In recent years, climate change, depletion of natural resources, and rising energy costs have led to an increased emphasis on sustainability. A widely accepted definition of sustainability, attributed to the Brundtland Commission of the United Nations, states that sustainable development is that which meets the needs of the present without compromising the ability of future generations to meet their own needs. In practice, a common heuristic for making technological systems environmentally sustainable is to make them eco-efficient, i.e., build using the least amount of the most appropriate materials and consuming the least amount of the most appropriate sources of energy throughout their lifetime. Sustainability is a difficult goal to achieve, because the systems under consideration comprise complex, inter-connected entities about whom first principles modeling is intractable. Therefore data-driven methods hold significant promise.

The goals of this KDD workshop are to:

• to bring together researchers working on applications of KDD to sustainability in diverse areas, especially in infrastructures such as IT, Smart Grids, water, and transportation. This will facilitate cross-disciplinary collaboration and cross pollination of ideas across domains.
• to familiarize the mainstream KDD community with diverse application areas within sustainability.
• to serve as a meeting ground and launchpad to galvanize and foster the development of this budding subcommunity.

• Naren Ramakrishnan, Virginia Tech (co-chair)
  
• Manish Marwah, HP Labs (co-chair)
  
• Amip Shah, HP Labs
• Jiawei Han, UIUC
• Carla Gomes, Cornell
• Hamsa Balakrishnan, MIT
• Hillol Kargupta, UMBC
• Katharina Morik, TU Dortmund
• Vipin Kumar, University of Minnesota
• Ratnesh Sharma, NEC Labs
• Andreas Krause, Caltech
• Mario Berges, CMU
• Karsten Schwan, Georgia Tech
• Martin Arlitt, HP Labs