Why closing the data divide is important for everyone
Regular readers of this newsletter will be familiar with our frequent call for more, better quality, comparable data – but sometimes it is worth taking a step back to consider why. In a world that increasingly relies on data, access to and use of that data can have far-reaching implications. However, access to and use of data is not always equal, and unequal access to and use of data can further entrench social and economic inequities. In a recent article, The Centre for Data Innovation, a US based think tank, advocates for policies that improve access to data, data quality, and data analytics.
A data-rich society brings benefits in a broad range of areas, from finance and government (identifying suspicious filings and informing fraud investigations) to the environment (monitoring glaciers) and health (stemming the spread of communicable diseases). However, policymakers must commit to closing the data divide to ensure everyone can receive these benefits.
The Centre for Data Innovation advocate for an array of policies to close the data divide – but two stood out. Firstly, data quality needs to be improved, to ensure accuracy, timeliness, precision, and representation. To get there, of course, requires strengthening data standardisation in both public and private organisations to make data more interoperable and useful.
The article also notes the need to enhance access to data – ensuring citizens and businesses can access data and put it to use. Key to this is data portability – which requires data to be made available in a standardised, machine-readable format. This gives data owners or users the ability to use their data as they want, or to share it with third parties for analysis. With XBRL-tagged business data, for example, users can export the data from financial reports into the software program or analytics tool of their choice.
Closing the data divide is essential for a fair society, where everyone has equal access to information that can increase transparency and lead to better decision-making. Policymakers and a wide range of public and private sector organisations should take action to improve data quality and access, which, of course, includes implementing machine-readable data standards like XBRL.
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