Big Policy Canvas Research Roadmap
[...] * This leads to a huge amount of data that can be used and are of an increased size and resolution, span across time series, and that they are not, in most cases, collected by means of direct elicitation of people. However, concerning data quality, a common issue is balance between random and systematic errors. Random errors in measurements are caused by unknown and unpredictable changes in the measurement. In that regard, the unification of data so as to be editable and available for policy making is of extreme importance: cancelling noise for instance is challenging.
Noise, random, and systematic errors must be transparent to policymakers.
cristian.lai, 12/09/2019 10:42