Introduction to data mining for sustainability

can bedefined as “capacity to endure the needs of today’s population without jeopardizingthe ability of the future generations to meet their own needs”. Sustainability impliesresourceconsumptionwithlittleinternalorexternaladverseimpact.Asystemorapro-cessissustainableifitsinputandoutputhavelittleadverseimpactonitsenvironment.A system that is not sustainable often leads to the failure (sometimes catastrophic) ofthe system itself or other systems in its environment. For example, a banking systemissustainablewhenitsfinancialtransactionsleadtolittleornoadverseeffectonitselfor other economic entities it interacts with. A domestic article such as a light bulb issustainable when its production and operation are reliable and result in little adverseimpact on its environment. For humans, sustainability has long term effects on threeimportant sectors: environmental, economic, and social. Earth system science pleadsfor global sustainability. The goal is to deliver the knowledge which allows to reduce

[1]  Peter Marwedel,et al.  Assigning program and data objects to scratchpad for energy reduction , 2002, Proceedings 2002 Design, Automation and Test in Europe Conference and Exhibition.

[2]  Kanishka Bhaduri,et al.  Distributed Anomaly Detection using Satellite Data From Multiple Modalitie , 2010, CIDU.

[3]  Heidrun Schumann,et al.  Space, time and visual analytics , 2010, Int. J. Geogr. Inf. Sci..

[4]  Vipin Kumar,et al.  Land cover change detection: a case study , 2008, KDD.

[5]  Sridhar Ramaswamy,et al.  Efficient algorithms for mining outliers from large data sets , 2000, SIGMOD '00.

[6]  D. Tilman,et al.  Productivity and sustainability influenced by biodiversity in grassland ecosystems , 1996, Nature.

[7]  Saso Dzeroski,et al.  Computational Discovery of Scientific Knowledge , 2007, Computational Discovery of Scientific Knowledge.

[8]  Kirk Martinez,et al.  Environmental Sensor Networks: A revolution in the earth system science? , 2006 .

[9]  Katharina Morik,et al.  Local Pattern Detection, International Seminar, Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers , 2005, Local Pattern Detection.

[10]  Wayne M. Getz,et al.  Duelling timescales of host movement and disease recovery determine invasion of disease in structured populations: Duelling timescales of host movement and disease recovery , 2005 .

[11]  Michael May,et al.  Ubiquitous Knowledge Discovery , 2010, Lecture Notes in Computer Science.

[12]  Thomas Bartz-Beielstein,et al.  Comparing SPO-tuned GP and NARX prediction models for stormwater tank fill level prediction , 2010, IEEE Congress on Evolutionary Computation.

[13]  Lorenza Saitta,et al.  Ubiquitous knowledge discovery: challenges, techniques, applications , 2010 .

[14]  R. Ferraro,et al.  Modeling the Earth system. Critical computational technologies that enable us to predict our planet's future , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[15]  Gerhard Fettweis,et al.  Low-energy DSP code generation using a genetic algorithm , 2001, Proceedings 2001 IEEE International Conference on Computer Design: VLSI in Computers and Processors. ICCD 2001.

[16]  David J. Diner,et al.  A data-mining approach to associating MISR smoke plume heights with MODIS fire measurements , 2007 .

[17]  Christian Bauckhage,et al.  Descriptive matrix factorization for sustainability Adopting the principle of opposites , 2011, Data Mining and Knowledge Discovery.

[18]  B. Ekasingh,et al.  A data mining approach to simulating farmers' crop choices for integrated water resources management. , 2005, Journal of environmental management.

[19]  Karsten Steinhaeuser,et al.  Data Mining for Climate Change and Impacts , 2008, 2008 IEEE International Conference on Data Mining Workshops.

[20]  Cecelia DeLuca,et al.  Modeling The Earth System , 2003 .

[21]  David Dreyer Lassen.  Predicting Land Temperature Using Ocean Data , 2004 .

[22]  Srinivasan Parthasarathy,et al.  Anomaly detection and spatio-temporal analysis of global climate system , 2009, SensorKDD '09.

[23]  Jean-François Boulicaut,et al.  Local Pattern Detection , 2008 .

[24]  Bernhard Schölkopf,et al.  Estimating the Support of a High-Dimensional Distribution , 2001, Neural Computation.

[25]  Pang-Ning Tan,et al.  Mining Scientific Data: Discovery of Patterns in the Global Climate System , 2001 .

[26]  João Gama,et al.  Ubiquitous Knowledge Discovery , 2011, IDA 2011.

[27]  Rahul Ramachandran,et al.  Real-time storm detection and weather forecast activation through data mining and events processing , 2008, Earth Sci. Informatics.

[28]  V. Blanke,et al.  The Power of Regeneration: Lessons from a Degraded Grassland , 2007 .

[29]  Vipin Kumar,et al.  Discovery of climate indices using clustering , 2003, KDD '03.

[30]  Thomas G. Dietterich.  Machine Learning in Ecosystem Informatics , 2007, Discovery Science.

[31]  Hillol Kargupta,et al.  MineFleet®: an overview of a widely adopted distributed vehicle performance data mining system , 2010, KDD.

[32]  VARUN CHANDOLA,et al.  Anomaly detection: A survey , 2009, CSUR.

[33]  Johannes Fürnkranz,et al.  Guest Editorial: Global modeling using local patterns , 2010, Data Mining and Knowledge Discovery.

[34]  Gennady L. Andrienko,et al.  Interactive cluster analysis of diverse types of spatiotemporal data , 2010, SKDD.

[35]  Stephen D. Bay,et al.  Mining distance-based outliers in near linear time with randomization and a simple pruning rule , 2003, KDD '03.

[36]  Pat Langley,et al.  Discovering Communicable Models from Earth Science Data , 2007, Computational Discovery of Scientific Knowledge.

[37]  Olaf Spinczyk,et al.  Towards Adjusting Mobile Devices to User's Behaviour , 2010, LWA.

[38]  Ashok N. Srivastava.  Greener aviation with virtual sensors: a case study , 2011, Data Mining and Knowledge Discovery.

[39]  Bernard Zenko,et al.  Estimating the risk of fire outbreaks in the natural environment , 2012, Data Mining and Knowledge Discovery.

[40]  Manish Marwah,et al.  Data analysis, visualization and knowledge discovery in sustainable data centers , 2009, COMPUTE '09.