Rethinking 'big data' as visual knowledge: the sublime and the diagrammatic in data visualisation

被引:27
|
作者
McCosker, Anthony [1 ]
Wilken, Rowan [2 ,3 ]
机构
[1] Swinburne Univ, Fac Hlth Arts & Design, Melbourne, Vic, Australia
[2] Swinburne Univ Technol, Melbourne, Vic, Australia
[3] Swinburne Inst Social Res, Hawthorn, Vic, Australia
基金
澳大利亚研究理事会;
关键词
SCIENCE;
D O I
10.1080/1472586X.2014.887268
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
Informational data, we are told, are proliferating ever more rapidly and with increasing complexity. In an age of 'big data' we are seeing a broad reaching, and often uncritical fascination with data visualisation and its potential for knowledge generation. At its extreme this represents a fantasy of knowing, or total knowledge. Nonetheless, for those working in visual anthropology, big data and data visualisation offer significant extensions to our ways of knowing and our categories of knowledge. In this article we probe the fascination and potential of data visualisation and its relevance for understanding human experience, social relations and networks. First, we argue that the celebration of informational aesthetics can be understood as a version of the Kantian mathematical sublime. Extending this analysis, we argue that productive possibilities for thinking about data visualisation are to be found in Deleuze's engagement with the diagram. The diagram, for Deleuze, does not represent but rather operates both as expression and problem resolution. It is incomplete in the dual sense of never capturing the totality of the object and in its dynamism. This approach points to the merits of this investment in data visualisation (the way it works as expression and problem resolution), but highlights the need to be cautious about fetishising the sublimity of 'beautiful data'.
引用
收藏
页码:155 / 164
页数:10
相关论文
共 50 条
  • [21] From Big Data to Big Knowledge: The Art of making Big Data Alive
    El Houari, Meryeme
    Rhanoui, Maryem
    El Asri, Bouchra
    [J]. 2015 INTERNATIONAL CONFERENCE ON CLOUD TECHNOLOGIES AND APPLICATIONS (CLOUDTECH 15), 2015, : 289 - 294
  • [22] Big Data: Knowledge is Power
    Wildner, Manfred
    [J]. GESUNDHEITSWESEN, 2015, 77 (8-9) : 531 - 532
  • [23] Big Data knowledge discovery
    Xhafa, Fatos
    Taniar, David
    [J]. KNOWLEDGE-BASED SYSTEMS, 2015, 79 : 1 - 2
  • [24] Knowledge Engineering with Big Data
    Wu, Xindong
    Chen, Huanhuan
    Wu, Gong-Qing
    Liu, Jun
    Zheng, Qinghua
    He, Xiaofeng
    Zhou, Aoying
    Zhao, Zhong-Qiu
    Wei, Bifan
    Gao, Ming
    Li, Yang
    Zhang, Qiping
    Zhang, Shichao
    Lu, Ruqian
    Zheng, Nanning
    [J]. IEEE INTELLIGENT SYSTEMS, 2015, 30 (05) : 46 - 55
  • [25] From Big Data to Knowledge: An Ontological Approach to Big Data Analytics
    Kuiler, Erik W.
    [J]. REVIEW OF POLICY RESEARCH, 2014, 31 (04) : 311 - 318
  • [26] Everyday data cultures: beyond Big Critique and the technological sublime
    Burgess, Jean
    [J]. AI & SOCIETY, 2023, 38 (03) : 1243 - 1244
  • [27] Big data for Scientific Knowledge
    Canals, Agusti
    Lopez-Borrull, Alexandre
    [J]. PROCEEDINGS OF THE 18TH EUROPEAN CONFERENCE ON KNOWLEDGE MANAGEMENT (ECKM 2017), VOLS 1 AND 2, 2017, : 197 - 205
  • [28] Big Data Knowledge Mining
    Banuqitah, Huda Umar
    Eassa, Fathy
    Jambi, Kamal
    Abulkhair, Maysoon
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2016, 7 (11) : 180 - 189
  • [29] Everyday data cultures: beyond Big Critique and the technological sublime
    Jean Burgess
    [J]. AI & SOCIETY, 2023, 38 : 1243 - 1244
  • [30] Data Colonialism: Rethinking Big Data's Relation to the Contemporary Subject
    Couldry, Nick
    Mejias, Ulises A.
    [J]. TELEVISION & NEW MEDIA, 2019, 20 (04) : 336 - 349