# Chapter 2

# Advent of the Age of Big Data Utilization

Recent years have seen dramatic growth viable in electronically processed data represented by “big data,” improvement in computer processing capacity and technological innovation in artificial intelligence and other areas. These developments are based on data. It is expected that data utilization will lead to productivity improvement and new demand exploration that have been overlooked, contributing to economic growth and innovation promotion. This chapter reviews the present situation including challenges for data distribution and utilization and project a path for utilizing data while eliminating fears among citizens and promoting companies’ consciousness reform based on questionnaire surveys covering citizens and companies results.

## Section 1 Expanding Distribution and Utilization of Data

The utilization of big data holds the key to data-driven economic growth and social reform. This section pays attention to “innovation creation” brought about by data distribution and utilization and outlines initiatives and challenges, the balance between the utilization and pro-

### 1. Definition and Scope of Big Data

Further progress in digitalization, advanced networks and IoT development through smaller and cheaper IoT devices such as smartphones and sensors are paving the way for us to efficiently collect and share big data including location information and action history provided through smartphones, information on Internet and television watching and consumption behaviors and massive data gained through miniaturized sensors.

Big data has attracted attention in recent years particularly because data for distribution has expanded to cover not only traditional virtual (cyberspace) data in the ICT field but also real data provided through IoT development and new ICT tools, and business-to-consumer and business-to-business data. (Figure 2-1-1-1)

While various views exist about how to classify big data, this paragraph pays attention to data generated by individuals, business and government sectors and classifies big data into the following four broad categories.

Figure 2-1-1-1 Scope of this chapter

section of data and international conformity of data utilization. It also covers a wide range of data including business-to-business data, focusing on data categories and sectors in which Japan has competitiveness and sorts out data utilization and industrial competitiveness.

## 1 ) Government: "Open data" provided by national and local governments

Open data has had a lead as big data. The Basic Act on the Advancement of Utilizing Public and Private Sector Data, described later, calls for strongly opening public information owned by national and local governments as data.

## 2 ) Business: Digitalizing and structuralizing know-how (called "digitalized intelligence")

Digitalized intelligence is interpreted as data other than personal data owned by industries or companies from agriculture and infrastructure management to business services. In the future, various knowhow and accumulated knowledge in various areas and industries and familiar personal intelligence are assumed to be digitalized.

## 3 ) Business: M2M (Machine to Machine) streaming data (called "M2M data")

M2M data includes IoT device data in production sites and sensing data (including strains, vibrations, and types and weights of passing vehicles) from IoT devices installed on bridges. M2M data and digitalized intelligence in 2) are positioned mainly as industrial data from the viewpoint of information generation and utilization. Particularly, B2B data is expected to demonstrate Japan's competitiveness and enhance industrial power.

In this chapter, digitalized intelligence and M2M data are collectively called “industrial data $ ^{10} $ .”