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Spatiotemporal Applications of Big Data

by Khalid Bin Muhammad, Tariq Rahim Soomro
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 21
Year of Publication: 2018
Authors: Khalid Bin Muhammad, Tariq Rahim Soomro
10.5120/ijca2018917921

Khalid Bin Muhammad, Tariq Rahim Soomro . Spatiotemporal Applications of Big Data. International Journal of Computer Applications. 181, 21 ( Oct 2018), 5-10. DOI=10.5120/ijca2018917921

@article{ 10.5120/ijca2018917921,
author = { Khalid Bin Muhammad, Tariq Rahim Soomro },
title = { Spatiotemporal Applications of Big Data },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2018 },
volume = { 181 },
number = { 21 },
month = { Oct },
year = { 2018 },
issn = { 0975-8887 },
pages = { 5-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number21/30007-2018917921/ },
doi = { 10.5120/ijca2018917921 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:06:33.589041+05:30
%A Khalid Bin Muhammad
%A Tariq Rahim Soomro
%T Spatiotemporal Applications of Big Data
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 21
%P 5-10
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Big data has emerged as a field of study and gained huge importance these days for both industry and researcher’s point of view. Initially database management systems (DBMS) developed to solve data management and relevant queries. Relational DBMS (RDBM) gave another innovation to the database field. Through the passage of time, it observed that some issues remained unsolved and required some more dimensions be added to the data. One of those was time and the other was location. Spatiotemporal aspects of data gained importance and scientists thought of incorporating these in the upcoming databases. This paper covers the inclusion of these dimensions in a database and its applications in today’s world. It also compares some of the tools used these days and suggests a combination for better results in an efficient and cost-effective way.

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Index Terms

Computer Science
Information Sciences

Keywords

Spatiotemporal Big Data RDBMS Hadoop.

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