(Feedback from Instituto Nacional de Estadistica; 28 September, 2017)

GSBPM and GSIM are two standards which are strongly linked, as we see in the picture appearing in both standards. We find this link absolutely essential in the construction of a modern statistical production process. It confers functional modularity and contains fundamental pieces of information to structure the process (input information objects, process parameters, subprocess description, output information object and process metrics). It would be advisable to provide some deeper guidance on this link by proposing some rules to specify this building block (e.g. how to specify the input object, how to describe the subprocess).

The part of GSIM of Structure seems to be described from the IT point of view but not from the Statistics point of view. We don't find certain objects like quality, estimates, variance, and errors. In contrast, we found a lot of different typology of processes. As an example, some objects of phase 5 and 6 of GSBPM that we don't find in GSIM could be: Variance, coefficient errors, aggregate, weights, edited and validated sample, quality indicators or dissemination product.

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  1. InKyung Choi

    28 Sep, 2017

    (Feedback from Statistics New Zealand; 28 September, 2017)

    In the modern data world, the linkage of the key GSIM objects to the relevant areas of GSBPM need to be made explicit, key GSIM information objects should be linked into the relevant sub-processes of the GSBPM so that people don't have to then try and navigate GSIM separately.  This would enhance the application to Admin and Big Data.  It would also be beneficial when statistical processes need to access data not held within the statistical organisation.  ie the data remains where it was captured - processes just run against it.

    Similar feedback has already made https://statswiki.unece.org/pages/viewpage.action?pageId=127665749