A Potential Framework for Integration of Architecture and Methodology to Improve Statistical Production Systems

Eltinge John L. (), Biemer Paul P. () and Holmberg Anders ()
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Eltinge John L.: Bureau of Labor Statistics, Postal Square Building, 2 Massachusetts Avenue, NE Washington DC, U.S.A.
Biemer Paul P.: RTI, Research Triangle Park, NC 27709-2194, U.S.A.
Holmberg Anders: Statistics Sweden, Box 24300, SE-701 89 Örebro, Sweden

Journal of Official Statistics, 2013, vol. 29, issue 1, 125-145

Abstract: This article outlines a framework for formal description, justification and evaluation in development of architectures for large-scale statistical production systems. Following an introduction of the main components of the framework, we consider four related issues: (1) Use of some simple schematic models for survey quality, cost, risk, and stakeholder utility to outline several groups of questions that may inform decisions on system design and architecture. (2) Integration of system architecture with models for total survey quality (TSQ) and adaptive total design (ATD). (3) Possible use of concepts from the Generic Statistical Business Process Model (GSBPM) and the Generic Statistical Information Model (GSIM). (4) The role of governance processes in the practical implementation of these ideas.

Keywords: Adaptive Total Design (ATD); Evolutionary Operation (EVOP); Generic Statistical Business Process Model (GSBPM); paradata; survey quality; cost and risk; stakeholder utility; total survey error (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:29:y:2013:i:1:p:125-145:n:7

DOI: 10.2478/jos-2013-0007

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