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Big Data in Computational Social Sciences and Humanities: An Introduction Read chapter Read first chapter

2018 | OriginalPaper | Chapter

3. Telling Stories Through R: Geo-Temporal Mappings of Epigraphic Practices on Penghu

Author : Oliver Streiter

Published in: Big Data in Computational Social Science and Humanities

Publisher: Springer International Publishing

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Abstract

Analyzing the transformation of epigraphic practices on Penghu in the wake of the Japanese occupation, we try to shed some light on a keystone event that shaped a century of epigraphic practices on Penghu and Taiwan and that has the potential to help us understanding the nature of social practices, their emergence, transformation, and conceptualization as tradition. We show to what extent the geological and climatic conditions of a site shape these processes, yet without fully determining their development. Instead, human agents twist and fix shaped practices in accordance with their political or economic strategies, trying to outperform potential rivals and to conquer new markets with convincing cosmologies that sell their strategic inventions. Based on a large digital archive of epigraphic practices in East Asia, we try to set up a showcase of how to approach this and similar datasets in a framework of digital humanities that is driven by a hermeneutic concern of understanding textual or symbolic communication. We use R as a Swiss army knife that allows us to plot tables, timelines, maps, and more, hoping to create a wider interest in data exploration endeavors, which despite their technical appearance, endow our lives with meaning and a sense of relatedness.

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previous chapter Application of Citizen Science and Volunteered Geographic Information (VGI): Tourism Development for Rural Communities
next chapter Expressing Dynamic Maps Through Seventeenth-Century Taiwan Dutch Manuscripts
Footnotes
1
Loops can frequently be avoided in R and a programming code consists of a sequence of function calls, the outcome of which is assigned to variables with meaningful names.
 
2
The Data Archiving and Networked Services is an institute of the Royal Netherlands Academy of Arts and Sciences (KNAW) and Netherlands Organization for Scientific Research (NWO).
 
3
In Line 1, you specify a folder on your computer that should contain the data and functions. If not existing, you have to create that folder before. In Line 2, you start the download into this folder.
 
4
R knows also a right assignment ->, allowing to write lines from left to right. As most and earliest programming languages used the left assignment, most people are used to read and write code from right to left. With the right-assignment however, one has in R the opportunity to write highly readable code in the style of UNIX pipes using the magrittr package.
 
5
Line 1: You specify the folder into which you downloaded the ThakBong data. Line 2: All functions and commonly used data are loaded. You can always start your analysis of ThakBong data in R with these two lines, unless you want to update functions and data from the online repository.
 
6
A data frame stores data tables, similar to data tables in a relational database. df.thakbong[1,] returns the first row, df.thakbong[,1] the first column, and df.thakbong[1,1] the first element in the first column. The values of one column are stored in a vector. A vector is a sequence of data elements of the same type, e.g., all elements must be numerical or textual. A vector can be created by combining different elements, as in kids <- c( ’Mary’,’Bill’) . The data in this vector can be accessed, e.g., as in kids[1], which would yield “Mary.”
 
7
A list is more flexible than a vector as it may contain any combination of simple and complex values. A list is created through the operator list as in age<-list( kids,c=( 12,11) ) . The second (complex) element of this list can be accessed as age[[2]]. As age[[2]] is a vector, we can access the age of the first kid directly as age[[2]][1].
 
8
The function lapply returns a list and sapply simplifies the output and returns a vector if possible. The mapply function applies a function repeatedly with different parameters for each application.
 
9
Loops are a much debated design feature of computer languages. Hated by some and beloved by others, they are frequently believed to be hard to read and hard to be maintained. Although R offers the possibility to avoid loops in many cases, one is free to use loops of functions of the apply family.
 
10
You can use an existing function in mapply or construct an unnamed function in sapply and lapply. This function is then applied to each of the split data frames. If you have to use an unnamed function but the functionality is given in available functions, you can call the existing function from within the unnamed function, as in function( x,y) YOURFUNCTION( x,y) .
 
11
An early travel account on Penghu can be found in 汪大淵 Wáng Dàyuan (Wang Dayuan) (1339/1981).
 
12
As maps and geo-locations are loaded through the internet, this step requires your computer to be online.
 
13
The assumption of a cutoff point at 75% is arbitrary in absolute terms. Yet, if applied consistently, the estimate would allow to compare the readability of tombstones depending on the region or the material. And still, this assumption seems to match the extent to which local people know their local graveyards. Talking after a survey to local people about the graveyard we have visited, our interlocutors are usually surprised to hear us talking about readable Qing tombstones. Likewise, people refer to tombs of the 1960s as old tombs, although we have found tombs of the Japanese period in the same graveyard. In one particular instance, locals on the Tongpan island told us that people started to inscribe their tombstones about 100 years ago, although we found among the ten remaining inscribed tombstones two Qing tombstones, dating back at least 120 years. The knowledge that local people have of their graveyard is thus astonishingly precise, but not as precise as the data that we get through our digital documentation.
 
14
Peng, Five Hundred Years Ago, It Was One Family: 16.
 
15
Ibid.16.
 
16
Examples of these derivations are the Liu Zhongzhi (劉仲質), the Yuzhi Baijiaxing (御制百家姓), and the Baijiaxing Er2bian (百家姓二編) Theobald (2011).
 
17
Yingchaun can neither be found on a modern map of China nor in The China Historical GIS. Yet, numerous publications locate Yingchaun in Henan (河南). Most of these publications, unfortunately, work without historical sources and copy instead widely from each other. Without proper sources, these publications do not lend themselves to corroborate or refute the historical existence of Yingchuan (潁川). Many other tanghao are without doubt historical placenames and some have even equivalents in the modern world.
 
18
The only tombstone on Wang’an with a ’旹’ (shí) that predates this hypothesized shift after 1881 has unfortunately been used as target for shooting games by bored ROC soldiers. One of their bullets hit what might have been the character ’旹’ , right in its center, leaving only a few millimeters of the upper character component unscattered.
 
Literature
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Streiter, O., Goudin, Y., & Huang, J. C. (2011). ThakBong, digitizing Taiwan’s tombstones for teaching, research and documentation. In TELDAP 2010 - The International Conference on Taiwan e-Learning and Digital Archives Program (pp. 146–157). Taipei: TELDAP agency.
Streiter, O., Goudin, Y., Huang, J. C., Lin, A. M.-f., & Yen, S. K.-j. (2010). Places of shared histories: Spatial patterns of placename types on Taiwan’s tombstones. In GeoInformatics for Spatial-Infrastructure Development in Earth and Allied Sciences (GIS-IDEAS) (pp. 29–34). Hanoi: Japan-Vietnam Geoinformatics Consortium (JVGC).
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Tsao, S., Song, S.-r., Lee, C.-y., & Shea, K.-s. (1999). Explanatory Text of the Geological Map of Taiwan, Scale 1:50,000 Sheet 73, Sheet 74, Sheet 75, Sheet 76, Penghu Islands. Taipei: Central Geological Survey.
汪大淵 Wáng Dàyuan (Wang Dayuan). (1339/1981). 島夷誌略校釋 Dǎo yí zhì è xiào shì (A Brief Account of Island Barbarians). Beijing: Zhonghua.
澎湖縣政府民政局 Pēnghúxiàn Zhèngfǔ Mínzhèngjú (Penghu County Civil Affairs Bureau). (2005). 續修澎湖縣志. 卷二. 地理志 Xù xū pēnghúxiàn zhì. Juǎn èr. Dìlı̌ zhì (The Annals of Penghu County. Volume XIII. Geography). Magong: Government of Penghu County.
Metadata
Title
Telling Stories Through R: Geo-Temporal Mappings of Epigraphic Practices on Penghu
Author
Oliver Streiter
Copyright Year
2018
Book
Big Data in Computational Social Science and Humanities

Print ISBN: 978-3-319-95464-6

Electronic ISBN: 978-3-319-95465-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-95465-3_3

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