SlideShare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our User Agreement and Privacy Policy.
SlideShare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our Privacy Policy and User Agreement for details.
Successfully reported this slideshow.
Activate your 14 day free trial to unlock unlimited reading.
g-Social - Enhancing e-Science Tools with Social Networking Functionality
Presentation of "g-Social - Enhancing e-Science Tools with Social Networking Functionality" given at the Workshop on Analyzing and Improving Collaborative eScience with Social Networks, Chicago October 8th, 2012. Co-located with IEEE eScience 2012.
Presentation of "g-Social - Enhancing e-Science Tools with Social Networking Functionality" given at the Workshop on Analyzing and Improving Collaborative eScience with Social Networks, Chicago October 8th, 2012. Co-located with IEEE eScience 2012.
3.
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.
• 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 instruments
Or generated by simulator
– Processed by software
– Information/Knowledge stored in computer
– Scientist analyzes database / files
using data management and statistics
– “Computational X” and “X-Informatics” 2009
3
4.
The disappearance of Tenacious (28/1/2007)
Farallon
Islands
Jim Gray
Manager of Microsoft Research's eScience Group.
1998 ACM Turing Award
4
5.
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 ocean
5
7.
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 services
7
8.
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 enable
flexible, secure, coordinated resource sharing among dynamic collections of
individuals and institutions
– Enable communities ( “ Virtual Organizations ” ) to share geographically
distributed 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 on
the economy and society [Jeremy Rifkin, “The European Dream,” Penguin
2004]
– The Grid has been described as the Next Generation Internet, the
implementation of the Global Computer etc.
8
9.
Grid Infrastructure development
‣ Nowadays, Grid infrastructures comprise an impressive
collection of computational and software resources
‣ drawing an increasing number of users from various disciplines
9
11.
Problem
• Collaboration is done externally to scientific
software environments
(email, web, portals, IM, etc.).
• Manual effort for transferring information
from one tool to another.
• Error prone and time consuming.
Lack of a unified, user-friendly software and
collaboration environment for scientists.
11
12.
Current Solutions
Pros
• Professional Networking
• Minimal Collaboration Functionality
General-Purpose
Cons
OSN • External to existing scientific software
environments – Web Based
• Do not support resource* sharing
Pros
• More immersive collaboration environment
than Generic OSN.
• Resource sharing and ability to run
experiments.
Scientific OSN Cons
• Application Domain Specific.
• Proprietary infrastructures – High
maintenance.
• Introduce additional information sources ->
User Information overload 13
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
14
14.
g-Eclipse
Grid Project
View
W
o
r
k
b
e
n
c
h
Information View Authentication View JSDL Editor View
15
15.
g-Social
Build on-top of the g-Eclipse Framework
Aims 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
16.
g-Social Abstractions
Enable seamless sharing and retrieval (via an OSN) of all particulars of the
research work performed in the context of a real scientific project.
Abstract a Scientific Collaborative Environment which utilize Online Social
Networks.
17
17.
Abstractions - Resources
Any file(s) related to the execution of
a Grid task specific to a scientific
project
• Input / Output Dataset
• Executable
• Source Code
• Documentation
• Publications
• …
18
18.
Abstractions – Social Meta-data
Descriptive meta-data that provide to
the OSN and its users information
about purpose and function of each
shared particular
• Name
• Function
• Purpose
• Version
• Tags
• License
• ….
19
19.
Abstractions – Authentication Manager
Enforces security and privacy control
of users while interacting with the
OSN
• Authorization / Authentication
against an OSN
• Monitor life-cycle of authentication
tokens
20
20.
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
21
21.
Abstractions – OSN Interface
• OSN are by design web-based
systems
• OSN-gEclipse interface serves as an
intermediate between the web-
browser and g-Eclipse.
• Invoking g-Eclipse when user clicks
on an g-Social link inside an OSN.
22
22.
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
23
23.
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 include
social meta-data specification.
24
24.
g-Social View
Collaborators Search for Shared Jobs OSN Authentication
List of Shared Jobs Share Job
View Job Details
25
25.
Implementation (g-Social View)
Authorization
• Authenticate / Authorize
against OSN
• Check auth of the underlying
storage infrastructure when
linking or retrieving a
resource
• Manage auth tokens life-
cycle
26
26.
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.
27
27.
Implementation (g-Social View)
View Share Job Details
• Social Meta-data
• Name
• Description
• Version
• Resource Handles
• Download Resource
28
28.
Conclusions & Future Work
Conclusions
g-Social enhances integrated e-Science Tools (g-Eclipse) with
Social 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.
Future Work
• Standardize social meta-data definition
• Support additional OSNs
• Recommendation System
• Release g-Social to Eclipse
29
29.
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
30