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

John L. Eltinge 1 , Paul P. Biemer 2 , and Anders Holmberg 3
  • 1 Bureau of Labor Statistics, Postal Square Building, 2 Massachusetts Avenue, NE Washington DC, U.S.A.
  • 2 RTI, Research Triangle Park, NC 27709-2194, U.S.A.
  • 3 Statistics Sweden, Box 24300, SE-701 89 Örebro, Sweden

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.

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