Using neighborhood association area as new spatial data infrastructure to link public administrative data with GIS in Indonesia

Muriadi Arip,Yan Wanglin,Kazuyo Hirose

doi:10.21924/cst.4.1.2019.111

Abstract

Despite its potential use for earth observation and GIS-based analysis, Public Administrative Database (PAD) has been neglected in the spatial big data discussions. For instance, linking unaggregated public databases to the smallest administrative units for mining spatial data currently absents from literatures. In this study, a neighbourhood association base map was developed and the usability as a platform for linking PAD in Indonesia was investigated. The base map is proposed as a new feature in the Indonesia’s SDI. A data model was developed, and data accuracy and reliability were assessed by a case study. Four unaggregated databases obtained from public institutions were examined using common structured query language. The results show that from 1.3 million records, more than 95% can be directly linked to the base map. Finally, it is concluded that despite existence of challenges, linking PAD with the base map is feasible and beneficial for GIS-based analysis.

Highlights

The advanced technology with extraordinary and exponential improvements in data storage and computing capacities makes it possible to collect, manage, and analyze data in magnitudes and in manners that would have been inconceivable just a short time ago, so have the world's governments developed large-scale, comprehensive data files on tax programs, workforce information, benefit programs, health, and education [1]
At first stage, digitized village sketch maps resulted in highly deviated features
The second, the deviation comes from changing village boundaries itself, that is when the village boundaries changed and cause differences between the sketch maps and the metric base maps

Summary

Introduction

The advanced technology with extraordinary and exponential improvements in data storage and computing capacities makes it possible to collect, manage, and analyze data in magnitudes and in manners that would have been inconceivable just a short time ago, so have the world's governments developed large-scale, comprehensive data files on tax programs, workforce information, benefit programs, health, and education [1]. Government departments and agencies around the world routinely collect administrative data produced by citizen interaction with the state [3]. It is not surprising that many researchers, those in spatial-based research, found the lack of theoretical frameworks in the use of PAD. With appropriate theoretical frameworks, adequate data infrastructure, and linking between data sources, PAD can be a big data source for earth observation and spatial-based analysis. Because what the data depicting is human-environment interactions occurred in spatiotemporal dimensions

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Conclusion