Biodiversity in China Zone II Versions EN1 Vol 3 (1) 2018
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A dataset of historical place names in Nanjing (1909, 1927 and 1937)
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: 2017 - 10 - 17
: 2017 - 10 - 24
: 2018 - 02 - 05
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Abstract & Keywords
Abstract: Historical place names, which record the temporal evolution of a historical city system, are of great significance to studies of the urban history of Nanjing and of modern Chinese history at large. Taking the years 1909, 1927 and 1937 as time axes, this study used the historical maps of Nanjing for corresponding years as base maps. By collecting and digitalizing place names from these maps and varied chorographies, the study established a geographical place classification system and built a dataset of historical place names in republican Nanjing.
Keywords: historical place name; Republic of China; Nanjing; map; GIS
Dataset Profile
Chinese title1909年、1927年、1937年南京城市历史地名数据集
English titleA dataset of historical place names in Nanjing (1909, 1927 and 1937)
Data corresponding authorChen Gang (chengang@nju.edu.cn)
Data authorsLiu Yuxuan, Yu Bingchen, Xu Haiyang, Chen Gang
Time range1909, 1927, 1937
Geographical scope118°22′ – 119°14′E, 31°14′ – 32°37′N
Data volume287 KB
Data formatESRI Shapefile
Data service system<http://www.sciencedb.cn/dataSet/handle/548>
Sources of fundingNational Natural Science Foundation of China (J41271160);
National Social Science Fund of China (14ZDA078)
Dataset compositionThe dataset consists of three parts of data: data of historical places in republican Nanjing in 1909, 1927, and 1937 respectively. It contains place names of corresponding periods extracted from chorographies.
1.   Introduction
The republican period is an important period of transition in Chinese modern history.1 As a cultural form, urban place names witness the development and changes of a city and are critical for exploring the city's spatial patterns in different periods. The change of place names records the evolution of a city and its people, and it contains a wealth of historical and cultural information.2
Abundant research findings have been made in the theories and methods of toponymy, with contents covering the origin, evolution, classification, function of geographical place names, and so on.3 In 2001, the Ministry of Civil Affairs of the People's Republic of China put forward the national standard of geographical names, which established a four-level place name classification system according to geographic attributes.4 On the standardization of geographical names, Wang et al. elaborated the principles, requirements and suggestions from the perspectives of national standardization, romanization and international standardization.5 Historical data of geographical names provide data support for studying the evolution of a city. As the capital of the Republic of China, Nanjing is the first city with full modern urban planning in Chinese modern history. Its influence on urban spatial structure and historical evolution is self-evident. Taking historical maps of republican Nanjing as work base and urban place names as research object, and by referring to Chronicle of the Capital (《首都志》) (known as the "Comprehensive Chronicle of Republican China"), this study examines, collects, and digitizes geographical name data of the three periods from maps and chorographies, and saves them as point vector data.
2.   Data collection and processing
2.1   Data sources
We selected three historical maps of Nanjing as base map for the study of urban place names. They were: New Measured Map of the Provincial Capital of Nanking by Jiangnan Military Academy (1909), Latest Map of Nanjing (1927) and New Map of Nanjing (1937). Figure 1 shows the technical flow of dataset generation.


Figure 1   Technical flow of dataset generation
However, maps usually have a limited and incomplete coverage of places depending on their designated functions. In this circumstance, documents that describe historical characters, events, places of a certain historical period, especially chorographies, importantly complement the study of urban spatial patterns. This study took historical maps as work base, supplemented by historical chorographies of the three periods. For 1909, the study used Annals of Shangyuan and Jiangning Counties (《上江两县志》), Continued Annals of Local History of Jiangning (《续纂江宁府志》), and Jinling Magazine (《金陵杂志》); the study used Xinjingbeicheng (《新京备乘》) for 1927 and Capital Chorography (《首都志》) for 1937. Completed in 1936, Capital Chorography is the oldest chorography in China. The data sources are detailed in Table 1.
Table 1   Outline of the data sources
MapNew Measured Map of the Provincial Capital of Nanking by Jiangnan Military AcademyLatest Map of NanjingNew Map of Nanjing
Year190919271937
Scale1:100001:100001:50000
PressJiangnan Military Academy (陆师学堂)Shanghai Zhonghua Book Company (中华书局)Rixinyudi Press (日新舆地学社)
ChorographyAnnals of Shangyuan and Jiangning Counties, for Tongzhi years (Wang Shiduo, 1874);
Continued Annals of Local History of Jiangning , for Tongzhi years(Mo Xiangzhi. 1874);
Jinling Magazine (Xu Shouqing, 1908)
Xinjingbeicheng (Chen Naixun, 1929)Capital Chorography (Wang Hanbiao, 1936)
2.2   Data collection and processing
Places of the three historical maps were manually digitalized and registered at the platform of the geographic information system software ArcGIS.
The 1: 25000 topographic map of Nanjing was taken as standard base map of this study. Spatial registration was based on the point data of the historical maps, where places of the least changes during these historical periods were registered, such as city wall and city gate. The GCS_Beijing_1954 coordinate system was selected, onto which the collected point data were directly positioned, whereas for linear data and plane data, central points were selected as positioning points which were subsequently saved as point data. Address and other attribute information were collected according to the place names extracted from historical maps and documents. In addition, the authors used scholars' published papers for further field investigations in a way to repair and supplement the attribute data. The data were then summarized and collated to complete the attribute data. Geographical places extracted from chorographies were verified against Baidu Map through spatial positioning, whereby the spatial relationship between places and road networks was calculated to complete registration.
2.3   Classification of place names
Based on the essential characteristics and functions of the places, we referred to the scope of different geographical entities as well as customer needs, distinguished and classified the place names by an established indicator system for place name classification.
2.4   Database of place names
Raw data of this database were drawn from chorographies. The database was built with the support of ArcGIS 10.0, based on the data model of Geodatabase. It mainly contains place name data of the three periods digitized and processed from historical maps and chorographies.
3.   Sample description
3.1   Classification system
After data processing, place names were distinguished and categorized based on national standards (GB/T 18521-2001) and Map World POI classification standards. The process of classification also considered toponymic information collected for the three periods, as well as particularities of the geographic entities of late Qing and republican China. Geographical places were classified into two categories according to national standards: natural geographical entity and human geographical entity. As the study focused on the functions of geographical entities, places were further divided into ten primary categories: hill and mountain, water body, traffic facility, city wall, urban and rural settlement, military and government agency, public facility, educational institution, religious shrine, and historical site (Table 2). By limiting the number of categories and clustering the places based on their function, the study generates a distribution map that better reflects the status of city development.
Table 2   Classification of geographical places in republican Nanjing
Primary categoryClassClass code
Hill and mountainMountA0100
Water bodyWaterBodyA0200
Traffic facilityTransportationB0300
City wallCityWallB0400
Urban and rural settlementSettlementB0500
Military and government agencyMechanismB0600
Public facilityFacilityB0700
Educational institutionSchoolB0800
Religious shrineShrineB0900
Historic siteScenicSpotB1000
According to the statistics, the number of valid place names was counted: 1,320 places in 1909, 1,048 places in 1927, and 1,666 places in 1937. Table 3 shows the distribution of the geographical places among different categories along different time periods.
Table 3   Quantitative statistics of geographical places in republican Nanjing
Year
Place
190919271937
Hill and mountain462342
Water body463759
Traffic facility589539507
City wall283737
Urban and rural settlement8851126
Military and government agency9971207
Public facility6779174
Educational institution5083398
Religious shrine2036563
Historic site1046353
Total132010481666
3.2   Dataset construction
The construction of this database mainly considered two aspects: spatial database design and attribute database design. The spatial database contains point data of historical place names with annotations. Specifics are shown in Table 4.
Table 4   Elements of the dataset
DatasetFeature layerFeature layer nameFeature type
Topographical dataPlace name in pointDZDMPoint
AnnotationDZDMZJAnnotation
The attribute database mainly includes place identification code, element code, place name, place name in traditional Chinese, primary category, primary category code, data source, address, geographic coordinate and remarks (Table 5).
Table 5   Structure of place name attributes
Serial No.AttributeData formatData length
1Place identification codeInt10
2Element codeInt10
3Place nameText50
4Place name in traditional ChineseText50
5Primary categoryText50
6Primary category codeText10
7Data sourceText50
8AddressText50
9Geographic coordinateText
10RemarksText50
3.3   Geographical place mapping
The year 1937 was the heyday of Shanghai's city development, which still profoundly impacts its development today. Taking 1937 as an example, we selected New Nanjing Map compiled and published in 1937, and chorographies as data sources. Based on spatial positioning and attribute entry of the toponymic data, we drew a map of geographical places of Nanjing in 1937 (Figure 2).


Figure 2   Distribution of geographical places of Nanjing in 1937
4.   Quality control and assessment
With a history of more than one hundred years, republican China is now left with inadequate mapping data. In comparison, historical geographical names of the periods are preserved intact in various historical documents, which lays a statistical basis for the study of historical geographical places of republican Nanjing. The study is further supported by reliable data sources – strictly controlled, publicly released maps (i.e., New Measured Map of the Provincial Capital of Nanking by Jiangnan Military Academy, Latest Map of Nanjing, and New Map of Nanjing), as well as detailed chorographies. During data acquisition, spatial registration and spatial positioning showed a high accuracy, and spatial positioning was performed by using spatial azimuth, distance and topological relationship to ensure a detailed, reliable and standard basic data set. In addition, the classification system was derived from a refinement of the Map World POI classification standards, and it was hence theoretically grounded and practically detailed. Although ArcGIS allowed a speedy and high-efficiency vectorization process, its limited intelligence level required vector data to be checked and repaired. To ensure the accuracy and reliability of the dataset, we then used topology rules for topological error checkup and topology tools for data recovery.
5.   Usage notes
The data in this dataset can be read and written by mainstream GIS software, or batch-processed by relevant function libraries in Python or other mainstream programming languages. The raw data of this dataset were extracted from historical maps and chorographies of Nanjing for the three periods (1909, 1927 and 1937). The classification system put forward by this paper provides a reasonable standard for classifying place names of a city. This dataset provides data basis for studying the historical development, urban spatial form, and spatial-temporal distribution of a city, etc. Its comprehensive coverage of geographical names allows readers to select any points of interest for specific analysis.
1.
Qin L. On the education legislation in the republican period (1912 – 1949). Doctoral dissertation, Hunan Normal University, 2014.
2.
Yin J. The main features of place name. Journal of Chinese Historical Geography 23 (1997): 127 – 142.
3.
Yu J. Research on spatial-temporal data modeling of urban historical place name: Taking Jiankang in six dynasties as an example. Master’s dissertation, Nanjing University, 2015.
4.
National Technical Supervision. Rules for Classification of Geographical Names and Code Representation. Beijing: China Standard Press, 2001.
5.
Wang J. Essays on Place Names by Wang Jitong. Shanghai: Social Sciences Academic Press (China), 1999.
Data citation
1. Liu Y, Yu B, Xu H et al. A dataset of historical place names in Nanjing (1909, 1927 and 1937). Science Data Bank. DOI: 10.11922/sciencedb.548
Article and author information
How to cite this article
Liu Y, Yu B, Xu H et al. A dataset of historical place names in Nanjing (1909, 1927 and 1937). China Scientific Data 3 (2018), DOI: 10.11922/csdata.2017.0001.zh
Liu Yuxuan
data collection and processing, writing of the paper.
MSc; research area: GIS analysis, design and development.
Yu Bingchen
data processing.
MSc; research area: GIS analysis, design and development.
Xu Haiyang
data processing.
MSc; research area: GIS analysis, design and development.
Chen Gang
technical support.
chengang@nju.edu.cn
PhD, Associate Professor; research area: GIS analysis, design and development.
National Natural Science Foundation of China (J41271160); National Social Science Fund of China (14ZDA078)
Publication records
Published: Feb. 5, 2018 ( VersionsEN1
Released: Oct. 24, 2017 ( VersionsZH2
Published: Feb. 5, 2018 ( VersionsZH4
References
中国科学数据
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