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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

A Framework for Data Research in GIS Database using Meshing Techniques and the Map-Reduce Algorithm

Author 1: Abdoulaye SERE
Author 2: Jean Serge Dimitri OUATTARA
Author 3: Didier BASSOLE
Author 4: Jose Arthur OUEDRAOGO
Author 5: Moubaric KABORE

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2021.0120374

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 3, 2021.

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Abstract: Everywhere, centers, laboratories, hospital and pharmacy have faced many challenges to delivery quality of health service due to constraints related to limited availability of resources such as drugs, places, equipments and specialists, often in health deficit with increasing number of patients, for instance during COVID-19 pandemic. Late information on these constraints from health service centers will play negatively on service quality because of time delayed between requesting service on place and the response to delivery safe service. All these problems don’t strengthen prevention or fighting against diseases in a region. This paper proposes a data research framework in a NoSQL database based on GIS data, containing an abstract table that could be inherited or specialized to any adopted GIS solution leading to a central data management instead of installing several database sites. The central database accepts data updated in back office by data owner and allows data research based on meshing Techniques and the map-reduce algorithm in front office. Variant meshing techniques have been presented to clustering GIS data with associated definitions of the content of map-reduce in order to improve processing time. In application in health service, the experimental results reveal that this system contributes to improve drug management in pharmacies and could be also used in others fields such as Finance, Education and Shopping through agencies spread over the territory, to strengthen national information systems and harmonised data.

Keywords: Map-reduce; big data; digital health; classification; Geographic Information System (GIS); COVID-19; Spark; Mon-goDb; NewSQL;NoSQL

Abdoulaye SERE, Jean Serge Dimitri OUATTARA, Didier BASSOLE, Jose Arthur OUEDRAOGO and Moubaric KABORE, “A Framework for Data Research in GIS Database using Meshing Techniques and the Map-Reduce Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 12(3), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120374

@article{SERE2021,
title = {A Framework for Data Research in GIS Database using Meshing Techniques and the Map-Reduce Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120374},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120374},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {3},
author = {Abdoulaye SERE and Jean Serge Dimitri OUATTARA and Didier BASSOLE and Jose Arthur OUEDRAOGO and Moubaric KABORE}
}


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