Special Issue on Environmental Data Mining
Karina Gibert · AI Communications · 2016
Data Mining is the discipline for non trivial identifying of valid, novel, potentially useful, ultimately understandable patterns in data [3] and provides the opportunity to extract relevant decisional knowledge from data bases in any application field.In particular it can contribute to a better understanding of Environmental Sciences.Environmental Sciences is a wide research field with a number of open problems that require attention.The technological development occurred in the last years has significantly increased the availability of environmental data to be exploited for better addressing current challenges in the area.My interest in data mining comes from the 90s, when I was a PhD student.From then, part of my research activity has been focused on disseminating data mining in different areas of application, as well as to contribute to these areas by applying data mining to some challenging real problems.Among other activities, I'm the chair of the Data Mining Techniques for Environmental Sciences (DMTES) workshop, which we organize every two years in the frame of the Environmental Modelling and Software Society biannual meetings.The DMTES series started in 2002, with the aim of becoming a multidisciplinar discussion forum for the Data Mining and Environmental Sciences communities.From then onwards, every two years the DMTES has been celebrated all along the world (Vermont (USA), Barcelona (Spain), Otawa (Canada), Leizig (Germany), San Diego (USA), Toulouse (France)), providing a valuable opportunity for a close contact between the data mining community and the Environmental Sciences community, and discussions arising in the workshop raise current challenges in both areas and synergic opportunities.From these meetings and other collaborations in environ-