The "Biographical Text Context Analysis System for Buddhist Temple Gazetteers" is a context analysis system with many advanced
exploratory functions. It is primarily created based on the biographical data contained in historical records of Buddhist
temples, commonly referred to as "Buddhist Temple Gazetteers." The content of the Buddhist Temple Gazetteers is highly diverse,
covering the history and development of Buddhist temples, geographical landscapes, ancestral lineages, temple land assets,
architectural monuments, significant documents, and artistic creations, among other topics. Notably, the biographical texts
contained within these gazetteers hold significant research and reference value. According to our preliminary statistics,
biographical data makes up approximately 17% of the overall content in the Buddhist Temple Gazetteers, making it the
second-largest category after artistic materials.
The system is primarily built using the "Digital Archives of Chinese Buddhist Temple Gazetteers" established by the Dharma Drum
Institute of Liberal Arts. This archive includes the digitalized version of two important collections of Temple Gazetteers, the
“Zhongguo Fosi Shizhi Huika (中國佛寺史志彙刊)” and the "Zhongguo fosizhi congkan (中国佛寺志丛刊)”. After extracting the
biographical texts from these collections, the system is developed with the DocuSky digital humanities platform from the Digital
Humanities Research Center at National Taiwan University. This allows for biographical data to be accessed not only from the
perspective of individual subjects but also preserves the semantic connections between the individuals and the temples. Through
the system's classification, mining and analysis, referencing, and visualization functions, users are able to deeply explore and
research Buddhist biographical topics across multiple contexts, including time, space, and the structural categories of the
gazetteers. This interactivity allows for in-depth exploration and research on topics related to Buddhist figures.
隋唐傳記人物籍貫地分析
The native places analysis of biographies of Sui and Tang Dynasties
選擇「佛寺志人物傳記TGZ_Biographies」文獻集,從時間資訊後分類中,選擇傳主朝代:隋唐時期,再由內容資訊後分類進行籍貫地的視覺化觀察。
Using the corpus "TGZ_Biographies", and from the post Classification of time elements, select the dynasty of the author: the Sui and Tang Dynasties, and change to the post Classification of Content elements, conducting a visual observation(GISLite) of the Native places.
寺志所收錄之傳記傳主數目分析
Analysis of the Number of Biographical Subjects Recorded in Chinese Temple Gazetteers
選擇「佛寺志人物傳記TGZ_Biographies」文獻集,從內容資訊後分類中,選擇傳主來源寺志,並以文字雲觀察。
Select the corpus 'TGZ_Biographies', and from the post-Classification of Content elements, choose the ‘Src._Gaz._Title’, and observe its number scale as a word cloud.
傳記傳主年代分佈圖之比較分析
Comparative Analysis of the Distribution of Biographical Subjects Across the Era Distribution Chart
選擇「佛寺志人物傳記TGZ_BIOGRAPHIES」文獻集,從時間資訊後分類的「年代分佈圖」檢索(ALT+),輸入「朝鮮|高麗|高句麗;日本」,即可對照看到佛寺志人文傳記中有涉及日韓相關記錄的年代分佈。
Select the corpus 'TGZ_Biographies'. From the post-classification of Time elements, choose the Era Distribution Chart for retrieval (ALT+). Enter "Joseon|Goryeo|Goguryeo; Japan" to view the comparative distribution of eras with records related to Japan and Korea in the Buddhist temple gazetteers' biographical accounts.
高影響力人物(在多個寺志有傳記)
High-Influence Individuals (with Biographies in Multiple Temple Gazetteers)
選擇「佛寺志人物傳記TGZ_Biographies」文獻集,從內容資訊後分類中,選擇「傳主被傳志數」,勾選欲觀察的數量後,轉換後分類項目為「傳主名」,即可顯示該被傳數量的傳主清單,也可以文字雲進行觀察。
Select the corpus 'TGZ_Biographies', and from the post-classification of Content elements, choose the ‘Src_Total’ from the list of post-classification fields. After filtering the numbers change to the ‘Name’ and observe the word cloud.
運作範例 Sample
傳記被個寺志記載的人物
人物的影響力地圖
Map of Individual's Influence
選擇「佛寺志人物傳記TGZ_Biographies」文獻集,從內容資訊後分類中,選擇「傳主名」,勾選欲觀察的傳主後,再選擇「來源寺志描述地點」,進行地圖的視覺化。
Select the corpus 'TGZ_Biographies', and from the post-Classification of Content elements, choose the ‘Name’, select the subjects you wish to observe, change the element to 'Src._Gaz_Coordinates', and proceed with the map visualization function.