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Research Article | Open Access |

A Semantic NoSQL Application Program Interface for Big Data

Author 1: K. ElDahshan Author 2: E. K. Elsayed Author 3: H. Mancy Author 4: A. AbuBakr
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 13, No. 12 · Published 2022

DOI: https://doi.org/10.14569/IJACSA.2022.0131285

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Abstract

Complexity, heterogeneity, schemaless-ness, data visualization, and extraction of consistent knowledge from Big Data are the biggest challenges in NoSQL databases. This paper presents a general semantic NoSQL Application Program Interface that integrates and converts NoSQL databases to semantic representation. The generated knowledge base is suitable for visualization and knowledge extraction from different Big Data sources. The authors use a case study of the COVID-19 pandemic prediction and other weather occurrences in various parts of the world to illustrate the suggested API. The Authors find a correlation between COVID-19 spread and deteriorating weather. According to the experimental findings, the API's performance is enough for heterogeneous Big Data.

Keywords

NoSQL database formatting semantic technology data integration pandemic prediction

How to Cite this Article

ElDahshan, K., Elsayed, E. K., Mancy, H., & AbuBakr, A. (2022). A Semantic NoSQL Application Program Interface for Big Data. International Journal of Advanced Computer Science and Applications, 13(12). https://doi.org/10.14569/IJACSA.2022.0131285

ElDahshan, K., et al.. "A Semantic NoSQL Application Program Interface for Big Data." International Journal of Advanced Computer Science and Applications, vol. 13, no. 12, 2022, https://doi.org/10.14569/IJACSA.2022.0131285.

@article{ElDahshan2022,
  title     = {A Semantic NoSQL Application Program Interface for Big Data},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {12},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {K. ElDahshan and E. K. Elsayed and H. Mancy and A. AbuBakr},
  doi       = {10.14569/IJACSA.2022.0131285},
  url       = {https://doi.org/10.14569/IJACSA.2022.0131285}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

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