A geohydrologie data visualization framework with an extendable user interface design

Yanfu Zhou, Jieting Wu, Lina Yu, Hongfeng Yu, Zhenghong Tang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We present a novel geohydrologic data visualization framework and apply the interface automata theory in support of time-varying multivariate data visualization tasks. The framework tackles heterogeneous geohydrologic data that has unique and complex data structures. The interface automata can generate a series of interactions and interfaces that are adapted to user selection and provide an intuitive method for visualizing and analyzing geohydrologic data. The interface automata can not only clearly guide user exploration, but also enhance user experience by eliminating automation surprises. In addition, our design can significantly reduce the entire system maintenance overhead, and enhance the system extendability for new datasets and data types. Our framework has been applied to a scientific geohydrologic visualization and analysis system, named INSIGHT, for the Nebraska Department of Natural Resources (NDNR). The new framework has brought many advantages that do not exist in the previous approaches, and is more efficient and extendable for visualizing geohydrologic data.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE International Conference on Big Data, Big Data 2016
EditorsRonay Ak, George Karypis, Yinglong Xia, Xiaohua Tony Hu, Philip S. Yu, James Joshi, Lyle Ungar, Ling Liu, Aki-Hiro Sato, Toyotaro Suzumura, Sudarsan Rachuri, Rama Govindaraju, Weijia Xu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2322-2331
Number of pages10
ISBN (Electronic)9781467390040
DOIs
StatePublished - Jan 1 2016
Event4th IEEE International Conference on Big Data, Big Data 2016 - Washington, United States
Duration: Dec 5 2016Dec 8 2016

Publication series

NameProceedings - 2016 IEEE International Conference on Big Data, Big Data 2016

Other

Other4th IEEE International Conference on Big Data, Big Data 2016
CountryUnited States
CityWashington
Period12/5/1612/8/16

Fingerprint

Data visualization
User interfaces
Automata theory
Natural resources
Data structures
Automation

Keywords

  • geohydrologic data
  • interface automata
  • visualization

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Hardware and Architecture

Cite this

Zhou, Y., Wu, J., Yu, L., Yu, H., & Tang, Z. (2016). A geohydrologie data visualization framework with an extendable user interface design. In R. Ak, G. Karypis, Y. Xia, X. T. Hu, P. S. Yu, J. Joshi, L. Ungar, L. Liu, A-H. Sato, T. Suzumura, S. Rachuri, R. Govindaraju, ... W. Xu (Eds.), Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016 (pp. 2322-2331). [7840865] (Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2016.7840865

A geohydrologie data visualization framework with an extendable user interface design. / Zhou, Yanfu; Wu, Jieting; Yu, Lina; Yu, Hongfeng; Tang, Zhenghong.

Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016. ed. / Ronay Ak; George Karypis; Yinglong Xia; Xiaohua Tony Hu; Philip S. Yu; James Joshi; Lyle Ungar; Ling Liu; Aki-Hiro Sato; Toyotaro Suzumura; Sudarsan Rachuri; Rama Govindaraju; Weijia Xu. Institute of Electrical and Electronics Engineers Inc., 2016. p. 2322-2331 7840865 (Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhou, Y, Wu, J, Yu, L, Yu, H & Tang, Z 2016, A geohydrologie data visualization framework with an extendable user interface design. in R Ak, G Karypis, Y Xia, XT Hu, PS Yu, J Joshi, L Ungar, L Liu, A-H Sato, T Suzumura, S Rachuri, R Govindaraju & W Xu (eds), Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016., 7840865, Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016, Institute of Electrical and Electronics Engineers Inc., pp. 2322-2331, 4th IEEE International Conference on Big Data, Big Data 2016, Washington, United States, 12/5/16. https://doi.org/10.1109/BigData.2016.7840865
Zhou Y, Wu J, Yu L, Yu H, Tang Z. A geohydrologie data visualization framework with an extendable user interface design. In Ak R, Karypis G, Xia Y, Hu XT, Yu PS, Joshi J, Ungar L, Liu L, Sato A-H, Suzumura T, Rachuri S, Govindaraju R, Xu W, editors, Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 2322-2331. 7840865. (Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016). https://doi.org/10.1109/BigData.2016.7840865
Zhou, Yanfu ; Wu, Jieting ; Yu, Lina ; Yu, Hongfeng ; Tang, Zhenghong. / A geohydrologie data visualization framework with an extendable user interface design. Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016. editor / Ronay Ak ; George Karypis ; Yinglong Xia ; Xiaohua Tony Hu ; Philip S. Yu ; James Joshi ; Lyle Ungar ; Ling Liu ; Aki-Hiro Sato ; Toyotaro Suzumura ; Sudarsan Rachuri ; Rama Govindaraju ; Weijia Xu. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 2322-2331 (Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016).
@inproceedings{25cb8a59690d435dabd5942f144fd131,
title = "A geohydrologie data visualization framework with an extendable user interface design",
abstract = "We present a novel geohydrologic data visualization framework and apply the interface automata theory in support of time-varying multivariate data visualization tasks. The framework tackles heterogeneous geohydrologic data that has unique and complex data structures. The interface automata can generate a series of interactions and interfaces that are adapted to user selection and provide an intuitive method for visualizing and analyzing geohydrologic data. The interface automata can not only clearly guide user exploration, but also enhance user experience by eliminating automation surprises. In addition, our design can significantly reduce the entire system maintenance overhead, and enhance the system extendability for new datasets and data types. Our framework has been applied to a scientific geohydrologic visualization and analysis system, named INSIGHT, for the Nebraska Department of Natural Resources (NDNR). The new framework has brought many advantages that do not exist in the previous approaches, and is more efficient and extendable for visualizing geohydrologic data.",
keywords = "geohydrologic data, interface automata, visualization",
author = "Yanfu Zhou and Jieting Wu and Lina Yu and Hongfeng Yu and Zhenghong Tang",
year = "2016",
month = "1",
day = "1",
doi = "10.1109/BigData.2016.7840865",
language = "English (US)",
series = "Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2322--2331",
editor = "Ronay Ak and George Karypis and Yinglong Xia and Hu, {Xiaohua Tony} and Yu, {Philip S.} and James Joshi and Lyle Ungar and Ling Liu and Aki-Hiro Sato and Toyotaro Suzumura and Sudarsan Rachuri and Rama Govindaraju and Weijia Xu",
booktitle = "Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016",

}

TY - GEN

T1 - A geohydrologie data visualization framework with an extendable user interface design

AU - Zhou, Yanfu

AU - Wu, Jieting

AU - Yu, Lina

AU - Yu, Hongfeng

AU - Tang, Zhenghong

PY - 2016/1/1

Y1 - 2016/1/1

N2 - We present a novel geohydrologic data visualization framework and apply the interface automata theory in support of time-varying multivariate data visualization tasks. The framework tackles heterogeneous geohydrologic data that has unique and complex data structures. The interface automata can generate a series of interactions and interfaces that are adapted to user selection and provide an intuitive method for visualizing and analyzing geohydrologic data. The interface automata can not only clearly guide user exploration, but also enhance user experience by eliminating automation surprises. In addition, our design can significantly reduce the entire system maintenance overhead, and enhance the system extendability for new datasets and data types. Our framework has been applied to a scientific geohydrologic visualization and analysis system, named INSIGHT, for the Nebraska Department of Natural Resources (NDNR). The new framework has brought many advantages that do not exist in the previous approaches, and is more efficient and extendable for visualizing geohydrologic data.

AB - We present a novel geohydrologic data visualization framework and apply the interface automata theory in support of time-varying multivariate data visualization tasks. The framework tackles heterogeneous geohydrologic data that has unique and complex data structures. The interface automata can generate a series of interactions and interfaces that are adapted to user selection and provide an intuitive method for visualizing and analyzing geohydrologic data. The interface automata can not only clearly guide user exploration, but also enhance user experience by eliminating automation surprises. In addition, our design can significantly reduce the entire system maintenance overhead, and enhance the system extendability for new datasets and data types. Our framework has been applied to a scientific geohydrologic visualization and analysis system, named INSIGHT, for the Nebraska Department of Natural Resources (NDNR). The new framework has brought many advantages that do not exist in the previous approaches, and is more efficient and extendable for visualizing geohydrologic data.

KW - geohydrologic data

KW - interface automata

KW - visualization

UR - http://www.scopus.com/inward/record.url?scp=85015153467&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85015153467&partnerID=8YFLogxK

U2 - 10.1109/BigData.2016.7840865

DO - 10.1109/BigData.2016.7840865

M3 - Conference contribution

AN - SCOPUS:85015153467

T3 - Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016

SP - 2322

EP - 2331

BT - Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016

A2 - Ak, Ronay

A2 - Karypis, George

A2 - Xia, Yinglong

A2 - Hu, Xiaohua Tony

A2 - Yu, Philip S.

A2 - Joshi, James

A2 - Ungar, Lyle

A2 - Liu, Ling

A2 - Sato, Aki-Hiro

A2 - Suzumura, Toyotaro

A2 - Rachuri, Sudarsan

A2 - Govindaraju, Rama

A2 - Xu, Weijia

PB - Institute of Electrical and Electronics Engineers Inc.

ER -