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Models can be a powerful instrument to guide environmental decision making. Data inter-operability can lower the costs and time involved in constructing multi-dimensional models of air pollution, soil erosion or deforestation. By focusing on establishing computing interfaces vast amounts of existing data can be organized and repetitive tasks in modelling can be minimized to support learning about the incentives for climate action that examine the trade-offs between sustainability, individual profit maximization and community based collective action.
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