1. Integrated Collaborative Information Systems
Thesis Proposal
Ahmet E. Topcu

2. Outline
Introduction
Motivation
Research Issues
Architecture

3. Introduction
Efforts for collaboration and sharing between users and communities.
Grid
Virtual Organizations
Sakai
Collaboration and Learning Environment for Education
Web 2.0
Represents new web-based services.
Provides rich and lightweight online tools
Provides reusable services and data
Updates software and data often very rapidly
Provides interactive user interfaces
Provides an architecture for easy user contribution
The Web and all its connected devices as one global platform of reusable services and data
Continuous and seamless update of software and data, often very rapidly
Development of tools and services aimed at fostering
online collaboration and sharing between users and communities.
Non web 2.0 there are learning management systems
There

4. Web 2.0 Examples Blogs (blogger.com, GoogleBlog)
Wikis(Wikipedia, WikiWikiWeb)
Social Networking Tools(MySpace ,LinkedIn)
Social Bookmarking Tools(del.icio.us ,YouTube)
Domain of scientific research (CiteULike , Connotea , and Bibsonomy)
Domain specific academic search tools(CiteSeer, Google Scholar, Windows Live Academic)

8. Motivation Need for exploiting large set of data sources
Google Scholar (GS), Windows Live Academic (WLA) may have different scope
Utilizing best capabilities of the tools
GS has number of cited publications.
WLA has Digital Object Identifier (DOI)

10. Motivation Integration Completeness Necessities for integration
Need for common data format
Completeness
No easy way to find all publications
Example: A search in Google Scholar for the publications of our research lab (Community Grids Lab) will return only about 20% of the total GS search content.
Wealth of information contained in numerous field remains largely outside the scope of tools
Currently there is no fast and reliable way to collect and analyze all the papers of a research group.
No easy way to find all publications that focus on a very narrow topic.
Wealth of information contained in numerous field remains largely outside the scope of automated tools for scholarly research.
Collection
Fast and reliable way to collect data.
Requirements for new features
Sum of the features not finished

11. Here is what we have done
In this arch we found these issues
I will briefly talk about this

12. Research Issues Integration Performance Flexibility and Extensibility
A model to integrate community tools.
A model to collect related documents of data naturally
Performance
The cost of integration of the systems
Overhead for extracting information and uploading them to the tools
Flexibility and Extensibility
Easy to add and remove service mechanism
Easy to integrate and collaborate services or gadgets
Support for scientific research which links both traditional simulations and observational analysis to the data of existing scientific documents
A model for a natural collection of related documents such as those of a research group or those of a conference.
An architecture for integration of information systems
A model for integration of community tools.
Support for scientific research.
A model for a natural collection of related documents
Service oriented base approach
Existing community systems consists of mechanism to collect information.
Features can be either be exchanged between “mass services and manipulated with separate interface.
WSDL compatible information services for Digital Entity (DE)
We will investigate

13. Architecture Principles
Community-centric platform of services
Integration of dynamic publication, search tools into Cyberinfrastructure based scholarly research.
Integration such scientific research defining metadata and using various url, and map them.
Services that aggregate information from a variety of sources (i.e., “mash-up” tools) and provide added value to communities of researchers
Do not build a new tool. Reuse the tools.
Easier to link together all relating information common Digital Entity (DE)
Mash-up: A Web page or application that integrates complementary elements from two or more sources.
This highlights of proposed architecture

17. Summary: Architecture
Build integration architecture
We do not reinvent existing tools
Use existing features of tools
Supports microformats and universal tagging services
Provides common metadata
Allows to use consistent data
Provides common resolution of filters

18. Usage of Integration Model
We have used/tested Semantic Research Grid (SRG) (a prototype model) for published scientific research publications in Community Grids Lab in which has 20 students ,and post-docs and faculty members works.

19. Security Model
Security in web 2.0 is inadequate. Provide security for inconsistent/in existed security model in web 2.0 domain.
There exists a number of security methods:
Access control matrix (ACL)
Transport Layer Security (TLS)
Role-based access control (RBAC)
Task-based access control (TBCA)
We used an access-control matrix model to provide security for our information system
Supports multiple groups and multiple users for each object.
Similar to UNIX file system
The Unix RWX bits corresponds to Read, Write, and Execute operation for each file and directory.
In proposed system, DE (Digital Entity) correspond to the file element and folder corresponds to the directory element.
For each DE and folder, there are three types of access rights defined in the systems: Read, Write, and Delete.
Such as the access control matrix, the role-based access control (RBAC), and the task-based access control (TBCA)
have been used in existing collaborative systems.
Access Rights:
The owner of DO and database can specify the DO and database permissions for group and other users.

20. Security Model II We have a security model that supports
Level of Authorization
Roles are defined as Super Administrator (SA) and Group Administrator (GA), User (U)
The system allows having more than one SA.
An existing SA can add other SAs to the system.
SA can assign any U to become GA, and remove GA from group.
Each group should at least one GA. GA add/remove U from group
User profile
Share user profile between sites.

21. Contribution Performance Flexibility and Extensibility Integration
We have successfully integrated Google Scholar and Windows Live Academic search tools and CiteUlike, Delicious annotation tools which provide a system that allow dynamic publication.
We will integrate CiteeSeer search tools to investigate our proposed architecture.
Performance
We will investigate the cost of integration of the new tools into the systems
Overhead for extracting information and uploading them to the tools
Flexibility and Extensibility
We provides flexibility allowing integration of different tools having common metadata.
Easy to add and extend service mechanism
Do COLLAbaroation aggregation
We have done partial integration part

22. End
Thanks!

23. Applications I : Search Tools
They have two main roles in the usage scenarios of our system:
They will be used to seed the creation of a community (e.g., the papers of a research group, the papers on a chemical compound, etc.).
These seeds will then be expanded and refined by our community-building tools and linked with the annotation tools. They will be used to extract the citation count of scientific papers.
Resim visualize
Significant developments in the areas of digital libraries and academic search (CiteSeer, Google Scholar (GS), Windows Live Academic (WLA)
CiteSeer was introduced in 1997 by Giles.
As the first tool in this category, CiteSeer is probably also the best known, especially in the field of Computer Science, which is its specialization domain.
The core feature of CiteSeer is Automated Citation Indexing,
a method for the automated extraction.
parsing and indexing of the citations contained in a paper and of the context of these citations in the paper’s body.
CiteSeer has pioneered a number of techniques for the automated extraction of document metadata, including front-end metadata such as title, author names, etc.

24. Applications II : Search Tools
Extract information from Search Domain.
Example: Using heuristic method for Google Scholar.
Extract Metadata to build DEs having search key.
This model can be used for various search tools
Collect metadata for scholarly published papers.
Build communities implied by the co-authors of papers.
Search DEs through populated metadata
information extraction tecniques