Abstract

For geospatial cyberinfrastructure-enabled web services, the ability of rapidly transmitting and sharing spatial data over the Internet plays a critical role to meet the demands of real-time change detection, response and decision-making. Especially for vector datasets which serve as irreplaceable and concrete material in data-driven geospatial applications, their rich geometry and property information facilitates the development of interactive, efficient and intelligent data analysis and visualization applications. However, the big-data issues of vector datasets have hindered their wide adoption in web services. In this research, we propose a comprehensive optimization strategy to enhance the performance of vector data transmitting and processing. This strategy combines: (1) pre- and on-the-fly generalization, which automatically determines proper simplification level through the introduction of appropriate distance tolerance speed up simplification efficiency; (2) a progressive attribute transmission method to reduce data size and, therefore, the service response time; (3) compressed data transmission and dynamic adoption of a compression method to maximize the service efficiency under different computing and network environments. A cyberinfrastructure web portal was developed for implementing the proposed technologies. After applying our optimization strategies, substantial performance enhancement is achieved. We expect this work to facilitate real-time spatial feature sharing, visual analytics and decision-making.

Original languageEnglish (US)
Pages (from-to)1-20
Number of pages20
JournalInternational Journal of Digital Earth
DOIs
StateAccepted/In press - Jan 12 2018

Fingerprint

Web services
Decision making
Data visualization
decision making
Data communication systems
data transmission
spatial data
Internet
Concretes
visualization
Geometry
tolerance
compression
Processing
geometry
services
method
Big data
data analysis
material

Keywords

  • cyberinfrastructure
  • interoperability
  • performance optimization
  • real-time
  • Web feature service

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Earth and Planetary Sciences(all)

Cite this

@article{c34e03ce28f34972971478955a87e243,
title = "A comprehensive optimization strategy for real-time spatial feature sharing and visual analytics in cyberinfrastructure",
abstract = "For geospatial cyberinfrastructure-enabled web services, the ability of rapidly transmitting and sharing spatial data over the Internet plays a critical role to meet the demands of real-time change detection, response and decision-making. Especially for vector datasets which serve as irreplaceable and concrete material in data-driven geospatial applications, their rich geometry and property information facilitates the development of interactive, efficient and intelligent data analysis and visualization applications. However, the big-data issues of vector datasets have hindered their wide adoption in web services. In this research, we propose a comprehensive optimization strategy to enhance the performance of vector data transmitting and processing. This strategy combines: (1) pre- and on-the-fly generalization, which automatically determines proper simplification level through the introduction of appropriate distance tolerance speed up simplification efficiency; (2) a progressive attribute transmission method to reduce data size and, therefore, the service response time; (3) compressed data transmission and dynamic adoption of a compression method to maximize the service efficiency under different computing and network environments. A cyberinfrastructure web portal was developed for implementing the proposed technologies. After applying our optimization strategies, substantial performance enhancement is achieved. We expect this work to facilitate real-time spatial feature sharing, visual analytics and decision-making.",
keywords = "cyberinfrastructure, interoperability, performance optimization, real-time, Web feature service",
author = "Hu Shao and WenWen Li",
year = "2018",
month = "1",
day = "12",
doi = "10.1080/17538947.2017.1421719",
language = "English (US)",
pages = "1--20",
journal = "International Journal of Digital Earth",
issn = "1753-8947",
publisher = "Taylor and Francis Ltd.",

}

TY - JOUR

T1 - A comprehensive optimization strategy for real-time spatial feature sharing and visual analytics in cyberinfrastructure

AU - Shao, Hu

AU - Li, WenWen

PY - 2018/1/12

Y1 - 2018/1/12

N2 - For geospatial cyberinfrastructure-enabled web services, the ability of rapidly transmitting and sharing spatial data over the Internet plays a critical role to meet the demands of real-time change detection, response and decision-making. Especially for vector datasets which serve as irreplaceable and concrete material in data-driven geospatial applications, their rich geometry and property information facilitates the development of interactive, efficient and intelligent data analysis and visualization applications. However, the big-data issues of vector datasets have hindered their wide adoption in web services. In this research, we propose a comprehensive optimization strategy to enhance the performance of vector data transmitting and processing. This strategy combines: (1) pre- and on-the-fly generalization, which automatically determines proper simplification level through the introduction of appropriate distance tolerance speed up simplification efficiency; (2) a progressive attribute transmission method to reduce data size and, therefore, the service response time; (3) compressed data transmission and dynamic adoption of a compression method to maximize the service efficiency under different computing and network environments. A cyberinfrastructure web portal was developed for implementing the proposed technologies. After applying our optimization strategies, substantial performance enhancement is achieved. We expect this work to facilitate real-time spatial feature sharing, visual analytics and decision-making.

AB - For geospatial cyberinfrastructure-enabled web services, the ability of rapidly transmitting and sharing spatial data over the Internet plays a critical role to meet the demands of real-time change detection, response and decision-making. Especially for vector datasets which serve as irreplaceable and concrete material in data-driven geospatial applications, their rich geometry and property information facilitates the development of interactive, efficient and intelligent data analysis and visualization applications. However, the big-data issues of vector datasets have hindered their wide adoption in web services. In this research, we propose a comprehensive optimization strategy to enhance the performance of vector data transmitting and processing. This strategy combines: (1) pre- and on-the-fly generalization, which automatically determines proper simplification level through the introduction of appropriate distance tolerance speed up simplification efficiency; (2) a progressive attribute transmission method to reduce data size and, therefore, the service response time; (3) compressed data transmission and dynamic adoption of a compression method to maximize the service efficiency under different computing and network environments. A cyberinfrastructure web portal was developed for implementing the proposed technologies. After applying our optimization strategies, substantial performance enhancement is achieved. We expect this work to facilitate real-time spatial feature sharing, visual analytics and decision-making.

KW - cyberinfrastructure

KW - interoperability

KW - performance optimization

KW - real-time

KW - Web feature service

UR - http://www.scopus.com/inward/record.url?scp=85041115266&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85041115266&partnerID=8YFLogxK

U2 - 10.1080/17538947.2017.1421719

DO - 10.1080/17538947.2017.1421719

M3 - Article

AN - SCOPUS:85041115266

SP - 1

EP - 20

JO - International Journal of Digital Earth

JF - International Journal of Digital Earth

SN - 1753-8947

ER -