g-social - enhancing e-science tools with social networking functionality

g-SocialEnhancing e-Science Tools with Social

Networking Functionality

Andriani Stylianou, Nicholas Loulloudes, Marios D. Dikaiakos

Overview

• Introduction

• Motivation

• Problem

• Current Solutions

• g-Social – Our Solution

• Abstractions

• Implementation

• Conclusion - Questions

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• Thousand years ago science was empirical– describing natural phenomena

• Last few hundred years: theoretical branch– using models, generalizations

• Last few decades: a computational branch– simulating complex phenomena

• Today: data exploration (eScience)– unify theory, experiment, and simulation

– Data captured by instrumentsOr generated by simulator

– Processed by software

– Information/Knowledge stored in computer

– Scientist analyzes database / filesusing data management and statistics

– “Computational X” and “X-Informatics”

Fourth Paradigm of Scientific Exploration (J. Gray)Source: J. Gray, talk to NRC/CSTB, “eScience - A Transformed Scientific Method.” Mountain View CA, 11 January 2007.

2009

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Jim Gray

Manager of Microsoft Research's eScience Group.

1998 ACM Turing Award

The disappearance of Tenacious (28/1/2007)

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FarallonIslands

The search for Tenacious (28/1/07 - 16/2/07)

• Night of 28/1: the USCG launched an airborne and seaborne SAR operation for Tenacious

– The SAR lasted for nearly two weeks - no signs found

• 31/1: the scientific community mobilized to help the SAR mission using online tools

– Computer scientists, oceanographers, engineers, volunteers, and Silicon Valley power players [NASA’s JPL, Amazon, Microsoft, Oracle, US Navy, Monterey Bay Aquarium Research

Institute, SDSC, Cornell Theory Center, Purdue, UWisc, Singular, Canadian Space Agency, Digital Globe.]

• A blog was setup to coordinate efforts and share ideas.Main foci of the effort were:

– Map the trajectory that Tenacious might have followed, in case Jim Gray lost control of the boat - to help guide the SAR operation

– Discover clues about Tenacious presence at sea

– Map the trajectories of large vessels traveling in the area, that may have collided with Tenacious

US/CG scoured 132,000 sq. miles of ocean5

Drift modeling

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The search for Tenacious: online version

An exemplary e-Science application scenario• A multidisciplinary virtual organization of people with a common goal

– Scientists, engineers, managers, officials, volunteers

• A variety of algorithms and software tools:

– Ocean-current models and simulators, image processing & recognition, cellphone signal tracking and triangulation, data-format transformation, data cleansing, satellite collection planning, data mining, image geo-referencing

• A deluge of data (hundreds of GBs) retrieved over the net from various sources, requiring processing and fusion to extract knowledge

– Satellite orbits, satellite imagery at different resolutions, multispectral datasets, Web Databases, radio buoy and airborne sensors, HF radars, data about offshore currents, Web cameras

• A federation of computing, networking and service infrastructures

– Grids, clusters, storage devices, crowd-sourcing services7

Computing Grids• e-Science motivated the development of Grid technologies and

Federated Computing Infrastructures during the last decade.

• The Grid vision by Foster, Kesselman, Tuecke [Grid 1.0]:

– Distributed computing infrastructures that enableflexible, secure, coordinated resource sharing among dynamic collections ofindividuals and institutions

– Enable communities ( “ Virtual Organizations ” ) to share geographicallydistributed resources as they pursue common goals, in the absence of:Homogeneity, Central location, Central control, Existing trust relationships

• The hype following the Grid:

– One of the sources of the impact of scientific and technological changes onthe economy and society [Jeremy Rifkin, “The European Dream,” Penguin2004]

– The Grid has been described as the Next Generation Internet, theimplementation of the Global Computer etc.

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Grid Infrastructure development

‣ Nowadays, Grid infrastructures comprise an impressivecollection of computational and software resources‣ drawing an increasing number of users from various disciplines

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MotivationData-Intensive Scientific Projects

Resources

Grid / Cloud Computing

Traditional Collaboration Tools

Scientists

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Problem

• Collaboration is done externally to scientificsoftware environments(email, web, portals, IM, etc.).

• Manual effort for transferring informationfrom one tool to another.

• Error prone and time consuming.

Lack of a unified, user-friendly software and collaboration environment for scientists.

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Current Solutions

General-Purpose OSN

Pros• Professional Networking• Minimal Collaboration FunctionalityCons• External to existing scientific software

environments – Web Based• Do not support resource* sharing

Scientific OSN

Pros• More immersive collaboration environment

than Generic OSN.• Resource sharing and ability to run

experiments.Cons• Application Domain Specific.• Proprietary infrastructures – High

maintenance.• Introduce additional information sources ->

User Information overload 13

Our Solution

g-Eclipse (www.eclipse.org/geclipse)• Integrated workbench framework• Build on-top of Eclipse (Extensible and community support)• Toolset for users, operators & developers of Grid/Cloud infrastructures

(gLite, GRIA, Amazon AWS) – Middleware agnostic• Rich functionality:

• Development & Deployment• Benchmarking & Testing• Workflow Programming

Online Social Networks• Easy establishment and management of groups• Automatic dissemination of notifications• Professional Networking• High Availability

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Information View

Grid Project View

Authentication View JSDL Editor View

Workbench

g-Eclipse

g-Social

Build on-top of the g-Eclipse FrameworkAims to enable collaboration among scientists that are/will utilize g-Eclipse

Features• Social Abstractions (Resources, Meta-data, Authentication).

• Definition of structured and standardized social meta-data

• Enrich social meta-data with links to project related resources.

• Access resources easily .

• Share project data and meta-data.

• Retrieve shared information.

• Seamless interaction with OSN.

• Facebook

• Twitter

• Extensible for other OSNs

g-Social Work Cycle 16

g-Social Abstractions

Enable seamless sharing and retrieval (via an OSN) of all particulars of theresearch work performed in the context of a real scientific project.

Abstract a Scientific Collaborative Environment which utilize Online SocialNetworks.

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Abstractions - Resources

Any file(s) related to the execution ofa Grid task specific to a scientificproject

• Input / Output Dataset

• Executable

• Source Code

• Documentation

• Publications

• …

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Abstractions – Social Meta-data

Descriptive meta-data that provide tothe OSN and its users informationabout purpose and function of eachshared particular

• Name

• Function

• Purpose

• Version

• Tags

• License

• ….

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Abstractions – Authentication Manager

Enforces security and privacy controlof users while interacting with theOSN

• Authorization / Authenticationagainst an OSN

• Monitor life-cycle of authenticationtokens

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Abstractions – Resource Manager

Resource sharing• Interact with Authentication Manager• Social meta-data• Encapsulate the above in a form

acceptable by and OSN

Resource Retrieval• Extraction of published meta-data• g-Eclipse Authentication Manager

invocation• Resource access via g-Eclipse file

system• Resource import in g-Eclipse workspace

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Abstractions – OSN Interface

• OSN are by design web-basedsystems

• OSN-gEclipse interface serves as anintermediate between the web-browser and g-Eclipse.

• Invoking g-Eclipse when user clickson an g-Social link inside an OSN.

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g-Social Implementation

• The g-Eclipse Grid Project.

• A placeholder for the organization of files/information related to the execution of Grid/Cloud tasks

• Executables (local file system)

• Input / Output dataset (g-Lite, AWS)

• Documentation

• Publication (IEEE, ACM, Elsevier)

• Infrastructure Configurations

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Implementation (Social Meta-Data Editor)

• Multi-Page GUI Editor• Easy Insertion of social

meta-data• Specify Location of

Resources

• XML content meta-data• Extend Job Submission Definition

Language (JSDL) schema to includesocial meta-data specification.

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Share Job

View Job Details

OSN AuthenticationSearch for Shared JobsCollaborators

List of Shared Jobs

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g-Social View

Authorization• Authenticate / Authorize

against OSN• Check auth of the underlying

storage infrastructure whenlinking or retrieving aresource

• Manage auth tokens life-cycle

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Implementation (g-Social View)

Share Job to OSN• Share job details as defined

in meta-data editor• Ask user to which OSN

details should be posted• Parse social meta-data• Encapsulate them in OSN

specific post formats.

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Implementation (g-Social View)

Implementation (g-Social View)

View Share Job Details• Social Meta-data

• Name• Description• Version

• Resource Handles• Download Resource

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Conclusions & Future Work

Future Work• Standardize social meta-data definition• Support additional OSNs• Recommendation System• Release g-Social to Eclipse

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Conclusionsg-Social enhances integrated e-Science Tools (g-Eclipse) withSocial Networking functionality. Specifically it:• Enables the definition of social meta-data for sharing and

retrieval of information among scientists.• Enriches meta-data with resource handles which might be

scattered in heterogeneous storage infrastructures.• Provides mechanisms for sharing and retrieving scientific

information with just a few clicks.

Questions – Contact Information

Andriani Stylianou (andriani.stylianou@epfl.ch)

Nicholas Loulloudes (loulloudes.n@cs.ucy.ac.cy)

Marios D. Dikaiakos (mdd@cs.ucy.ac.cy)

http://grid.ucy.ac.cy

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