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Glyph-Master FX GMF Kanji Database KDB Kanji-Galaxy KGC Moji-Brain MJB

About

Summary

Introduction

WAJI is a fully independent and private initiative dedicated to Japanese characters. It began in 2005 as a simple collection of kanji. Over time, that collection grew in both size and complexity and eventually evolved into the Kanji Database (KDB).
As work on the Kanji Database progressed, new requirements emerged and led to the development of additional related projects. The first of these was Glyph-Master FX (GMF), an advanced glyph editor and browser application, followed by a sophisticated search engine for Japanese character data with the name Kanji-Galaxy (KGC).
Later, to help both myself and others learn Japanese characters more effectively, development began on an innovative learning platform Moji-Brain (MJB).

Objectives

The main goal of WAJI is to become a leading source for everything related to Japanese characters.
This goal will not be achieved simply by gathering vast amounts of data. It also requires critical review, careful verification, and a strong commitment to quality and accuracy. To meet this standard, WAJI follows a radically different approach to collecting, correcting, comparing, and correlating information (4C method) supported by modern information technologies and tools.
Another important objective is to foster a friendly and collaborative community where everyone interested in Japanese characters is welcome to participate, share knowledge, and engage in discussion.

Motivation

My long-standing fascination with Japan, its diverse culture, and its beautiful language naturally led me to a deeper interest in its unique and complex writing system.
After consulting countless books and other sources, several major problems became clear:

Fragmented and Limited Resources

Most available references on Japanese characters are either highly specialized or limited in scope. Many cover only a fraction of existing characters, while others focus only on specific aspects such as readings, variant forms, or historical details. A comprehensive and unified source of information is still missing.

Limited Digital Availability

Even today, many Japanese characters remain digitally unavailable because they are not supported by character sets or fonts. Without unique code points and usable fonts, unsupported characters can often only be represented through impractical workarounds such as images.

Quality and Accuracy Problems

Although many valuable resources on Japanese characters do exist, the quality and correctness of some so-called leading references and international standards are not satisfactory. Some even contain obvious errors, which should not be acceptable in authoritative sources.

Lack of Correction and Consistency

There is also a troubling lack of willingness to correct clear mistakes and long-standing inconsistencies that have accumulated over time. For example, kanji with controversial or variable stroke order such as 必, 左, and 右.

Progress

Although WAJI has been in development for more than 20 years, with only limited public announcements, substantial progress has been made behind the scenes, mostly in the areas of data collection, database design, and backend development.
Along the way, it was also necessary to learn and master many new skills, technologies, and workflows. These included UI/UX design, data engineering, data governance, data analytics, server administration, deployment and operations, automation, computer vision, and machine and deep learning.

Conclusion

For these reasons, there is a clear need to address the problems outlined above and to provide a better solution.
Another powerful motivation is that WAJI and its applications, despite being created as a spare-time project with very limited resources, have already developed into highly capable solutions. In many respects, they now rival, and sometimes even outperform, today’s best available sources and solutions.

Team

Jörn Ishikawa

  • Leadership
  • Design
  • Engineering
  • Infrastructure and Automation
  • Data
  • Machine Learning and AI
  • Quality and Knowledge Management
  • Outreach and Sourcing

Yukiko Ishikawa

  • Data
  • Quality and Knowledge Management
  • Outreach and Sourcing

History