**2. Main points of this book**

Technological change is one of the greatest issues in the modern world. As the world faces societal challenges, for example, climate challenges, aging problem, and energy security, technology will contribute to new or better solutions for those problems. New technologies take longer to develop and mature; moreover which tend to be born in the interconnection of multiple technology fields, therefore early detection of emerging technological concepts across multiple disciplines will be a very important issue.

**(iii)** identification of key technology players,

potential acquisition target).

enhancement of the data-driven innovation.

\* and Mari Jibu2

\*Address all correspondence to: osabe-yoshiyuki@jpo.go.jp

1 Patent Information Policy Planning Division, Japan Patent Office, Japan

**3.3. Fields close to scientometrics**

**Author details**

Yoshiyuki Osabe<sup>1</sup>

**References**

Press; 1997

**3.2. Data-driven innovation**

**(iv)** discover of white areas where no one achieves a field yet, and

**(v)** understanding of stakeholders (e.g., competitors, upstream and downstream partners,

Introductory Chapter: Scientometrics http://dx.doi.org/10.5772/intechopen.78027 5

Recently, creating a new business and solving social problems utilizing big data have been expected to increase. The Ministry of Economy, Trade and Industry in Japan is supporting business creation through data utilization, and enterprises are developing advanced measures in the fields such as agriculture and medical care. On the other hand, new cooperation beyond industrial barriers between a present entity and a new entity created sharing data is still limited. For the economic development in near future, so-called "Data-Driven Innovation" will be necessary for firms: for example firms will utilize data sharing beyond entities, creating new added value. Since companies, especially SMEs, have rarely data scientists who deal with big data, scientometrics indicator or tools thereof can contribute to

Although "scientometrics" is mainly a study of relations between text of articles or patents and their authors/institutions, it is also highly corresponded to "science of sociology" which is mainly a study of relations between authors/institutions and text networking, or AI-related fields like "semantic

A reconstruction or remodeling of S&T fields above mentioned reinforces the knowledge-based development in terms of society and economy. Scientometrics will be able to foster a development of science, technology, and innovation by a quantitative perception and evidence-based policy making. Further study and development of scientometrics are expected in future.

2 Center for Research and Development Strategy, Japan Science and Technology Agency, Japan

[1] Hess DJ. Science Studies: An Advanced Introduction. New York: New York University

search" and "machine translation." Interdisciplinary research with other fields is expected.

Our goal is to seek to develop automated methods that aid the systematic, continuous and comprehensive assessment of technological emergence using one of the major foresight exercises, scientometrics. There is now a huge flood of scientific and technical information, especially scientific publications and patent information. Using the information patterns of emergence for technological concepts have been discovered and theories of technical emergence have also been developed in several years. We have been developing visualization tools that thousands of technical areas have been interacted with each other and evolved in time. Several indicators of technical emergence have been improved by universities, international organizations, and funding agencies.

This book intends to provide readers a comprehensive overview of the current state-of-the-art in scientometrics, focusing on the systematic, continuous and comprehensive assessment of technological emergence. This book is composed of 12 chapters by cutting-of-edge authors of many different nationalities from Europe to Asia.

Especially the chapter "Mapping Science based on research content similarity" by Dr Kawamura shows an interesting methodology for analyzing publications based on an adaptation of word embedding and paragraph embedding with an entropy-based word clustering methodology. The proposed combination of word embedding and entropy-based approach is very useful for the scientometrics community.
