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Japanese and Asian Historical Resources in the Digital Age

The National Museum of Japanese History
Makoto Goto, Satoru Nakamura, Chifumi Nishioka, Arianti Ayu Puspita, Taizo Yamada, Yuta Hashimoto, Natsuko Yoshiga, Tatsuki Sekino, Naoki Kokaze, and Shohei Yamasaki

Open Access

Japanese and Asian Historical Resources in the Digital Age, including the following papers:

"Constructing Data Infrastructure for Diversity of Local Resources and Local Culture" by Makoto Goto
"The University of Tokyo Digital Archives Development Project: Developing an Approach for Utilizing Academic Assets Across "Different Organizations" by Satoru Nakamura
"Promoting Open Access: The Development, Collaborations, and Evaluation of the Kyoto University Rare Materials Digital Archive" by Chifumi Nishioka
"Digitization of Cultural Artifacts for Design Education in Indonesia" by Arianti Ayu Puspita
"Development of a Historical Data Repository for the Distribution Platform of Japanese Historical Materials" by Taizo Yamada
"Rethinking the Digital Presentation of Historical Japanese Documents in the Age of Online Multimedia" by Yuta Hashimoto
"Conversion of Historical Ogihan Business Records into Linked Open Data via Human–Machine Cooperation" by Natsuko Yoshiga
"Processing of Japanese calendar dates in information systems — Tools and resources of HuTime Project" by Tatsuki Sekino
"Application of the methodology for structuring historical financial records to a Japanese historical source along with financial information" Naoki Kokaze
"Proportional ratios for adapting the administrative boundary changes of prefectures in the first half of the Meiji period to build long-term prefectural panel data" by Shohei Yamasaki

Citable Link

Published: 2021

Publisher: The National Museum of Japanese History

Copyright: 2021

ISBN(s)

978-1-60785-511-8 (open access)

Resources

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This image shows a part of working screen on a browser. An automatically chosen title and a partial designation of MeCab analysis are indicated in it.

Randomly chosen sentence and the automatic result of morphemic analysis

From Conversion of Historical Ogihan Business Records into Linked Open Data via Human–Machine Cooperation by Natsuko Yoshiga, Section 4.1

Randomly chosen sentence from the Title property and automatic results of morphemic analysis.

A result of morphological analysis (MeCab) is shown in Japanese. MeCab can properly tokenize words from Japanese sentences.

An example of morphemic analysis with MeCab

From Conversion of Historical Ogihan Business Records into Linked Open Data via Human–Machine Cooperation by Natsuko Yoshiga, Section 4.1

An example of morphemic analysis with MeCab.

A worker for the named entity extraction checks if a test sentence is properly tokenized and labeled with a named entity class.

An example of automatic labeling results for named-entity classes and the modification form

From Conversion of Historical Ogihan Business Records into Linked Open Data via Human–Machine Cooperation by Natsuko Yoshiga, Section 4.1

An example of automatic labeling results for named-entity classes (left) and the resulting modification form (right).

A worker chooses a decision if an automatic result is OK in this form. Some proposals by workers may be entered in the form.

An example of adding a new registration candidate label

From Conversion of Historical Ogihan Business Records into Linked Open Data via Human–Machine Cooperation by Natsuko Yoshiga, Section 4.1

An example of adding a new registration candidate label using the named-entity class modification function (left).

All workers can check real-time progress online.

Example of real-time progress by participants

From Conversion of Historical Ogihan Business Records into Linked Open Data via Human–Machine Cooperation by Natsuko Yoshiga, Section 4.1

Example of real-time progress, which shows the number of ONDB titles and named-entity extraction tasks completed by participants.

A number of checked titles clearly increased when paid workers attended for named entity extraction after July 2019.

The total number of ONDB titles for which named-entity extraction tasks were completed by month

From Conversion of Historical Ogihan Business Records into Linked Open Data via Human–Machine Cooperation by Natsuko Yoshiga, Section 4.1

The total number of ONDB titles for which named-entity extraction tasks were completed, aggregated by month.

Paid workers continued to work much compairing to non-paid workers.

The average number of tasks completed per hour by a participant over twelve months

From Conversion of Historical Ogihan Business Records into Linked Open Data via Human–Machine Cooperation by Natsuko Yoshiga, Section 4.3

The average number of tasks completed per hour by a participant over twelve months. The upper and lower figures depict the activities of unpaid and paid participants, respectively.

Event and Terms occupy near 60% in all named entity classes. Event words are generally easy to analyze by MeCab's preset dictionary.

The ratio of named entities of each class

From Conversion of Historical Ogihan Business Records into Linked Open Data via Human–Machine Cooperation by Natsuko Yoshiga, Section 5

The ratio of named entities of each class.

Person, Role and Place are difficult to identify from titles because it is not easy to find these historic and hyperlocal words on the Web.

Definition of the named-entity classes in ONDB

From Conversion of Historical Ogihan Business Records into Linked Open Data via Human–Machine Cooperation by Natsuko Yoshiga, Section 3.2

Definition of the named-entity classes in ONDB.

Date expressions of the Japanese calendar are converted into dats of the Gregorian calendar by using HuTime calendar conversion service.

HuTime calendar conversion service

From Processing of Japanese Calendar Dates in Information Systems: Tools and Resources of the HuTime Project by Tatsuki Sekino, Section 2.1

HuTime calendar conversion service. Date representations entered into the left text area are converted, and then the results are shown as output in the right text area. Input and output calendars are specified by a drop-down list at the top of the form.

A HuTime Calendar LOD resource of a calendar month links with other related resources and data.

Example of calendar-period resource provided by the HuTime Calendar LOD

From Processing of Japanese Calendar Dates in Information Systems: Tools and Resources of the HuTime Project by Tatsuki Sekino, Section 2.2

Example of calendar-period resource provided by the HuTime Calendar LOD. The resource placed at the center represents the Japanese calendar month, leap eighth months in the year of Genroku (元禄) 15, and links to the various data related to the calendar period. Ellipses and rectangles show the resources and literal values, respectively.

Timelines and a chart are displayed on a webpage using HuTime.

An example of the visualization of temporal information using HuTime

From Processing of Japanese Calendar Dates in Information Systems: Tools and Resources of the HuTime Project by Tatsuki Sekino, Section 3

An example of the visualization of temporal information using HuTime. The top timeline shows events related to the Tenshō (天正) embassy who officially visited Europe from Japan. This timeline has two timescales of both the Japanese and the Gregorian calendar. The second and third timelines show major events in Rome, Italy, and Japan, respectively. The bottom chart shows relative changes in estimated air temperature in Europe (the data are shown as relatives to the values in 1551). As shown in this example, HuTime allows the comparison of different types of temporal information on the same temporal axis.

Thirteen relations between time intervalsare shown with names of the reations based on Allen relations.

Allen relations

From Processing of Japanese Calendar Dates in Information Systems: Tools and Resources of the HuTime Project by Tatsuki Sekino, Section 4

Allen relations are classified relations between two time intervals into thirteen types. Each relation has an inverse relation except for the equals relation (e.g., before versus after relations).

Image of TEI-compliant metadata markup describing local financial resources based on Shōzei and Kugai taxation. The metadata includes values for county names, quantities, and units.

Markup example of the Shōzei and Kugai rice plants assigned to Suruga County

From Application of the Methodology for Structuring Historical Financial Records to a Japanese Historical Source along with Financial Information by Naoki Kokaze, Section 3.1

Markup example of the Shōzei and Kugai rice plants assigned to Suruga County

This map compares the size of each country's financial resources in ancient Japan, based on the values of Shozei and Kugai rice plants.

Financial comparison of administrative counties based on the number of Shōzei and Kugai rice plants. Map by Tableau Desktop

From Application of the Methodology for Structuring Historical Financial Records to a Japanese Historical Source along with Financial Information by Naoki Kokaze, Section 3.1

Financial comparison of administrative counties based on the number of Shōzei and Kugai rice plants. Created by Author. Map by Tableau Desktop

Image of TEI-compliant metadata markup as described in the body text, including values for 'expression' and 'article'.

Markup example of data processing on the abalone names

From Application of the Methodology for Structuring Historical Financial Records to a Japanese Historical Source along with Financial Information by Naoki Kokaze, Section 3.2

Markup example of data processing on the abalone names

This diagram illustrates how abalone is described in which formula in the Enki Shiki.

Variations of the names referring to abalone in the Engi-shiki. Graph by E2D3

From Application of the Methodology for Structuring Historical Financial Records to a Japanese Historical Source along with Financial Information by Naoki Kokaze, Section 3.2

Variations of the names referring to abalone in the Engi-shiki. Created by Author. Graph by E2D3