
eDocuments
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Step 1: Visit The Scientists
• Understand what they are doing and how they are doing it?
• Ask them how they would like to improve it.• Show each application to other scientists.
Ask the other scientists how they would improve it.
• Help each group improve their work - help them using whatever technology they are currently using
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Step 2: Add some technology
• Install the super-multi-protocol Virtual Organization software and provide a NOC for the VO software - identity and simple attributes - make sure the VO is easy to use!
• Install Sakai - point it at the VO software for identity add icon at the top of Sakai
• Give each scientist an account in the VO• Give each effort in the field a site within Sakai
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Heart Study CollaboratoryLogin
My Workspace A B C D E Open Forum
Home
Chat
Resources
Tutorials
Site B
Mail List
Live Meetings
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Step 2: Use the VO
• For those who want to protect their information, help them add SSO to their sites, backed by the VO service
• Since it is multi-protocol - likely there will be no modification of the underlying science code - only a server configuration change Identity
ACL
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A
B
D
E
Vol 4Vol 3
Vol 2Vol 1F
C
Compute
Data Models
Tutorials
Experiments
Remote Observation
eDocumentsIdentityACL
Heart Study CollaboratoryLogin
My Workspace A B C D E Open Forum
Home
Chat
Resources
Tutorials
Site B
Mail List
Live Meetings
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Step 4: Unique Identifier Service
• Come up with a way for any member of the VO to “get” a unique identifier
• Demand some information (build a little data model)– Person’s name and organization (implicit from request)– What kind of thing this will represent (experiment, document, image
series)– Simple description– Keyword/value extensions
• Build an simple way request and retrieve these through a simple web service - capture implicit metadata from request (when, IP address, etc). Make sure it works from perl!
• Encourage community to start marking “stuff” with these identifiers in their stovepipes
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Step 5: Data Models
• Begin to work with subsets of the field to try to find common data models across stovepipes
• Start simple - use very simple RDF - human readable
• Broaden / deepen model slowly - explore variations
• Define simple file-system pattern for storing metadata associated with a file and/or a directory
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Step 6: A Backup-Style Repo
• Build a data repository which will function as a backup
• Basic idea - each time you get identifier - this enables backup space - any data and/or metadata can be uploaded under that particular identifier and left in the repository
• Make the repo multi-protocol, FTP, DAV, Web-Service with attachments, GridFTP, etc.
• Make it so there can be a network of cooperating repositories
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A
B
D
E
Vol 4Vol 3
Vol 2Vol 1F
C
Compute
Data Models
Tutorials
Experiments
Remote Observation
eDocumentsIdentityACL
Heart Study CollaboratoryLogin
My Workspace A B C D E Open Forum
Home
Chat
Resources
Tutorials
Site B
Mail List
Live Meetings
GUIDService
CentralRepo
LocalRepo
LocalRepo
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Year 4 and on…
• Once the basic stovepipes have been “brought in from the cold” and made part of a community with no harm, the next steps are to begin to work “cross-stovepipe”– Evolve data models to be far richer with many variants– Build value added tools that are aware of the data models
and are usable across stovepipes
• Teach the community to build and share tools - gently encourage development standards - Java / JSR-168 perhaps
• Most important: Always listen to the users
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Science at the center of
eScience
Connect
Enhance
Data Models
Data Storage
New Tools
New Approaches
PriorityScience
Scientists
… start at the center and work outwards…
… apply technology when the users will see it as a “win” …
Com
mun
icat
e
New
Tec
hnol
ogie
s
Rep
osito
ries
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Conclusion
• Many years ago, eScience had science as its main focus
• Custom approaches resulted in too many unique solutions
• Computer scientists began a search for the “magic bullet” - each group found a different magic bullet
• Each group now competes for mind share (and funding) to be the “one true” magic bullet
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Conclusion (cont)
• One way to solve the “many competing technologies” solution is to form “super groups” which unify the technologies
• No single technology gets to claim “they are the one” (Middleware cannot be “in the middle” because then it gets “in the way”)
• Each technology needs to become a drop-in service/component which is available for use only when appropriate
• Once we can get past looking at the technologies as the main focus, we get back to science as the main focus
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Lets remember why we started this whole field in the first place…
• Scientific Domain• Groups of People• Common User Interface• Data Sharing
– In the moment– Long-term
• Experimental Equipment• Compute• Visualization
To downloadwww.dr-chuck.com
“Chuck’s Talks”