GSio: A programmatic interface for delivering Big Earth data-as-a-service

Pablo R. Larraondo; Sean Pringle; Jian Guo; Joseph Antony; Ben Evans

doi:10.1080/20964471.2017.1397898

GSio: A programmatic interface for delivering Big Earth data-as-a-service

Pablo R. Larraondo^*, Sean Pringle, Jian Guo, Joseph Antony, Ben Evans

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

In this paper, we present GSio, a software system for serving geospatial raster or gridded Big Earth Data at scale. GSio allows different scientific communities to consume geospatial analysis ready data. It provides a generic interface to the data, which removes the need to interact with individual files, and can interoperate with existing geospatial collections hosted on data centres and public clouds. A distributed compute model is used to read and transform the data in parallel using a cluster of compute nodes for delivering data as a service to users. Several use cases are presented demonstrating different scenarios where this service has been used.

Original language	English
Pages (from-to)	173-190
Number of pages	18
Journal	Big Earth Data
Volume	1
Issue number	1-2
DOIs	https://doi.org/10.1080/20964471.2017.1397898
Publication status	Published - 22 Dec 2017

Access to Document

10.1080/20964471.2017.1397898

Cite this

@article{f86e07a06ea84521a3eb3f298830e4c2,

title = "GSio: A programmatic interface for delivering Big Earth data-as-a-service",

abstract = "In this paper, we present GSio, a software system for serving geospatial raster or gridded Big Earth Data at scale. GSio allows different scientific communities to consume geospatial analysis ready data. It provides a generic interface to the data, which removes the need to interact with individual files, and can interoperate with existing geospatial collections hosted on data centres and public clouds. A distributed compute model is used to read and transform the data in parallel using a cluster of compute nodes for delivering data as a service to users. Several use cases are presented demonstrating different scenarios where this service has been used.",

keywords = "Big Earth Data, data-as-a-service, distributed, geospatial, scalable",

author = "Larraondo, {Pablo R.} and Sean Pringle and Jian Guo and Joseph Antony and Ben Evans",

note = "Publisher Copyright: {\textcopyright} 2017 The Author(s). Published by Taylor & Francis Group and Science Press on behalf of the International Society for Digital Earth, supported by the CASEarth Strategic Priority Research Programme.",

year = "2017",

month = dec,

day = "22",

doi = "10.1080/20964471.2017.1397898",

language = "English",

volume = "1",

pages = "173--190",

journal = "Big Earth Data",

issn = "2096-4471",

publisher = "Taylor and Francis Ltd.",

number = "1-2",

}

TY - JOUR

T1 - GSio

T2 - A programmatic interface for delivering Big Earth data-as-a-service

AU - Larraondo, Pablo R.

AU - Pringle, Sean

AU - Guo, Jian

AU - Antony, Joseph

AU - Evans, Ben

N1 - Publisher Copyright: © 2017 The Author(s). Published by Taylor & Francis Group and Science Press on behalf of the International Society for Digital Earth, supported by the CASEarth Strategic Priority Research Programme.

PY - 2017/12/22

Y1 - 2017/12/22

N2 - In this paper, we present GSio, a software system for serving geospatial raster or gridded Big Earth Data at scale. GSio allows different scientific communities to consume geospatial analysis ready data. It provides a generic interface to the data, which removes the need to interact with individual files, and can interoperate with existing geospatial collections hosted on data centres and public clouds. A distributed compute model is used to read and transform the data in parallel using a cluster of compute nodes for delivering data as a service to users. Several use cases are presented demonstrating different scenarios where this service has been used.

AB - In this paper, we present GSio, a software system for serving geospatial raster or gridded Big Earth Data at scale. GSio allows different scientific communities to consume geospatial analysis ready data. It provides a generic interface to the data, which removes the need to interact with individual files, and can interoperate with existing geospatial collections hosted on data centres and public clouds. A distributed compute model is used to read and transform the data in parallel using a cluster of compute nodes for delivering data as a service to users. Several use cases are presented demonstrating different scenarios where this service has been used.

KW - Big Earth Data

KW - data-as-a-service

KW - distributed

KW - geospatial

KW - scalable

UR - http://www.scopus.com/inward/record.url?scp=85073324476&partnerID=8YFLogxK

U2 - 10.1080/20964471.2017.1397898

DO - 10.1080/20964471.2017.1397898

M3 - Article

SN - 2096-4471

VL - 1

SP - 173

EP - 190

JO - Big Earth Data

JF - Big Earth Data

IS - 1-2

ER -

GSio: A programmatic interface for delivering Big Earth data-as-a-service

Abstract

Access to Document

Other files and links

Fingerprint

Cite this