Intrinsic Origin and Design Application of Thick Data

XIAO Zhuo, LIANG Qiao

Packaging Engineering ›› 2026, Vol. 47 ›› Issue (2) : 131-142.

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Packaging Engineering ›› 2026, Vol. 47 ›› Issue (2) : 131-142. DOI: 10.19554/j.cnki.1001-3563.2026.02.013
Industrial Design

Intrinsic Origin and Design Application of Thick Data

  • XIAO Zhuo, LIANG Qiao*
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Abstract

The work aims to review and analyze the current research on the anthropological concept of "thick data", exploring the origins and development of thick data, and studying its application in design processes and research tools. Citespace citation analysis and in-depth literature review were combined to sort out the development of thick data theory and practice and design research methods for thick data were explored through case studies. The three stages of the development of thick data research in China were summarized, the connotations of terminology under the two major research lineages abroad were explained, and the core concepts of thick data were applied to design research. In China, thick data has undergone three stages of introduction, conceptualization and theorization. Internationally, based on different strategies for anthropology's engagement with the (big) data revolution, thick data research can be categorized into two lineages and three conceptual dimensions. Furthermore, by exploring the anthropological roots of thick data, this paper proposes a design research methodology grounded in thick data and investigates approaches for constructing user profiles based on thick data.

Key words

thick data / design research / design research methods of thick data

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XIAO Zhuo, LIANG Qiao. Intrinsic Origin and Design Application of Thick Data[J]. Packaging Engineering. 2026, 47(2): 131-142 https://doi.org/10.19554/j.cnki.1001-3563.2026.02.013

References

[1] 谭浩, 郭雅婷. 基于大数据的用户画像构建方法与运用[J]. 包装工程, 2019, 40(22): 95-101.
TAN H, GUO Y T.Construction Method and Application of Personas Based on Big Data[J]. Packaging Engineering, 2019, 40(22): 95-101.
[2] 梁若愚, 张凌浩. 面向产品设计迭代的缺陷信息挖掘方法研究[J]. 包装工程, 2019, 40(24): 150-157.
LIANG R Y, ZHANG L H.Defect Information Mining Method for Product Design and Improvement[J]. Packaging Engineering, 2019, 40(24): 150-157.
[3] 谭浩, 尤作, 彭盛兰. 大数据驱动的用户体验设计综述[J]. 包装工程, 2020, 41(2): 7-12.
TAN H, YOU Z, PENG S L.Big Data-Driven User Experience Design[J]. Packaging Engineering, 2020, 41(2): 7-12.
[4] WANG T. Big Data Needs Thick DataEthnography Matters[EB/OL] [2023-10-08](2025-05-11). https://ethnographymatters.wordpress.com/2013/05/13/big-data-needs-thick-data/.
[5] 李成熙, 文庭孝. 厚数据研究综述[J]. 高校图书馆工作, 2022, 42(1): 8-14.
LI C X, WEN T X.Thick Data: A Research Review[J]. Library Work in Colleges and Universities, 2022, 42(1): 8-14.
[6] CHEN C M.CiteSpace II: Detecting and Visualizing Emerging Trends and Transient Patterns in Scientific Literature[J]. Journal of the American Society for Information Science and Technology, 2006, 57(3): 359-377.
[7] 叶丽雅. 厚数据, 给大数据以灵魂[J]. IT经理世界, 2015(6): 54-55.
YE L Y.Thick Data Gives Soul to Big Data[J]. CEOCIO China, 2015(6): 54-55.
[8] 武涛, 刘叶婷. “进化”中的大数据: 新特性、新变化、新态势[J]. 信息系统工程, 2015(3): 101-103.
WU T, LIU Y T.Big Data in Evolution: New Features, Changes and Trends[J]. China CIO News, 2015(3): 101-103.
[9] 娄泽黎, 沈斌. 浅议“厚数据”思维下的我国海关“智慧风险管理”[J]. 中国市场, 2017(30): 154-156.
LOU Z L, SHEN B.On "Smart Risk Management" of China's Customs under the Thinking of "Thick Data"[J]. China Market, 2017(30): 154-156.
[10] 袁曦临. 制约我国智库研究与发展的瓶颈问题——跨学科研究与专题性研究资源保障[J]. 情报资料工作, 2017, 38(5): 99-104.
YUAN X L.On the Bottleneck Problem Restricting the Think Tank Research and Development in China: Interdisciplinary Research and Thematic Research Resources Support[J]. Information and Documentation Services, 2017, 38(5): 99-104.
[11] 涂涛, 胡柯铭. 一极两仪:教育大数据与厚数据关系辨析[J]. 中国电化教育, 2019(8): 18-22.
TU T, HU K M.Two Forms of the Supreme Ultimate: An Analysis of the Relationship between Educational Big Data and Thick Data[J]. China Educational Technology, 2019(8): 18-22.
[12] 张希煜, 茅明睿, 邢晓旭, 等. “厚数据+大数据” 激活老旧社区公共生活——以北京鸭子桥社区为例[J]. 北京规划建设, 2018(5): 4-10.
ZHANG X Y, MAO M R, XING X X, et al."Thick Data+Big Data" Activates Public Life in Old Communities—Taking Beijing Yaziqiao Community as an Example[J]. Beijing Planning Review, 2018(5): 4-10.
[13] 张晨旭, 张凌浩. 厚数据背景下面向城市合租人群的冰箱设计策略[J]. 大众文艺, 2020(2): 102-103.
ZHANG C X, ZHANG L H.Refrigerator Design Strategy of Sharing People from Cities under the Background of Thick Data[J]. Art and Literature for the Masses, 2020(2): 102-103.
[14] 郑儒雅, 汤晓敏, 王云. 厚数据支持下的城市老旧社区公园更新路径研究——以上海松江人乐花园为例[J]. 安徽农业大学学报, 2020, 47(6): 986-995.
ZHENG R Y, TANG X M, WANG Y.Research on Renewal Path of Urban Old Community Park Supported by Thick Data—A Case Study of Shanghai Songjiang Renle Garden[J]. Journal of Anhui Agricultural University, 2020, 47(6): 986-995.
[15] 孙智中, 张晨. 基于厚数据的信息分析: 内涵与模式[J]. 情报资料工作, 2020, 41(3): 69-75.
SUN Z Z, ZHANG C.Information Analysis Based on Thick Data: Connotation and Model[J]. Information and Documentation Services, 2020, 41(3): 69-75.
[16] PEDERSEN M A.Editorial Introduction: Towards a Machinic Anthropology[J]. Big Data & Society, 2023, 10: 20539517231153803.
[17] BOYD D, CRAWFORD K.CRITICAL QUESTIONS FOR BIG DATA: Provocations for a Cultural, Technological, and Scholarly Phenomenon[J]. Information, Communication & Society, 2012, 15(5): 662-679.
[18] BLOK A, PEDERSEN M A.Complementary Social Science? Quali-Quantitative Experiments in a Big Data World[J]. Big Data & Society, 2014, 1(2): 2053951714543908.
[19] BLOK A, CARLSEN H B, JØRGENSEN T B, et al. Stitching Together the Heterogeneous Party: A Complementary Social Data Science Experiment[J]. Big Data & Society, 2017, 4(2): 205395171773633.
[20] BORNAKKE T, DUE B L.Big-Thick Blending: A Method for Mixing Analytical Insights from Big and Thick Data Sources[J]. Big Data & Society, 2018, 5: 2053951718765026.
[21] HONG A, BAKER L, PRIETO CURIEL R, et al.Reconciling Big Data and Thick Data to Advance the New Urban Science and Smart City Governance[J]. Journal of Urban Affairs, 2023, 45(10): 1737-1761.
[22] CHRISTIN A.The Ethnographer and the Algorithm: Beyond the Black Box[J]. Theory and Society, 2020, 49(5): 897-918.
[23] BJERRE-NIELSEN A, GLAVIND K L.Ethnographic Data in the Age of Big Data: How to Compare and Combine[J]. Big Data & Society, 2022, 9: 20539517211069893.
[24] VOM LEHN D.Data, now Bigger and Better![J]. Consumption Markets & Culture, 2018, 21(1): 101-103.
[25] VARGHESE D, RANGANATHAN S.From texts to Contexts: The Relevance of Digital Ethnography in a Foucauldian Discourse Analysis of Online Gender Talk in Kerala[J]. Journal of Information, Communication and Ethics in Society, 2022, 20(4): 516-530.
[26] CURRAN J.Big Data or ‘Big Ethnographic Data’? Positioning Big Data within the Ethnographic Space[J]. Ethnographic Praxis in Industry Conference Proceedings, 2013, 2013(1): 62-73.
[27] ASTRUPGAARD S L, LOHSE A, GREGERSEN E M, et al.Fixing Fieldnotes: Developing and Testing a Digital Tool for the Collection, Processing, and Analysis of Ethnographic Data[J]. Social Science Computer Review, 2024, 42(5): 1223-1243.
[28] ARASTOOPOUR IRGENS G, EAGAN B.The Foundations and Fundamentals of Quantitative Ethnography[M]// Advances in Quantitative Ethnography. Cham: Springer Nature Switzerland, 2023: 3-16.
[29] BUCKINGHAM SHUM S.Book Review: Quantitative Ethnography by David Williamson Shaffer[J]. Journal of Learning Analytics, 2019, 6(1): 23-60.
[30] MUNK A K, WINTHEREIK B R.Computational Ethnography: A Case of COVID-19’s Methodological Consequences: Digital[M]// The Palgrave Handbook of the Anthropology of Technology. Singapore: Springer Nature Singapore, 2022: 201-214.
[31] LATZKO-TOTH G, BONNEAU C, MILLETTE M. Small Data, Thick Data: ThickeningStrategies for Trace- Based Social Media Research[M]// The SAGE Handbook of Social Media Research Methods. 1 Oliver's Yard, 55 City Road London EC1Y 1SP: SAGE Publications Ltd, 2016: 199-214.
[32] GEERTZ C.The Interpretation of Cultures[M]. New York: Basic Books, 1973.
[33] BROADWELL G A, BUTT M, KING T H.Syntax from the Bottom Up: Elicitation, Corpus Data, and Thick Descriptions[J]. Proceedings of the LFG14 Conference, 2014: 131-157.
[34] 杨焕. 数据与设计的融合——大数据分析导出用户需求洞察的创新路径研究[J]. 装饰, 2019(5): 100-103.
YANG H.The Integration of Data and Design: The Innovation Path Research of User Requirement Insight through Big Data Analysis[J]. Art & Design, 2019(5): 100-103.
[35] PONTEROTTO J.Brief Note on the Origins, Evolution, and Meaning of the Qualitative Research Concept Thick Description[J]. The Qualitative Report, 2015: 538-549.
[36] 柏琳瑶. 设计民族志在适老化盥洗空间体验设计中的应用研究[D]. 北京: 北京邮电大学, 2022.
BAI L Y.Research on the Application of Design Ethnography in the Experience Design of Age-Friendly Washroom Space[D]. Beijing: Beijing University of Posts and Telecommunications, 2022.
[37] 张朵朵, 李浩. 迈向超学科融合: 设计人类学的知识谱系研究[J]. 艺术设计研究, 2022(6): 56-63.
ZHANG D D, LI H.Towards Transdisciplinary Integration: A Knowledge Pedigree Research of Design Anthropology[J]. Art & Design Research, 2022(6): 56-63.
[38] MÜLLER F. Design Ethnography: Epistemology and Methodology[M]. Cham: Springer International Publishing, 2021.
[39] SALVADOR T, BELL G, ANDERSON K.Design Ethnography[J]. Design Management Journal (Former Series), 1999, 10(4): 35-41.
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