-------- Original-Nachricht -------- Betreff: [isworld] Final Call for Papers: Special Issue on Collective Intelligence - Journal of Information Sciences - Elsevier Publisher Datum: Wed, 03 Sep 2008 17:15:54 +0100 Von: Epaminondas Kapetanios E.Kapetanios@westminster.ac.uk Antwort an: Epaminondas Kapetanios E.Kapetanios@westminster.ac.uk An: AISWORLD Information Systems World Network isworld@lyris.isworld.org
Special Issue on Collective Intelligence ----------------------------------------
Submission site is now open: http://ees.elsevier.com/ins
Journal of Information Sciences, Elsevier Publisher
Impact factor of this journal: 2007: 2.147, Journal Citation Reports 2008, published by Thomson Reuters
Important Note: ---------------
Select 'Special Issue: Collective Intelligence' as Article Type during submission of the paper
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GUEST EDITORS:
Dr. Epaminondas Kapetanios, University of Westminster, London, UK Dr. Georgia Koutrika, Stanford University, USA
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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
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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.
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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.
* How do we plug-in personal data and knowledge into a problem solving social network?
* How do we create systems to enable collaboration?
* How do we guarantee communication at different levels of expertise and cultural and multi-lingual backgrounds?
* How do we guarantee communication between experts and end users in their role as members of a particular society and participants in problem-solving strategies and techniques?
* How do we harness the inherent complexity of networked solutions?
* How can we create cooperating systems in a cost-effective way?
* How can we integrate systems in a meaningful way without sacrificing autonomy?
* How can we bring together diverse conceptions and interpretations of user communities?
* How do we cope with uncertainty and probability in data management and knowledge discovery?
* What are the mechanisms to support group formation multiple interpretive perspectives, negotiation of group knowledge
* What are the technological and social reconfigurations that are needed to achieve computer supported collaborative knowledge building, i.e., group cognition, that transcends the limits of individual cognition
* How do we design and offer software, which analyzes and relies on empirical instances of collaboration?
* How do we ensure that quality in knowledge and software creation and consumption is assured?
* How can we ensure security and trustworthiness in networked environments?
* How do we enable learning via computer games and multimedia enhanced knowledge sources?
* How do we make sure which inference and reasoning techniques are applied to available data? Does reasoning and available data match?
APPLICATIONS:
Applications as varied as collaborative curriculum development, writing summaries by students and designing space voyages by NASA engineers can be addressed. A non-exhaustive list of application paradigms is the following:
* Collaborative Scientific Problem Solving * Maintaining Model Bases * Environmental Monitoring and Global Climate Change * Collaborative Business Models and the Enterprise 2.0 * Collaborative e-Learning * Social Networking Analysis * E-Governance * Collective Environment Monitoring Systems * etc.
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SUBMISSION GUIDELINES:
Manuscripts should be submitted on-line 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 http://www.elsevier.com/locate/ins.
A tutorial and guide for authors is also available on-line 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.