Evaluation Platform of Sustainability for Global Systems

Statistical Approach to Geospatial Information for Big Data Integration

verfasst von: Aki-Hiro Sato, Hiroe Tsubaki

Verlag: Springer Nature Singapore

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

The authors of this book assert that Grid Square statistics, a method of aggregating data within a geographically defined Grid, may be an effective solution to approach geospatial data for big data integration. Grid Square statistics is a technique that allows us to collect and analyze data based on Grids and makes it easier to understand patterns and trends. Sustainability, a key concern for the future of our society, often involves balancing multiple independent objectives. These objectives and key performance indicators must be shared to solve multi-dimensional optimization problems with some constraints related to sustainability issues. However, many of these sustainability issues are challenges that are part of global systems, which are modeled as a complex system consisting of many components. Social, economic, and environmental aspects in our socio-economic systems require solutions designed for the sustainability of our society.

These conditions imply that Big Data must contribute to evaluating our current situation, actions, and changes to continuously change our behavior and society based on a Plan-Do-Check-Action (PDCA) cycle. The PDCA cycle, also known as the Deming cycle, is a four-step management method used to improve processes and products continuously. We must understand how to construct a platform by using Big Data to do so. Thus, extracting meaningful information from Big Data is crucially important in the advanced information society.

This book provides case studies based on Grid Square statistics. It shows their applications to socio-economic and environmental problems such as tourism, where we analyze visitor patterns to optimize resource allocation, SDGs indicator, where we monitor the sustainability of our socio-economic systems, and disaster management, where we face natural disaster to enhance preparedness. Finally, the book proposes a World Grid Square Statistics Reference Architecture for constructing data applications across organizations and domains and reports on design concepts, system architecture, and the implication of a data platform for World Grid Square data and statistics.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction

Abstract

This chapter depicts the background and concepts of a platform designed to evaluate global systems. Sustainability is a crucial concern within our socioeconomic-environmental systems and is formalized as multi-dimensional optimization problems containing several key performance indicators. Big data has enabled us to analyze and improve our world from a holistic point of view. Moreover, geospatial big data enhances the understanding of sustainability from regional aspects. However, they have several challenges from data and computation points of view. The utilization of Grid Square statistics can contribute to addressing critical issues to evaluate the sustainability of our world by enabling us to share and compute data and statistics in a reasonable way based on their ability on discretization or digitalization. Furthermore, this chapter addresses the purpose and motivation of this book and its structure.

Aki-Hiro Sato, Hiroe Tsubaki

Chapter 2. Methods and Concepts About Evaluation

Abstract

This chapter discusses the evaluation in the PDCA cycle consisting of plan (P), do (D), check (C), and action (A) for policy making. We will discuss a method that incorporates Bardach’s eight steps of policy analysis and performs policy analysis in a data-driven manner. Throughout gap analysis and data analysis to define problems based on evidence obtained at the policy analysis step, we explain how to identify gaps between ideal and current situations. Gap analysis is helpful to compare and analyze policy alternatives. Furthermore, to conduct policy analysis in a data-driven and systematic manner, it is effective to build a data infrastructure for the index values of evaluation criteria. As a data management framework, we introduce the Generalized Statistical Business Process Model (GSBPM), which is practical when an organization produces data and statistics, and KPI management, which is essential when an organization manages its process based on KPIs.

Aki-Hiro Sato, Hiroe Tsubaki

Chapter 3. Grid Squares and Grid Square Statistics

Abstract

This chapter introduces some examples of Grid Square and Grid Square statistics concepts. The purpose of this chapter is to introduce examples of Grid Square statistics and to help readers deepen their understanding of Grid Square statistics. Grid Square statistics need a standardized Grid Square coding system. This chapter introduces several definitions of Grid Square coding system and compares their strength and weakness. Moreover, we explain the Japanese National Grid Square codes (JIS X0410:2002) standardized in the Japan Industrial Standards (JIS). The Japanese National Grid Square statistics have been developed since the 1960s for both industrial and government usage in Japan. Finally, we show the definition of the World Grid Squares as an extension of JIS X0410:2002 for worldwide usage.

Aki-Hiro Sato, Hiroe Tsubaki

Chapter 4. Statistical Foundations About Grid Square Statistics

Abstract

This chapter introduces the statistical properties of Grid Square statistics. Grid square statistics can be described as tabular expressions, especially as matrix data or a contingency table in case of summarization for frequency or categorical data. We explain how to produce Grid Square statistics from qualitative and quantitative data. We further discuss errors in Grid Square statistics created as a statistical inference based on random sampling. For example, there are several Grid Square statistics about the number of persons within a Grid Square based on logs of mobile communication such as mobile phones and Wi-Fi base stations and land cover categorization produced by satellite images. Moreover, we confirm basic arithmetic operations between Grid Square statistics and explain the most fundamental procedure to convert Grid Square statistics on one Grid coordinate system into Grid Square statistics on another Grid coordinate system with concrete examples.

Aki-Hiro Sato, Hiroe Tsubaki

Chapter 5. How to Construct Data Infrastructure Based on Grid Square Statistics

Abstract

Grid square statistics—a kind of spatial statistics—is useful as a tool for analyzing, comparing and synthesizing statistics regarding anonymization. This chapter proposes how a data cube (linked open data) of World Grid Square Statistics can be constructed based on data collected from a range of sources, such as official statistics, satellite imagery, and point data from Internet providers. We present a definition of our World Grid Square coding system and a method of generating grid square statistics. We further propose a system for providing grid square statistics in a number of specific areas regarding their context and demonstrate their application to a data visualization and analytics platform.

Aki-Hiro Sato, Hiroe Tsubaki

Chapter 6. Distributed Architecture for Grid Square Statistics

Abstract

This chapter introduces distributed architecture for storing, searching, and computing Grid Square statistics. Since the data of Grid Square statistics is enormous, we need to consider efficient computation methods under limited computer resources. The distributed architecture gives us many solutions for handling Grid Square statistics. This chapter explains the fundamental principle of parallel computation with MapReduce algorithms or divide-and-conquer methods. We mention Amdahl’s law and Gustafson’s law. Moreover, we find an implementation of Web API a useful method to exchange data among elements of a distributed system. Finally, we propose a parallelization and distributed architecture for Grid Square statistics.

Aki-Hiro Sato, Hiroe Tsubaki

Chapter 7. Producing Grid Square Statistics on Demand

Abstract

This chapter proposes an on-demand service to produce Grid Square statistics. This on-demand service is based on the Generic Statistical Business Process Model (GSBPM) developed by UNECE. GSBPM consists of eight phases: Specify Needs, Design, Build, Collect, Process, Analyze, Disseminate, and Evaluate. We prototype an on-demand service for World Grid Square statistics as a web data application based on data collected from the OpenStreetMap (OSM) service. The system conducts processes automatically, from request acceptance to disseminating the World Grid Square statistics. We propose the following four steps to form the on-demand service in real-time: (i) users check out points of interest; (ii) the service automatically accesses Web API of Web Feature Service (WFS) to collect the data on points of interest; (iii) the system computes Grid Square statistics, and (iv) disseminates them. Since the types of points of interest dealt with in WFS vary enormously, and the total number of the World Grid Squares is vast, it is impossible to produce World Grid Square statistics for all the possible types of interests beforehand. However, our proposed service can produce and serve the Grid Square statistics in response to users’ requests. Moreover, we discuss a potential extension of the proposed system to other types of geographical expressions, such as postal codes and addresses.

Aki-Hiro Sato, Hiroe Tsubaki

Chapter 8. Case Studies

Abstract

This chapter shows some examples of Grid Square statistics and their applications. Specifically, we review several studies on Grid Square statistics. Mainly using Japanese data and statistics, we consider some use cases for disseminating official statistics such as population census, measuring economic activities of tourism, natural disaster risk assessment, and an SDGs indicator (SDG 11.3.1). Moreover, we explain the concept of text Grid analysis and show examples of text Grid Square data analysis.

Aki-Hiro Sato, Hiroe Tsubaki

Backmatter

Titel: Evaluation Platform of Sustainability for Global Systems
verfasst von: Aki-Hiro Sato
Hiroe Tsubaki
Verlag: Springer Nature Singapore
Electronic ISBN: 978-981-9722-96-9
Print ISBN: 978-981-9722-95-2
DOI: https://doi.org/10.1007/978-981-97-2296-9