Commercial Visual Analytics Systems-Advances in the Big Data Analytics Field

被引:29
|
作者
Behrisch, Michael [1 ]
Streeb, Dirk [2 ]
Stoffel, Florian [2 ]
Seebacher, Daniel [2 ]
Matejek, Brian [1 ]
Weber, Stefan Hagen [3 ]
Mittelstaedt, Sebastian [3 ]
Pfister, Hanspeter [1 ]
Keim, Daniel [2 ]
机构
[1] Harvard Univ, Cambridge, MA 02138 USA
[2] Univ Konstanz, D-78464 Constance, Germany
[3] Siemens AG, Corp Res Germany, D-80333 Munich, Germany
关键词
System comparison; commercial landscape; visual analytics research; advances; development roadmap; IMAGE RETRIEVAL; VISUALIZATION; TIME; EXPLORATION; DESIGN; PROJECTIONS; KNOWLEDGE; FRAMEWORK; GUIDANCE; MODEL;
D O I
10.1109/TVCG.2018.2859973
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Five years after the first state-of-the-art report on Commercial Visual Analytics Systems we present a reevaluation of the Big Data Analytics field. We build on the success of the 2012 survey, which was influential even beyond the boundaries of the InfoVis and Visual Analytics (VA) community. While the field has matured significantly since the original survey, we find that innovation and research-driven development are increasingly sacrificed to satisfy a wide range of user groups. We evaluate new product versions on established evaluation criteria, such as available features, performance, and usability, to extend on and assure comparability with the previous survey. We also investigate previously unavailable products to paint a more complete picture of the commercial VA landscape. Furthermore, we introduce novel measures, like suitability for specific user groups and the ability to handle complex data types, and undertake a new case study to highlight innovative features. We explore the achievements in the commercial sector in addressing VA challenges and propose novel developments that should be on systems' roadmaps in the coming years.
引用
收藏
页码:3011 / 3031
页数:21
相关论文
共 50 条
  • [1] Visual analytics towards big data
    Ren, Lei
    Du, Yi
    Ma, Shuai
    Zhang, Xiao-Long
    Dai, Guo-Zhong
    Ruan Jian Xue Bao/Journal of Software, 2014, 25 (09): : 1909 - 1936
  • [2] Agile Visual Analytics for Banking Cyber "Big Data"
    Jonker, David
    Langevin, Scott
    Schretlen, Peter
    Canfield, Casey
    2012 IEEE CONFERENCE ON VISUAL ANALYTICS SCIENCE AND TECHNOLOGY (VAST), 2012, : 299 - 300
  • [3] Big Data Visual Analytics: Fundamentals, Techniques, and Tools
    Quang Vinh Nguyen
    Engelke, Ulrich
    SA'17: SIGGRAPH ASIA 2017 COURSES, 2017,
  • [4] Multimedia Big Data Analytics: A Survey
    Pouyanfar, Samira
    Yang, Yimin
    Chen, Shu-Ching
    Shyu, Mei-Ling
    Iyengar, S. S.
    ACM COMPUTING SURVEYS, 2018, 51 (01)
  • [5] Agile Visual Analytics in Data Science Systems
    Kandogan, Eser
    Engelke, Ulrich
    PROCEEDINGS OF 2016 IEEE 18TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS; IEEE 14TH INTERNATIONAL CONFERENCE ON SMART CITY; IEEE 2ND INTERNATIONAL CONFERENCE ON DATA SCIENCE AND SYSTEMS (HPCC/SMARTCITY/DSS), 2016, : 1512 - 1519
  • [6] A Comprehensive Survey on Big Data Technology Based Cybersecurity Analytics Systems
    Saravanan, S.
    Prakash, G.
    APPLIED SOFT COMPUTING AND COMMUNICATION NETWORKS, 2021, 187 : 123 - 143
  • [7] Big Data Analytics for Personalized Recommendation Systems
    Leung, Carson K.
    Kajal, Abhishek
    Won, Yeyoung
    Choi, Justin M. C.
    IEEE 17TH INT CONF ON DEPENDABLE, AUTONOM AND SECURE COMP / IEEE 17TH INT CONF ON PERVAS INTELLIGENCE AND COMP / IEEE 5TH INT CONF ON CLOUD AND BIG DATA COMP / IEEE 4TH CYBER SCIENCE AND TECHNOLOGY CONGRESS (DASC/PICOM/CBDCOM/CYBERSCITECH), 2019, : 1060 - 1065
  • [8] Big graph visual analytics
    Haglin, David
    Trimm, David
    Wong, Pak Chung
    INFORMATION VISUALIZATION, 2017, 16 (03) : 155 - 156
  • [9] Model-Driven Visual Analytics for Big Data
    Cheng, Shenghui
    Wang, Bing
    Zhong, Wen
    Xie, Cong
    Mahmood, Salman
    Wang, Jun
    Mueller, Klaus
    2016 NEW YORK SCIENTIFIC DATA SUMMIT (NYSDS), 2016,
  • [10] An algebra for distributed Big Data analytics
    Fegaras, Leonidas
    JOURNAL OF FUNCTIONAL PROGRAMMING, 2017, 27