[Conference:] Proceedings of the NSF Workshops on Big Data and Urban Informatics, University of Illinois at Chicago, Chicago, IL, August 11-12, 2014
This paper re-conceptualizes the planning process in the big data era based on the improvements that non-linear modeling approaches provide over the mainstream linear approaches. First, it demonstrates challenges of conventional linear methodologies in modeling complexities of residential energy use, addressing the “variety” from the three Vs of big data. Suggesting a non-linear modeling schema to analyze household energy use, the paper develops its discussion around the repercussions of the use of non-linear modeling in energy policy and planning. Planners / policy-makers are not often equipped with the tools needed to translate complex scientific outcomes into policies. To fill this gap, this work proposes modifications in the traditional planning process in order to be able to benefit from the abundance of data and the advances in analytical methodologies. The conclusion section introduces three short-term repercussions of this work for energy policy (and planning, in general) in the big data era: tool development, data infrastructures, and planning education.
Energy Policy Residential Buildings Non-Linear Modeling Big Data Planning Process