Informed energy decision making requires effective software, high-quality input data, and a suitably trained user community. Developing these resources can be expensive and time consuming. Even when data and tools are intended for public re-use they often come with technical, legal, economic and social barriers that make them difficult to adopt, adapt and combine for use in new contexts.
We focus on the promise of open, publically accessible software and data as well as crowdsourcing techniques to develop robust energy analysis tools that can deliver crucial, policy-relevant insight, particularly in developing countries, where planning resources are highly constrained – and the need to adapt these resources and methods to the local context is high. We survey existing research, which argues that these techniques can produce high-quality results, and also explore the potential role that linked, open data can play in both supporting the modelling process and in enhancing public engagement with energy issues.
Morgan Bazilian (a,b), Andrew Rice (c), Juliana Rotich (d), Mark Howells (e), Joseph DeCarolis (f), Stuart Macmillan (g,h), Cameron Brooks (i), Florian Bauer (j), and Michael Liebreich (k).
(a) United Nations Industrial Development Organisation, Vienna, Austria
(b) International Institute for Applied Systems Analysis, Laxenburg, Austria
(c) Computer Laboratory, University of Cambridge, Cambridge, UK
(d) Ushahidi, Nairobi, Kenya
(e) Royal Swedish Institute of Technology, Stockholm, Sweden
(f) North Carolina State University, North Carolina, USA
(g) Stanford University, California, USA
(h) National Renewable Energy Laboratory, Colorado, USA
(i) Tendril Networks, Colorado, USA
(j) Renewable Energy and Energy Efficiency Partnership, Vienna, Austria
(k) Bloomberg New Energy Finance, London, UK
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