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Collaborative eScience: Evolving Approaches Charles Severance Rutgers CyberInfrastructure Meeting April 4, 2006 www.dr-chuck.com

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Page 1: A View on eScience

Collaborative eScience: Evolving Approaches

Charles Severance

Rutgers CyberInfrastructure Meeting

April 4, 2006

www.dr-chuck.com

Page 2: A View on eScience

Outline

• A look back at the past 15 years • Putting the “collab” in Collaborative eScience• The current tools of Collaborative eScience

– Collaboration– Portals– Repository

• Reflecting on 15 years of Experience– What is wrong with Middleware?– Authorization and Authentication - Are we there yet?

• A “future” eScience Case Study

Page 3: A View on eScience

The Founding Concepts

• Scientific Domain• Groups of People• Common User Interface• Data Sharing

– In the moment– Long-term

• Experimental Equipment• Compute• Visualization

Page 4: A View on eScience

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 ?

Page 5: A View on eScience

What was SPARC?

BeforeUARC..

Page 6: A View on eScience

What was SPARC?

UARC/SPARC

Page 7: A View on eScience

SPARC

2/2001 600 users 800 data sources

Page 8: A View on eScience

SPARC Software

• Written from scratch– No Middleware– No Portal Technology

• Three rewrites over 10 years– NextStep– Java Applets with server support– Browser based - kind of like a portal

• At the end, in 2001 - it was ready for another rewrite

Page 9: A View on eScience

Keys to SPARC Success

• Ten years of solid funding– Team consistency – Long enough to learn 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

Page 10: A View on eScience

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

Page 11: A View on eScience

WorkTools

Over 9000 users (2000 active) at the end of 2003

WorkTools - The “organic” single-server approach - if you build it (and give away free acounts), they will come…

Page 12: A View on eScience

CompreHensive CollaborativE Framework (CHEF)

• Fall 2001: CHEF Development begins – Generalized extensible framework for building

collaboratories

• Funded internally at UM• All JAVA - Open Source

– Jakarta Jetspeed Portal– Jakarta Tomcat Servlet Container– Jakarta Turbine Service Container

• Build community of developers through workshops and outreach

Page 13: A View on eScience

CHEF Applications

• CourseTools Next Generation

• WorkTools Next Generation

• NEESGrid

• NSF National Middleware Grid Portal

Page 14: A View on eScience

NEESGrid - The EquipmentNetwork for Earthquake Engineering Simulation

NSF Funded. NCSA, ANL, USC/ISI, UM, USC, Berkeley, MSU

Page 15: A View on eScience

CHEF-Based NEESGrid Software

Page 16: A View on eScience

Overall Data Modeling EffortsOverall Data Modeling Efforts

NEES

Site A Site CSite B

Equipment People

Experiments Trials

Equipment People

Experiments Trials

Data Data Data

TsnumaiSpecimen

Shake TableSpecimen

GeotechSpecimen

CentrifugeSpecimen

Units Sensors Descriptions

SiteSpecificationsDatabase

ProjectDescription

Domain Specificmodels

Common Elements

Data / Observations

Page 17: A View on eScience

DT Main System

PTZ/USB

StillCapture

DT Client

BT848Video

Frames

DT Client

Capturing Video and Data

Camera ControlGateway

DAQData

CaptureDT Client

SimulationCoordinator

Site A Site B

Page 18: A View on eScience

DT Main System

Data Monitoring Tools

Still Image / Camera Control

~

< >^

^

< >

Camera ControlGateway

Creareviewers

Still imagecameracontrol

Thumb-nail

Page 19: A View on eScience

What’s in a name?

Sakai is named after Hiroyuki Sakai of the Food Channel Television program “Iron Chef”. Hiroyuki is renowned for his fusion of French and Japanese cuisine.

Page 20: A View on eScience

Sakai General Collaborative Tools

• Announcements • Assignments

• Chat Room

• Threaded Discussion

• Drop Box

• Email Archive

• Message Of The Day

• News/RSS

• Preferences

• Resources

• Schedule

• Web Content

• Worksite Setup

• WebDAV

Page 21: A View on eScience

Requirements Overlap

PhysicsResearch

Collaboration

EarthquakeResearch

Collaboration

Teachingand

Learning

Grid ComputingVisualization

Data Repository

Large DataLibraries

QuizzesGrading Tools

SyllabusSCORM

ChatDiscussionResources

Page 22: A View on eScience

Sakai: Product Placement

Collaboration and eResearch

TeachingandLearning

Page 23: A View on eScience

Additional General CollaborationTools Under Development

• Wiki based on Radeox

• Blog• Shared Display• Shared

Whiteboard• Multicast Audio• Multicast Video

These are works-in-progress by members of the Sakai eResearch community. There are no dates for release.

Page 24: A View on eScience

NMI / OGCE www.ogce.org

NSF National Middleware InitiativeIndiana, UTexas, ANL, UM, NCSA

Page 25: A View on eScience

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

Page 26: A View on eScience

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

Page 27: A View on eScience

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

Page 28: A View on eScience

The Ecology of Collaborative eScience

Page 29: A View on eScience

CollaborativeTools

SharedCompute

DataSources

DataRepository

PortalTechnology

KnowledgeTools

Scope of Collaborative E-Science“..composing and orchestrating many technologies…”

“..interoperability is key…”

IdentityACL

Page 30: A View on eScience

User Interface for Collaborative E-

Science

Portals are an excellent technology for building a federated user interface across these disparate components using standards like JSR-168.

CollaborativeTools

SharedCompute

DataSources

DataRepository

PortalTechnology

KnowledgeTools

IdentityACL

Page 31: A View on eScience

Portals may only be an intermediate

step in the process..

CollaborativeTools

SharedCompute

DataSources

DataRepository

PortalTechnology

KnowledgeTools

IdentityACL

DesktopApplications

Page 32: A View on eScience

Focus of Sakai Activity in eScience

Sakai is focused primarily on integration with portals and working closely with data repositories.

CollaborativeTools

SharedCompute

DataSources

DataRepository

PortalTechnology

KnowledgeTools

IdentityACL

Discuss First

Page 33: A View on eScience

Collaboration .vs. Portal • Basic organization is about the

thing it represents - Teragrid, NVO

• Site customization is based on the resource owners

• Sometimes there is an individual customization aspect

• Many small rectangles to provide a great deal of information on a single screen

• Portals think of rectangles operating independently - like windows

• Think “Dashboard”

• Basic organization is about the shape of the people and groups

• Customization based on the “group leaders”

• New groups form quickly and organically

• Doing one thing at a time - chat, upload - perhaps multiple active windows on a desktop

• Very interactive• Think of navigation as picking a tool

or switching from one class to another

• Think “Application”

Page 34: A View on eScience

Sakai Portlet Version 0.2

• Tree View

• Gallery View

• Proxy portlets

• Source in SVN

• Configurable via properties file

Announcements (sakai.announcements)

Assignments (sakai.assignment)

Chat Room (sakai.chat)

Discussion (sakai.discussion)

Gradebook (sakai.gradebook.tool)

Email Archive (sakai.mailbox)

Membership (sakai.membership)

Message Forums (sakai.messageforums)

Preferences Tool (sakai.preferences)

Presentation (sakai.presentation)

Profile (sakai.profile)

Resources (sakai.resources)

Wiki (sakai.rwiki)

Tests & Quizzes (sakai.samigo)

Roster (sakai.site.roster)

Schedule (sakai.schedule)

Site Info (sakai.siteinfo)

Syllabus (sakai.syllabus)

Page 35: A View on eScience

Sakai JSR-168 Portlet

• Web Services are used to login to Sakai establish a session and retrieve a list of Sakai Sites, Pages, and Tools

• The portlet is 100% stock JSR-168– Works in Pluto, uPortal, and GridSphere

Page 36: A View on eScience

Three Variations

• Display the Sakai gallery - all of Sakai except for the login and branding.

• Retrieve the hierarchy of sites, pages and tools display in a tree view with the portlet and show selected tools/pages in an iframe within the portlet

• Proxy tool placement for a particular Sakai tool such as sakai.preferences

Page 37: A View on eScience

Sakai Gallery View

Page 38: A View on eScience

How Gallery Works

uPor

tal,

Plu

to,

or G

ridS

pher

e

Sak

ai

Web

Svc

sC

haro

nP

orta

l

Sak

aiP

ortle

t

Login

/portal/gallery

Page 39: A View on eScience

Sakai Tree View

Page 40: A View on eScience

How Tree View Works

uPor

tal,

Plu

to,

or G

ridS

pher

e

Sak

ai

Web

Svc

sC

haro

nP

orta

l

Sak

aiP

ortle

t

Login

ToolList

/portal/page/FF96

Page 41: A View on eScience

Sakai Proxy Tool

Page 42: A View on eScience

Proxy Tool Selection

Page 43: A View on eScience

How Proxy Portlet Works

uPor

tal,

Plu

to,

or G

ridS

pher

e

Sak

ai

Web

Svc

sC

haro

nP

orta

l

Sak

aiP

ortle

t

Login

SiteList

/portal/page/FF96

1

2

Page 44: A View on eScience

SakaiSite.getToolsDom<sites> <portal>http://localhost:8080/portal</portal> <server>http://localhost:8080</server> <gallery>http://localhost:8080/gallery</gallery> <site> <title>My Workspace</title> <id>~csev</id> <url>http://localhost:8080/portal/worksite/~csev</url> <pages> <page> <id>af54f077-42d8-4922-80e3-59c158af2a9a</id> <title>Home</title> <url>http://localhost:8080/portal/page/af54f077-42d8-4922-80e3-59c158af2a9a</url> <tools> <tool> <id>b7b19ad1-9053-4826-00f0-3a964cd20f77</id> <title>Message of the Day</title> <toolid>sakai.motd</toolid> <url>http://localhost:8080/portal/tool/b7b19ad1-9053-4826-00f0-3a964cd20f77</url> </tool> <tool> <id>85971b6b-e74e-40eb-80cb-93058368813c</id> <title>My Workspace Information</title> <toolid>sakai.iframe.myworkspace</toolid> <url>http://localhost:8080/portal/tool/85971b6b-e74e-40eb-80cb-93058368813c</url> </tool> </tools> </page> </pages> </site></sites>

New WS method is upwards compatible with getSitesDom

Page 45: A View on eScience

Sakai Repository Integration Approach

Page 46: A View on eScience

Focus of Sakai Activity in eScience

Sakai is focused primarily on integration with portals and working closely with data repositories.

CollaborativeTools

SharedCompute

DataSources

DataRepository

PortalTechnology

KnowledgeTools

IdentityACL

Discuss Now

Page 47: A View on eScience

Collaboration .vs. Repository

• Many different systems may be active at the same time

• Systems evolve, improve, and are often replaced every few years

• Systems focused on the dynamic needs of users and applications

• Thousands of simultaneous online users

• Performance tuning• Must be very easy to use;

almost unnoticeable• Used informally hundreds of

times per day per user• Think “E-Mail”

• Generally one system for the area

• Long term strategic choice for institution

• System focused on accessing, indexing, curation, and storage

• Millions of high quality objects properly indexed

• Data and metadata quality• Must enforce standards and

workflow to insure data quality• Most use is very purposeful:

search, publish, add value• Think “Library”

Page 48: A View on eScience

Inbound Object Flow

Ingest

Create and use in

native form

Pre

pare

for

stora

ge

DataModel

Store

Curate, convert, update and maintain over time

Index Lens

Se

arch

Vie

w

Re

use

DRSakai

The DR establishes a data model for “site” objects. The CLE hands sites to the DR. The DR may have to do “model” or content cleanup

before completing the ingest process.

The lens or disseminator understands

the data model and is capable of

rendering the objects. The lens is part of

the DR.

Preparation for storage may include cleanup, conversion,

copyright clearance, and other workflow steps.

Page 49: A View on eScience

Outbound Object Flow

DataModel

Index LensSearch

Vie

w

Reuse

DR

Sakai

Sakai can find and re-use objects in the

repository.

DataModel

Lens

Vie

w

Se

arch

Reuse

Page 50: A View on eScience

Sakai and Repositories Going Forward

• Instead of solving the problem by creating a single DR technology that is a superset - which might take years

• Focus on data portability between systems - reduce the impedance mismatch (or needed conversion between systems)

• RDF enables object portability across systems, languages, and technologies

Page 51: A View on eScience

Sakai Repository Approach

• Move Sakai and other Collaboration systems toward RDF– Experiment with using RDF as native storage format– High Performance RDF - Fedora testing - 180M tuples -

complex queries - 70ms

• Move data repositories toward RDF– Move from schema-based stovepipe objects to OWL/RDF

based objects with referential integrity– Explore dimensions of portability of disseminator / lenses -

this is an important research area

• Get started immediately….

Page 52: A View on eScience

Fedora Images

Page 53: A View on eScience

Some Reflections

Page 54: A View on eScience

CollaborativeTools

SharedCompute

DataSources

DataRepository

PortalTechnology

KnowledgeTools

Where is the Middleware?

“..composing and orchestrating many technologies…”

“..interoperability is key…”

IdentityACL

Page 55: A View on eScience

Middleware

CollaborativeTools

SharedCompute

DataSources

DataRepository

PortalTechnology

KnowledgeTools

IdentityACL

Is Middleware The Universal Connector?

Page 56: A View on eScience

CollaborativeTools

SharedCompute

DataSources

DataRepository

PortalTechnology

KnowledgeTools

IdentityACL

The Universal Connectors

tcp/ip http/https

web services

Page 57: A View on eScience

CollaborativeTools

SharedCompute

DataSources

DataRepository

PortalTechnology

KnowledgeTools

Is Middleware “inside” each application?

IdentityACL

Page 58: A View on eScience

CollaborativeTools

SharedCompute

DataSources

DataRepository

PortalTechnology

KnowledgeTools

Middleware is simply another component - used as needed

Middleware

IdentityACL

Page 59: A View on eScience

CollaborativeTools

SharedCompute

DataSources

DataRepository

PortalTechnology

KnowledgeTools

Identity and Access Control: A very important function of Middleware

Middleware

IdentityACL

Lets Talk about This

Page 60: A View on eScience

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

Page 61: A View on eScience

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?

Page 62: A View on eScience

AUTHN/AUTHZ Meetings

Page 63: A View on eScience

My eScience Fantasy

Page 64: A View on eScience

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

Page 65: A View on eScience

A

B

D

E

Vol 4Vol 3

Vol 2Vol 1F

C

Compute

Data Models

Tutorials

Experiments

Remote Observation

eDocuments

Page 66: A View on eScience

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

Page 67: A View on eScience

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

• 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

Page 68: A View on eScience

Heart Study CollaboratoryLogin

My Workspace A B C D E Open Forum

Home

Chat

Resources

Tutorials

Site B

Mail List

Live Meetings

Page 69: A View on eScience

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

Page 70: A View on eScience

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

Page 71: A View on eScience

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

Page 72: A View on eScience

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

Page 73: A View on eScience

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

Page 74: A View on eScience

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

Page 75: A View on eScience

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

Page 76: A View on eScience

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

Page 77: A View on eScience

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

Page 78: A View on eScience

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 is not “in the middle”)

• 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

Page 79: A View on eScience

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”