Collaborative Knowledge Discovery in Databases: A Knowledge Exchange Perspective

Claudia Diamantini, Domenico Potena, Waleed W. Smari

In a Knowledge Discovery in Databases (KDD) process, human capabilities and judgment are still a fundamental ingredient to ensure that useful and valid knowledge is derived from data. Such capabilities assume the form of skills and expertise in different domains such as databases, statistics, machine learning, data mining, as well as the specific business/application domain. Thus, in order to manage a knowledge discovery project, a team of different experts is worth being constituted. In this paper we analyze the Collaborative Knowledge Discovery in Databases environment in terms of the different information team workers need to exchange to collaborate, surveying the main existing technologies for information representation and exchange, and enlightening possible directions of future work. Furthermore, we propose an open environment supporting users in the management of specific KDD information and activities.

Subjects: 12. Machine Learning and Discovery; 11. Knowledge Representation


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