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Slicing the Public Pie: A primer on data representations & issues surrounding their use @HealthCanada

Data Ideology (AKA Service Standards)

A huge area in digital data concerns the approach taken in its creation and use. After validating methodology, analyzing perceptual aspects only touch on a specific dataset in a specific case for one user (i.e. the researcher) at one point in time. In order to move beyond snapshot use, the following needs to be outlined to other viewers of a representation of data (upon request):

source data is gathered in acceptable ways from reliable sources
whether or not the representation can be manipulated (in any ways for any purposes)
whether or not the data and/or representation will be stored
who will have access to the data and representation

Addressing these issues will identify service standards, which includes the selection of a data representation. An industry standard in this regard is the Information Technology Information Library (ITIL). While the basic aspects of ITIL are outlined in the white paper (cover on the right), in a nutshell, it is a data service management cycle. Are the perceptions of data representations continually aligned with the needs of those who work with those representations? Are the data service needs of those who work with those representations continually met? These are the two big questions addressed by ITIL professionals.

The focus of this primer will now shift towards these questions in the context of the Canadian Federal Public Service. You may click on the Table of Contents link below for an introduction to the questions about any IT/IM service standards for a publically-funded institutions in Canada. Or, you may jump directly into:

Data Ideology (AKA Service Standards)

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