INS Special Issue on Collective Intelligence

Guest Editors

 * Dr. has guest editor::Epaminondas Kapetanios, University of Westminster, London, UK
 * Dr. has guest editor::Georgia Koutrika, Stanford University, USA

Important Dates

 * Submission of Abstracts to Guest Editors (optional): August 15, 2008
 * Initial Submission: October 1, 2008
 * First Round Reviews: January 15, 2009
 * Resubmission by: March 15, 2009
 * Final Acceptance: May 15, 2009
 * Publication: Second half 2009

with pre-publication via www.sciencedirect.com

Background
Since the first formal specifications of modern computing machinery as laid out by Alan Turing and his contemporary fellows, we have been witnessing, during the last three decades, an evolutionary path in computing towards more personalized and contextualized data and knowledge artefacts.

The optimal usage of distributed computing, data and knowledge resources has always been the means in order to tackle hard problems in fields, such as science, engineering and medicine. The SETI (Search for Extra-Terrestrial Intelligence, Berkeley, USA) project is one prominent example in this category followed by the Human Genome project. It is no surprise that projects like e-Science, as recently launched by the UK government, and the GRID computing are meant to create a computing paradigm, where "the computer is the network". In all these approaches, however, the problem seems to be well defined and no synergies across participants from different cultural and professional backgrounds are requested in order to create a solution.

In the early 21st century with the rise of the Social and Semantic Web, however, the answer of "what is a network" has been relaxed by the inclusion of users and user communities, which form social networks via computerized means. Ecosystems of humans and machines have been created where the involvement of human beings as creators and consumers of data and knowledge as well as in problem solving and learning tasks has been of paramount importance. Clusters of computers have been enhanced by clusters of humans. Formation of social groups follows the same principles of social behaviour, common interests, e.g., studies, hobbies, games. Wikipedia has been a success story of a collaborative environment for knowledge creation and sharing. Facebook, MySpace, del.icio.us, Flickr have been further success stories of social networking with digital media.

This special issue explores the notion of this human-machine model of Collective Intelligence (CI) and its potential to become a new computing paradigm for creating solutions or strategies to tackle difficult problems, where the synergistic interactions of a group of people with diverse cultural and professional backgrounds are requested. This issue aims at studying the move from (system-) collected knowledge and intelligence, to collective knowledge and intelligence and exploring the challenge of boosting the collective IQ of organizations and society where both human and machine contribute actively to the resulting intelligence with each doing best what they do best.

Software Engineering contributions sought
This is by no means an exhaustive list of challenges and research questions to be addressed by the submitted papers for all elements of the best research practice as based on the triple theory, methodology, model - languages - system  implementation.

In particular, contributions in terms of one or more of the following Software Engineering aspects are welcome:

systems supporting Collective Intelligence in terms of group formation, multiple interpretative perspectives, negotiation of group knowledge, etc.
 * Software engineering principles and methodologies addressing the construction of


 * Principles and methodologies for collaborative software design and development

computer supported collaborative software engineering
 * Technological and social reconfigurations that are needed to achieve

instances of collaboration
 * Design patterns and offer of software, which analyzes and relies on empirical


 * Quality assurance in collective software creation and consumption


 * Software metrics for collaborative systems

Submission Guidelines
Optional abstracts to gauge the appropriateness of a research idea for further development for the special issue are welcome, and should be submitted to the Guest Editors via E.Kapetanios@westminster.ac.uk and koutrika@stanford.edu.

Manuscripts should be submitted online at http://ees.elsevier.com/ins/ by the date of initial submission, double spaced in 11 or 12-point fonts,  with no more than 45 pages, inclusive of all references, figures and tables. Submitted manuscripts will be reviewed according to the peer review policy of the Information Sciences Journal as available on-line at www.elsevier.com/locate/ins.

A tutorial and guide for authors is also available online at http://ees.elsevier.com/ins/ Please make sure that you register yourself prior to submitting your paper.

As papers are uploaded, authors should make sure to select the correct special issue (select "Special Issue: Collective Intelligence" when reaching the Article Type step). Only original and unpublished papers will be considered.

The special issue will finally comprise 9 single line spacing papers of 25 pages each.