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CALL FOR BOOK CHAPTERS (Springer)
Chapter Proposals Submission Deadline: 28/02/2010
Full Chapters Due: 15/07/2010
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NEXT GENERATION DATA TECHNOLOGIES FOR COLLECTIVE COMPUTATIONAL INTELLIGENCE
A book edited by:
Dr Nik Bessis, University of Bedfordshire, United Kingdom
Dr Fatos Xhafa, University of London (Birkbeck), United Kingdom
To be published in the Studies in Computational Intelligence book series, Springer (2011)
http://www.beds.ac.uk/departments/computing/staff/nik-bessis/cfc_cgi
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Introduction
The use of collaborative decision and management support systems has evolved over the years through developments in distributed computational science in a manner, which provides applicable intelligence in decision-making. The rapid developments in networking and resource integration domains have resulted in the emergence and in some instances to the maturation of distributed and collaborative paradigms such as Web Services, P2P, Grid and Cloud computing, Data Mashups and Web 2.0. Recent implementations in these areas demonstrate the applicability of the aforementioned next generation technologies in a manner, which seems the panacea for solving very complex problems and grand challenges. A broad range of issues are currently being addressed; however, most of these developments are focused on developing the platforms and the communication and networking infrastructures for solving these very complex problems, which in most instances are well-known challenges. The enabling nature of these technologies allows us to visualize their collaborative and synergetic use in a less conventional manner which are currently problem focused.

The Overall Objective of the Book
In this book, the focus is on the viewpoints of the organizational setting as well as on the user communities, which those organizations cater to. The book appreciates that in many real-world situations an understanding using computational techniques of the organization and the user community needs is a computational intelligence itself. Specifically, current Web and Web 2.0 implementations and future manifestations will store and continuously produce a vast amount of distributed data, which if combined and analyzed through a collective and computational intelligence manner using next generation data technologies will make a difference in the organizational settings and their user communities. Thus, the focus of this book is about the methods and technologies which bring various next generation data technologies together to capture, integrate, analyze, mine, annotate and visualize distributed data made available from various community users ? in a meaningful and collaborative for the organization manner.

In brief, the overall objective of this book is to encapsulate works incorporating various next generation distributed and other emergent collaborative data technologies for collective and computational intelligence, which are also applicable in various organizational settings. Thus, the book aims to cover in a comprehensive manner the combinatorial effort of utilizing and integrating various next generation collaborative and distributed data technologies for computational intelligence in various scenarios. The book also distinguishes itself by focusing on assessing whether utilization and integration of next generation data technologies can assist in the identification of new opportunities, which may also be strategically fit for purpose.

Topics:
Chapters should be written in a manner readable for both specialists and non-specialists. Chapters could address issues related to past, present and future collective computation intelligence methods, theories and practices. These should be focused on next generation paradigms and with a particular focus (but not limited) to Data Stream, Click stream, Distributed Data Capture, Data Architecture, Data Integration, Data Push, Data Grids, Distributed Data Analysis and Modeling, Distributed Data Resource Discovery, Allocation and Management, Distributed Data/Text Mining, Data Annotation, Data Clustering, Partitioning, Cloud Computing, P2P, Data Next Generation Visualization, Data Mashups, Web 2.0, Decision Making, Data Knowledge Management, Data Scheduling, Data Query Systems and Languages.
Recommended topic areas include, but are not limited to:
* Critical Reviews on:
o Theory and Strategies Fundamentals in Collective Computational Intelligence
o Next Generation Technologies for Collective Computational Intelligence
* Theory and Strategies Fundamentals in Collective Computational Intelligence
o Social and Virtual User Communities/Organizational Structures and Dynamics
o Ad-Hoc Social Networking Analysis, Collective Behavior, Marketing, Advertising, Productivity
o Artificial Intelligence, Classifier, Self-adaptive Ant Colony, Swarm and Evolutionary Agents
o Data/Text Mining, Data Clustering, Graph Partitioning, Collaborative Decision Making
o Multi-objective Optimization Techniques in Fluid, Dynamic Distributed Environments
* Next Generation Technologies for Collective Computational Intelligence
o Groupware, Social Networks (Web 2.0) for Cooperative and Collaborative Endeavors
o Ad-Hoc Networks, Ontology Management, Semantic Web, Web Services, Multi-Agents
o Meta-Data, Annotation, Intra-/Inter Tagging, Inference Engines, Reasoning
o Architectures, Discovery, Retrieval, Scheduling, Allocation, Monitoring
o Enabling Distributed and Collaborative Technologies (Grids, P2P, Cloud, Mashups, etc)
o Data Management, Data Growth, Storage, Implications
o Security, Privacy, Trust and Reputation Management
* Applications of Next Generation Technologies for Collective Computational Intelligence
o Languages, Components, Programs, Knowledge Portals and/or Applications
o User Community/Organizational Needs Response Developments in various settings including (but not limited to) space missions, transportation and other control systems, sensors, smart homes, disaster management, threat detection, bioinformatics, environmental control and climate change, resource and energy consumption control, business, economics, supply-chain management, planning and operations, media, advertising, marketing, etc
o Performance, Scalability, Robustness, Verification, Validation, Benchmarking
* Future Concepts and Theories for Collective Computational Intelligence
o Concepts and Frameworks of Applicable Future Theories, Technologies, Practices, Trends, Strategies for and Implications of Collective Computational Intelligence

Submission Information
Academics, researchers and practitioners are invited to submit by 28 February 2010, a 2-page manuscript proposal detailing the background, motivations and structure of their proposed chapter. Authors of accepted proposals will be notified by 15 March 2010 and will be given instructions and guidelines for chapter preparation. Full chapters are due on 15 July 2010 and should be of 8,000 words in length and/or between 25 to 30 pages long. All chapters will be reviewed on a double-blind basis. The book is scheduled to be published in the Studies in Computational Intelligence book series, Springer. For information about the publisher and the book series, visit http://www.springer.com/series/7092 . This publication is anticipated to be released in 2011.

Important Dates
28 February 2010: 2-page Proposal Submission Deadline
15 March 2010: Notification of Proposal Acceptance
15 July 2010: Full Chapter Submission (in Word or PDF)
31 August 2010: Notification of Full Chapter Acceptance
15 October 2010: Revised Chapter Submission
15 November 2010: Final Notification of Acceptance
30 November 2010: Final Material Submission

Inquiries and submissions can be forwarded electronically (in Word or PDF) to:
Dr Nik Bessis
University of Bedfordshire, United Kingdom
E-Mail: nik.bessis@beds.ac.uk
URL: http://www.beds.ac.uk/departments/computing/staff/nik-bessis
or
Dr Fatos Xhafa
University of London (Birkbeck), United Kingdom
E-Mail: fatos@lsi.upc.edu
URL: http://www.lsi.upc.edu/~fatos/
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