COVID-19: An Open Source Data Repository on GitHub Tackles Global Pandemic Information
The global pandemic has presented unique challenges and at the same time, has shown the incredible ability of the tech community to provide open source tools to organize and comprehend data related to the crisis. One such commendable project is the COVID-19 project on GitHub, developed by Pomber. As this public repository evolves, it brings the global community together by buzzing with the most recent data on the spread, recovery, and unfortunate loss from the virus.
Project Overview:
The primary objective of the COVID-19 GitHub project is to provide a comprehensive, time-series dataset of the pandemic. It aims to convert the data from the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) into a more accessible JSON format. This repository attracts data scientists, researchers, statisticians, and anyone interested in tracking and analyzing data related to the COVID pandemic.
Project Features:
This project takes the CSV files from the JHU CSSE and converts them into a more readable JSON format, making it easier for users to understand and monitor pandemic trends. It presents a time-series statistical approach, tracking cases at the sub-regional level globally, including detailed data of confirmed cases, deaths, and recovered patients. Thus, the project enables users to visualize and realize the spread, intensity, and effect of the virus over time.
Technology Stack:
This project heavily relies on JavaScript for data transformation and it hosts the datasets on GitHub. The decision to use JavaScript allows for easy integration with technologies that read and display JSON. Significant libraries used include 'csvtojson' for converting CSV data to JSON and 'node-fetch' for making HTTP requests to the JHU CSSE data repository.
Project Structure and Architecture:
In this project, the data is neatly structured based on date, country, and region, making the dataset perfectly suitable for time-series analysis. The code is also modularised with defined roles for file download, conversion, and the accuracy check of converted JSON files. This organized structure promotes reusability and easy comprehension of the project.
