数字人文中的可视化

doi:10.11959/j.issn.2096-0271.2022085

Abstract

Abstract:

The development of information technology has promoted the generation of a new scientific research paradigm.Social sciences and humanities have gradually developed a data-driven research method in recent years.From the perspective of visualization, the current status of visualization applications in digital humanities was summarized from three levels, task, data, and application, through the analysis of papers at the digital humantites conference organized by alliance of digital humanities organizations.By analyzing different projects setup by different experts with different backgrounds, i.e., humanities, visualization, and art.The great potential of multidisciplinary cooperation to improve the quality of digital humanities plus visualization projects was revealed.The practice of Peking University in exploring this new paradigm of multidisciplinary cooperation in digital humanities plus visualization was shared, which included education in multidisciplinary, practice experience on promotion, and research experience in intelligent visualization.Finally, two ways for the future development of the interdiscipline between digital humanity and visualization were revealed, the cooperation between experts and the collaboration between humans and computers.

Key words: visualization, digital humanities, multidisciplinary, education, big data in social science and humanities

CLC Number:

TP391

Yuchu LUO, Hao WU, Yuhan GUO, Shaocong TAN, Can LIU, Ruike JIANG, Xiaoru YUAN. Visualization in digital humanities[J]. Big Data Research, 2022, 8(6): 74-93.

Figures/Tables 9

References 30

[1]	SCHREIBMAN S , SIEMENS R , UNSWORTH J . A companion to digital humanities[M]. Hoboken: John Wiley ＆Sons, 2008.
[2]	王军 . 从人文计算到可视化:数字人文的发展脉络梳理[J]. 文艺理论与批评, 2020(2): 18-23.
	WANG J . From humanities computing to visualization:a survey of the development of digital humanities[J]. Theory and Criticism of Literature and Art, 2020(2): 18-23.
[3]	DEFANTI T A , BROWN M D . Visualization in scientific computing[J]. Advances in Computers, 1991,33: 247-307.
[4]	TUFTE E R . The visual display of quantitative information[J]. Journal for Healthcare Quality, 1985,7(3): 15.
[5]	THOMAS J J , COO K K A . Illuminating the path:the research and development agenda for visual analytics[M].[S.l.:s.n.], 2005.
[6]	HOCKEY S . The history of humanities computing[M]// A companion to digital humanities. Malden: Blackwell Publishing Ltd., 2004: 1-19.
[7]	BUSA R . The annals of humanities computing:the index thomisticus[J]. Medicina Nei Secoli, 1980,17(3): 443-459.
[8]	李卓群, 林泽斐 . 数字人文组织联盟的建设与启示[J]. 数字图书馆论坛, 2022(9): 63-69.
	LI Z Q , LIN Z F . The construction and enlightenment of the alliance of digital humanities organizations[J]. Digital Library Forum, 2022(9): 63-69.
[9]	COLLINS C , VIEGAS F B , WATTENBERG M . Parallel tag clouds to explore and analyze faceted text corpora[C]// Proceedings of 2009 IEEE Symposium on Visual Analytics Science and Technology. Piscataway:IEEE Press, 2009: 91-98.
[10]	TERRAS M . Crowdsourcing in the digital humanities[M]// A new companion to digital humanities. New York: John Wiley＆ Sons, 2015: 420-438.
[11]	KOHLHAMMER J , MAY T , HOFFMANN M . Visual analytics for the strategic decision making process[C]// Proceedings of the GeoSpatial Visual Analytics.Dordrecht:Springer. 2009: 299-310.
[12]	J?NICKE S , FRANZINI G , CHEEMA M F ,et al. Visual text analysis in digital humanities[J]. Computer Graphics Forum, 2017,36(6): 226-250.
[13]	J?NICKE S , GE?NER A , FRANZINI G ,et al. TRAViz:a visualization for variant graphs[J]. Digital Scholarship in the Humanities, 2015.
[14]	KEIM D A , OELKE D . Literature fingerprinting:a new method for visual literary analysis[C]// Proceedings of 2007 IEEE Symposium on Visual Analytics Science and Technology. Piscataway:IEEE Press, 2007: 115-122.
[15]	CANON C , BOYLE D , HEPWORTH K . Ethical and effective visualization of knowledge networks[J]. Digital Humanities Quarterly, 2022.
[16]	MCGUFFIN M J , BALAKRISHNAN R . Interactive visualization of genealogical graphs[C]// Proceedings of IEEE Symposium on Information Visualization. Piscataway:IEEE Press, 2005: 16-23.
[17]	LENARDO I D , DESCOMBES A . Repopulating Paris:massive extraction of 4 million addresses from city directories between 1839 and 1922[C]// Proceedings of the Digital Humanities Conference 2019.[S.l.:s.n.], 2019.
[18]	DONALDSON C , GREGORY I , TAYLOR J E . Implementing corpus analysis and GIS to examine historical accounts of the English Lake District[J]. Historical Atl as, 2017: 152-172.
[19]	EL KHATIB R , SCHAEBEN M . Why map literature? Geospatial prototyping for literary studies and digital humanities[J]. Le Champ Numérique, 2020,10(1).
[20]	GRANDJEAN M , JACOMY M . Translating networks:assessing correspondence between network visualisation and analytics[C]// Proceedings of the Digital Humanities Conference 2019.[S.l.:s.n.], 2019.
[21]	Harvard Univer sity, Academia Sinica, Peking University. China biographical database[Z]. 2018.
[22]	包弼德, 王宏苏, 傅君劢 ,等. “中国历代人物传记资料库”(CBDB)的历史、方法与未来[J]. 数字人文研究, 2021,1(1): 21-33.
	BOL P K , WANG H S , FULLER M A ,et al. The history,methods,and future of the China biographical database (CBDB) project[J]. Digital Humanities Research, 2021,1(1): 21-33.
[23]	BASTIAN M , HEYMANN S , JACOMY M . Gephi: an open source software for exploring and manipulating networks[C]// Proceedings of the International AAAI Conference on Web and Social Media. California:AAAI Press, 2009,3(1): 361-362.
[24]	BORGATTI S P , EVERETT M G , FREEMAN L C . UCINET for Windows:software for social network analysis[J]. Analytic Technologies, 2002,6: 12-15.
[25]	SCHICH M , SONG C M , AHN Y Y ,et al. A network framework of cultural history[J]. Science, 2014,345(6196): 558-562.
[26]	ALHARBI M , LARAMEE R S , CHEESMAN T . TransVis:integrated distant and close reading of Othello translations[J]. IEEE Transactions on Visualization and Computer Graphics, 2022,28(2): 1397-1414.
[27]	XIANG F , ZHU S S , WANG Z G ,et al. Enhanced family tree:evolving research and expression[C]// Proceedings of ACM SIGGRAPH 2020 Art Gallery. New York:ACM Press, 2020: 367-373.
[28]	LAI C F , LIN Z X , JIANG R K ,et al. Automatic annotation synchronizing with textual description for visualization[C]// Proceedings of 2020 CHI Conference on Human Factors in Computing Systems. New York:ACM Press, 2020: 1-13.
[29]	LIU C , XIE L W H , HAN Y ,et al. AutoCaption:an approach to generate natural language description from visualization automatically[C]// Proceedings of 2020 IEEE Pacific Visualization Symposium. Piscataway:IEEE Press, 2020: 191-195.
[30]	LIU C , HAN Y , JIANG R K ,et al. ADVISor: automatic visualization answer for natural-language question on tabular data[C]// Proceedings of 2021 IEEE 14th Pacific Visualization Symposium. Piscataway:IEEE Press, 2021: 11-20.

Metrics

Recommended 0

No Suggested Reading articles found!

Visualization in digital humanities

RichHTML

PDF下载

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 9

References 30

Related Articles 15

Metrics

Recommended 0

[1]	Haihong QIAN, Maoyi WANG, Yun XIONG. Digital transformation in higher education:a systematic review [J]. Big Data Research, 2023, 9(3): 56-70.
[2]	Yadong WU, Jiaming CHEN, Yan LUO, Xuefeng WANG, Dechun HUANG, Chao NI, Jiming LAN, Suiqun LI, Weihan ZHANG, Wei DAI. An overview of Caideng metaverse research [J]. Big Data Research, 2023, 9(3): 97-113.
[3]	Ye LIU, Wei CHENG, Yan LI, Yimeng YIN, Huijie SUN. Research on the construction of educational community from the perspective of metaverse [J]. Big Data Research, 2023, 9(1): 78-86.
[4]	Yaxiu YU, Xin LI. Research on text annotation method of ancient works from the perspective of digital humanities：a case study on MARKUS [J]. Big Data Research, 2022, 8(6): 15-25.
[5]	Tongzheheng ZHENG, Bin LI, Minxuan FENG, Bolin CHANG, Dongbo WANG. Explore the structuration of historical books:the construction and quantitative analysis of digital humanities database of the Biographies of the Shiji [J]. Big Data Research, 2022, 8(6): 40-55.
[6]	Jing CHEN. Humanities big data and its application in the field of digital humanities [J]. Big Data Research, 2022, 8(6): 3-14.
[7]	Haishan GUAN, Yulong ZHENG, Bifan WEI, Zemin ZHANG, Hao YUE, Bin SHI, Bo DONG. Extraction and visualization analysis of key elements of tax preferential policies [J]. Big Data Research, 2022, 8(5): 106-123.
[8]	Liang FAN, Xiaorong ZHANG, Yadong WU, Cheng CHEN, Fang WANG. A sort-last architecture based parallel volume visualization algorithm for unstructured grid [J]. Big Data Research, 2021, 7(4): 117-129.
[9]	Jingxi WEN, Hufei YU, Jiang XIN, Yan TANG. Analysis of gender differences in the brain based on deep learning [J]. Big Data Research, 2021, 7(4): 130-140.
[10]	Chao CHEN, Yadong WU, Chaoshuai FU, Xing TONG, Pan LI, Qikai CHU, Xuenan WANG. Research on visualization of Chinese Baijiu culture [J]. Big Data Research, 2021, 7(2): 78-98.
[11]	Lin YANG, Wei WANG, Ji ZHU, Mingzheng WANG. Research and practice on education data standard system for data sharing [J]. Big Data Research, 2020, 6(6): 3-13.
[12]	Huanyou CHAI, Sannyuya LIU, Lingyun KANG, Yaxian ZHANG, Qing LI, Zhi LIU. Research on the mechanism and key technologies for big data collection in education [J]. Big Data Research, 2020, 6(6): 14-25.
[13]	Xiangchun HE, Shaoqing GUO. Construction and application of regional education platform based on data intelligence [J]. Big Data Research, 2020, 6(6): 40-51.
[14]	Jieyu YUE, Chaoyang LUO, Jingshu DING, Qing LI. Research on privacy protection mechanism and technology of educational big data [J]. Big Data Research, 2020, 6(6): 52-63.
[15]	Yuanzhuo WANG, Jianye YU. Construction of big data teaching system under the background of emerging engineering education [J]. Big Data Research, 2018, 4(6): 11-18.