Abstract
Both data mining and decision support are branches of applied problem solving. Both fields are not simply about technology, but are processes that require highly skilled humans. As with any knowledge intensive enterprise, collaboration — be it local or remote — offers the potential of improved results by harnessing dispersed expertise and enabling knowledge sharing and learning. This was precisely the objective of the SolEuNet Project — to solve problems utilizing teams of geographically dispersed experts. Unfortunately, organizations find that realizing the potential of remote e-collaboration is not an easy process. To assist in the understanding of difficulties in e-collaborative enterprises, a model of the e-collaboration space is reviewed. The SolEuNet Remote Data Mining Virtual Organization and its implemented methodology — a key factor for success — is analyzed with respect to the e-collaboration space model. The case studies of three instances of using the Remote Data Mining Virtual Organization are presented.
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Moyle, S., McKenzie, J., Jorge, A. (2003). Collaboration in a Data Mining Virtual Organization. In: Mladenić, D., Lavrač, N., Bohanec, M., Moyle, S. (eds) Data Mining and Decision Support. The Springer International Series in Engineering and Computer Science, vol 745. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0286-9_5
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DOI: https://doi.org/10.1007/978-1-4615-0286-9_5
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