Chance Discovery is the discovery of chance, rather than discovery by chance. A ``chance" here means a new event/situation that can be conceived either as an opportunity or as a risk in the future. The ``discovery" of chances is of crucial importance since it may have a significant impact on human decision making. Desirable effects of opportunities should be actively promoted, whereas preventive measures should be taken in the case of discovered risks. In other words, chance discovery aims to provide means for inventing or surviving the future, rather than simply predicting the future.

This session will discuss several problems in Chance Discovery. As shown, Chance Discovery is a research to study how to discover rare or novel events causing potentially significant situation. Although the event itself could not be significant. A chance might be computationally or manually discovered. Thus, advanced computational techniques such as abduction and induction (including data mining) could be applied to Chance Discovery. In addition, personalised and very traditional (sometimes, manual) data mining method could also be effective in Chance Discovery. We have discussed limitations of conventional data mining methods. And many new computational methods, and concepts and mechanisms of human discovery have been proposed. In the contexts, we have discussed how to discover and suggest events causing significant but hidden events. Our common understandings are that we deal with events in the real world, therefore, we need to have knowledge about movement in society, behaviour of people, as well as computational methods. In addition, it is important to discuss effective chance evaluation, selection, and suggestion methods. It would be a gate for fantastic and innovative applications.
Thus, we would like to discuss from logical, computational, cognitive, sociological, economical and psychological viewpoints. In addition, we would like to discuss ``curation'' of chance. Traditionally, curation is not only concerned with long-term care of books, paintings or other artefacts. It is also about maintaining their integrity and enabling and promoting their availability to appropriate audiences (http://www.jisc.ac.uk/e-sciencecurationreport.pdf). In addition, ``curation'' has recently focused on even in the marketing field. As shown above, for chance discovery, we have focused on strategies to discover rare or novel events and those to present hints of chance to users. By curation, we add a more active action to chance discovery, which curators usually struggle to explicitly or implicitly express extended or hidden meanings (values) to potential audiences. It should be related to ``value sensing'' in chance discovery. And, it should be related to ``chance sysnthesis.''
In addition, we would like to discuss how to create and design the market where data are reasonably dealt with, i.e., sold, opened free, or shared after negotiation. Our ultimate goal is to have each people on the earth feel free to share one's own data with others without fearing of the loss of business opportunities.
In order to make a social environment where analysts and decision makers in active businesses and sciences can be provided with data they need, in this workshop we also aim to (re)design an environment called the Market of Data, where each user or provider of data can understand the value of each part of data so that one can buy/sell it for a reasonable price. Here, the value of each part of data shall be visualized to aid users' considering its possible contribution to promoting/creating businesses and scientific findings.
Of course, other viewpoints are also welcome!

Topics to be discussed (will not be restricted to):

• Analysis of human behaviour.
• Analysis of complex systems (society, community etc.).
• Applications of Chance Discovery.
• Innovations as Chance Discovery.
• Value sensing in Chance Discovery.
• Chance synthesis
• Characterization of ``Chance.''
• Logical foundations for Chance Discovery.
• Theories and methodologies to discover rare or novel events.
• Theories and methodologies to foretell next trends.
• Theories and methodologies to make aware of significant events.
• Theories and methodologies for an evaluation and selection of chance.
• Models and methodologies for effective suggestion of chance.
• Relationship between computational and manual methods.
• Integration of computational and manual methods.
• Curation of chance
• Knowledge representation
• Methods for creative communication and argumentation
• Data/Text mining and visualization

Submission:

• no changes may be made to the Procedia template and the instructions must be followed exactly
• the maximum length of 10 pages must not be exceeded
• the paper must be presented at the conference

Your papers can be submitted to (both):

• KES submission system (PROSE):
  
  http://www.kes2014is.prosemanager.com/login.asp
  Please select IS06: Chance Discovery and Market of Data

  Akinori Abe (Chiba University)

  ave@ultimaVI.arc.net.my

Important Dates:

• 30 April, 2014: Submission deadline of papers (extended!!)
• 2x May, 2014: Notification of acceptance of papers.
  
• 1 June, 2014: Deadline for camera-ready papers (via PROSE)
  attention!! Hard deadline - will not be extended
  
• 16 June, 2014: Early Registratoin Deadline
  Every paper must have at least one author who has registered for the conference with payment by the Early Registration Deadline for the paper to appear in the proceedings.
• 15, 16 & 17 September 2014: Session