What will the new Public Data Transparency Principles mean for researchers and HEIs?
1 July, 2010 | in Blogs
By: Angus Whyte
The new Government's Public Sector Transparency Board met last week for the first time and promptly published a draft set of Public Data Principles on the data.gov.uk team blog. So what does this mean for research data and HEI's?
The principles are far-reaching and challenge public sector bodies to deliver far more than they already do under Freedom of Information legislation. The draft defines public data as " the objective, factual, non-personal data on which public services run and are assessed, and on which policy decisions are based, or which is collected or generated in the course of public service delivery."
In their current form - some commentors have pointed out that the consultation process has not been spelled out in much detail so far - the principles demand that provision will be driven by (I paraphrase) user needs and a legal 'right to data'. They also say that open licences must apply, everything must be in machine-readable and standards-compliant form, available through the data.gov.uk portal, and without delay. Echoing FOI, public bodies are called on to "maintain and publish inventories of their data holdings".
The question posed in the header was 'what does this mean for research and HEI's?' There seems no reason to doubt the principles will apply to HEIs and much of the data they gather for administrative purposes. And research data? Clearly there are some fields, public health for example, where the 'data behind the graph' can be seen as the evidence-base for policy making. The same might apply in other fields that aim for 'evidence-based policy', especially as academics are called on by funders to demonstrate the relevance of their work to policy-makers and other would-be beneficiaries. Do the principles apply here, or even more widely to any publicly-funded research that produces 'non-personal' data, or should there be FOI-style exemptions? An interesting space to watch, with resourcing implications for data curation at the very least!
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