18-20 June 2014 @ at 6th International Conference on Intelligent Decision Technologies, Chania, Greece. http://idt-14.kesinternational.org
Submissions due: February 7, 2014
Notification of Acceptance: February 28, 2014 Upload of Final
Publication Files: March 10, 2014
Aim and Scope
Contemporary collaboration settings are often associated with huge, ever-increasing amounts of multiple types of data, which may vary in terms of relevance, subjectivity and importance, ranging from individual opinions to broadly accepted practices. In such settings, collective sense making is crucial for well-informed decision making. This sense making process may both utilize and provide input to intelligent information analysis tools.
This session aims to bring together researchers and practitioners from different scientific fields and research communities to exchange experiences and discuss the topic of how data-intensive and cognitively-complex sense making and decision making within diverse types of teams can be facilitated and augmented. The session will offer a venue for targeted discussion on the development and evaluation of innovative services that shift in focus from the mere collection and representation of large-scale information to its meaningful assessment, aggregation and utilization. Of particular interest are approaches that bring together the reasoning capabilities of the machine and the humans in contemporary collaborative settings.
In parallel, much interest is given to larger issues surrounding analytical practices and data sharing practices in the above settings.
Submissions are expected to cover a number of main themes (research issues), including:
- Innovative approaches to the exploration, delivery and visualization of the pertinent information.
- Novel collaboration tools and platforms for handling ill-defined domains.
- Collaborative sense making of real-world multi-faceted data.
- Novel mechanisms for understanding collaborative patterns and
- Advances in cloud computing and scalable high-performance data
mining for data-intensive collaboration.
Nikos Karacapilidis, University of Patras & CTI, Greece Lydia Lau,
University of Leeds, UK Pavlos Peppas, University of Patras, Greece