Open AccessData Organisation and Process Design Based on Functional Modularity for a Standard Production Process
Author(s) -
David Cienfuegos Salgado,
M. Elisa Esteban,
Maria Novás,
Soledad Saldaña,
Luis Sanguiao
Publication year - 2018
Publication title -
journal of official statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.605
H-Index - 24
eISSN - 2001-7367
pISSN - 0282-423X
DOI - 10.2478/jos-2018-0041
Subject(s) - modularity (biology) , computer science , metadata , hierarchy , production (economics) , process (computing) , abstraction , data mining , object (grammar) , theoretical computer science , data science , artificial intelligence , programming language , world wide web , macroeconomics , epistemology , economics , market economy , biology , philosophy , genetics
We propose to use the principles of functional modularity to cope with the essential complexity of statistical production processes. Moving up in the direction of international statistical production standards (GSBPM and GSIM), data organisation and process design under a combination of object-oriented and functional computing paradigms are proposed. The former comprises a standardised key-value pair abstract data model where keys are constructed by means of the structural statistical metadata of the production system. The latter makes extensive use of the principles of functional modularity (modularity, data abstraction, hierarchy, and layering) to design production steps. We provide a proof of concept focusing on an optimisation approach to selective editing applied to real survey data in standard production conditions at the Spanish National Statistics Institute. Several R packages have been prototyped implementing these ideas. We also share diverse aspects arising from the practicalities of the implementation.