The case for standardised environmental data collection
A recent episode of the Data for the People! podcast draws on an XBRL US paper to make the case for standardising the way environmental agencies collect and report data. The episode exposes how fragmented environmental reporting requirements across federal and state regulators, involving data such as greenhouse gas emissions, results in reduced data quality and interpretation burdens for public agencies and the private sector.
The podcast paints a familiar but frustrating picture: similar information is reported in multiple formats to multiple bodies, hampering the public sector’s ability to use the data by making it harder to monitor trends or evaluate the effectiveness of environmental policy. Private organisations also pay a real cost in time and money on analysis of disparate data streams.
The argument for a common, structured approach is straightforward: consistent, machine-readable data would dramatically improve usability, comparability, and policy effectiveness. It’s encouraging to see these arguments being made explicitly in the environmental data space.
Listen to the episode here.
