TMRA 2009TMRA 2009Construction of Authority Information for Personal Names Focused on the Former

Japanese Nobility using a Topic Mapp y g p p

2009/11/12, Leipzig, Germany, p g, yNorio Togiya

(togiya.norio@iii.u-tokyo.ac.jp)University of TokyoUniversity of Tokyo

Motomu Naito (motom@green.ocn.ne.jp)Knowledge Synergy Inc.

Table of Contents1. Introduction2. Target of investigationg g3. Constructing Authority Information4. Demo (authority topic map)4. Demo (authority topic map)5. Issues and Discussion5 1 Person’s name problem5.1 Person s name problem 5.2 Diversity of Information Items5 3 Problems of Centralized Topic Map5.3 Problems of Centralized Topic Map6. Future work:

Toward Distributed and Linked Topic MapsToward Distributed and Linked Topic Maps 7. Conclusion

1. IntroductionBackground・ There are many variant personal names for the same Japanese y p p

historical individual・ When handling historical data it is desirable to control them

h i d b idi h i f i i・ But there is no database providing such information in Japan at the present

・ There is a need to construct the authority information for personalThere is a need to construct the authority information for personal names structured in a standardized data description language

Purpose・ To investigate and analyze persons who played significant social

and cultural role・ To construct the authority information of them to support

historical and cultural studyhistorical and cultural study

2. Target information・ In the first stage, we are constructing a topic map of the authority

information relatively small scale and limited area・ We are focusing on the former Japanese nobility・ Japanese aristocracy is existing from after Meiji Restoration in

1869 til ft th d f WWⅡ i 19471869 until after the end of WWⅡ in 1947・ They played significant social and cultural roles in the

pre-WWⅡ periodpre WWⅡ period・ They often changed their name and had many alias names・ Meanwhile different persons often had the same name

3. Constructing Authority Information

We constructed our first topic map for the Authority I f i di h f ll iInformation according to the following process- Categorizing authority information

O l ki- Ontology making- Topic map making

A li i ki- Application making

3.1 Categorizing authority information・ We collected and analyzed information items・ We categorized those items and mapped them to information items

of Topic Maps ・ The following table shows the categories and TM correspondence

Categories of personal name authority information Correspondence in Topic MapsName Kanji (family name/personal name) Topic name

table: Categories of personal name source data (1/3)

Name

(multiple responses possible)

Kanji (family name/personal name) Topic name

Reading (family name/personal name) Variant and/or Internal occurrence

Romanization (family name/personal name) Variant and/or Internal occurrence

Type of names (alternatives or childhood names) (multiple responses possible)

Variant and/or Internal occurrence

Nationality (multiple responses possible) Linked by association to other topics

Gender (multiple responses possible) Linked by association to other topics

Rank (multiple responses possible) Linked by association to other topics

Profession (multiple response possible) Linked by association to other topicsProfession (multiple response possible) Linked by association to other topics

Person ID Subject ID

table: Categories of personal name source data (2/3)

Categories of personal name authority information Correspondence in Topic Maps

Related URL/URI Person URI External occurrence

Related URL (multiple response possible) External occurrence

Dates of birth and death

DOB (Western calendar only) (multiple responses possible)

External occurrence

DOD (Western calendar only)(multiple responses possible)

External occurrence(multiple responses possible)

Brief biography Japanese biography Internal occurrence

English biography Internal occurrence

Pl f bi th ( lti l ibl ) Li k d b i ti t th t iPlace of birth (multiple responses possible) Linked by association to other topics

Place of residence (multiple responses possible) Linked by association to other topics

table: Categories of personal name source data (3/3)

Categories of personal name authority information Correspondence in Topic Maps

Administrative data Date of input (multiple responses possible) Internal occurrence

Last update Internal occurrence

Type Internal occurrence

Language code (multiple responses possible) Internal occurrence

Character code Internal occurrence

Source confirmation Internal occurrence

Input by (multiple responses possible) Internal occurrenceInput by (multiple responses possible) Internal occurrence

Relationship (multiple responses possible

Teacher, student, acquaintance, father, mother, elder brother, elder sister, younger brother, younger sister, husband, wife, child

Association

3.2 Ontology makingWe made ontology according to the categorized items (subjects) and relationships between them

Ontology diagram of the topic map- Squares represent Topic types- Lines represent Association types

3.3 Topic map making- The topic map was generated using DB2TM which is included in Ontopiap

- Ontology definition file and XML configuration file are needed for DB2TM

- Ontology definition file defines the following:- Topic types

Name types- Name types- Association types- Association role typesyp- Occurrence types

- XML configuration file defines the mapping rule from EXCEL (CSV f ) i h l d fi i i(CSV format) into the ontology definition

3.4 Application makingWe developed the application using Ontopia Navigator Framework

Th f f h b li i

J2EE Web Server

The feature of the web application- Displaying instance list of each topic type

JSP Page

e.g. Tomcat

http

topic type- Displaying instance detail(names, occurrences and assciations)

N i i iTaglibs

topicmap

- Navigating topic map - Character string search- Tolog query interface

Query engine

<HTML>pages

- Graphical representation

server client

（Source: Ontopia, “The Ontopia Navigator Framework Developer’s Guide” ）

4. Demo Th b li i f l h i iThe web application for personal authority topic map

Screen shots of the application

5. Issues and discussion

- Many names for one person5.1 Person’s name problem

y p- The same name for many persons - Three notations for each name

Kanji nameReading (Katakana or Hiragana name)g ( g )Roman name

- How to describe them as topic namep- Content model is showed as follows:

name = element name { typicalName, aliasName* }typicalName = element typicalName { kanjiName, katakanaName, romanName } aliasName = element aliasName { kanjiName, katakanaName, romanName }{ j }

5. Issues and discussion5 2 Di it f I f ti It(1) Two kind of information items

d l i f i i

5.2 Diversity of Information Items

・ Fundamental information itemsThey are good candidate for PSI and PSDex: typical name alias nationality gender ordersex: typical name, alias, nationality, gender, orders,

date of birth and death, born and lived place, etc. ・ Specific information itemsp

They change according to individual domain and viewex: biographical outline, achievement, personal connection,

i i iposition, expertise, etc.(2) Items not depend on person

ex: place country organization occupation etcex: place, country, organization, occupation, etc.・ We cannot make exhaustive list for them if we pick up them

by occurrence basis. But if we make those list once, we can yshare them among many application

5. Issues and discussion

・ Authority information consists of diverse items and many

5.3 Problems of Centralized Topic Map

independent items・ It is very difficult and troublesome to integrate those items into

one centralized topic mapone centralized topic map・ Such topic map become complicated, hard to understand and

difficult to maintaindifficult to maintain・ Moreover there are different relations depending on domains

and ranges and they change according to the point of views・ It is desirable that we can filter out specific relation and link

from others flexibly

6. Future work:

Instead of centralized topic map, distributed and linked topic maps

Toward Distributed and Linked Topic Maps

are preferable・ Those topic maps are specialized and relatively simple and small

C tl l t f ’ i f ti i i h it d b・ Currently a large amount of person’s information is inherited by many libraries, museums, research institutes, etc. separately.

・ We think it is natural those organization continue to manage themWe think it is natural those organization continue to manage them・ We are making topic maps about information owned by them

- Author information owned by National Diet Library:800,000 records

- Historical person information owned by National Institute of Japanese Literat re: 50 000 recordsJapanese Literature: 50,000 records

・ Next we plan to create topic maps for places, countries, organizations, occupations, etc individuallyorganizations, occupations, etc individually

・ Then we will make effort to link them

Toward Distributed and Linked Topic Maps W l i h h i f TMRAP S bj3We are planning to use the mechanism of TMRAP, Subj3ct, Ontopedia to realize the Distributed and Linked Topic Maps

7. Conclusion・ As the first stage, we created the topic map for personal name

authority information focused on the former Japanese nobilitiesy p・ It made clear the genealogies, the network of the marriage

and other interrelationships between themand other interrelationships between them・ We believe our authority information is very useful for

researchers to study persons and their network related socialresearchers to study persons and their network related social, cultural and historical affair

・ There are strong needs to personal authority from various domainThere are strong needs to personal authority from various domain・ The data structure, Topic Maps, and the system structure we

propose have generality scalability and flexibilitypropose have generality, scalability and flexibility・ Thus, those are adaptable for various fields in the future

Thank you!