INTRODUCTION

We, Debug Army, chose "Mapping Data for Societal Benefits" as our NASA space app challenge 2023. The reason we chose this challenge was we wanted to make an open-data platform where multiple different categorized data from different federal repositories could be found under a single, interactive commonly categorized data hub.

Data Nexus, a free easy-to-use platform, is designed to take into consideration the arduous process of accessing data about space. However, Data Nexus is not limited to data regarding space. We’ve also incorporated data from generally categorized topics such as climate, marine life, agriculture, health, etc. to make it readily available to end users with just a few clicks. In other words, our project is a warehouse for data that, in spite of being already available on the internet, are strenuous to find. Moreover, one has to crawl through different websites — many websites. We have a collection of over 3000 relevant datasets, each categorized into particular categories. Our data search process is stunningly swift, with key-to-key search updates.

Apart from this feature — indexing datasets — we have another groundbreaking feature that predicts the climatic conditions of the future in different countries by analyzing CO2 emissions throughout decades in the past.

HaCkathon Journey

Firstly, we gathered data availability from different federal repositories like GES DISC, EarthData.Nasa, NOAA, Data.gov, U.S Department of Agriculture, Center for Disease Control and Prevention, and USGS Geo Data.

After that we made a common category of 12 for all the data from those websites naming:

Space Exploration and Astronomy
Climate and Weather
Ocean and Marine
Solar Hub
Spectral/Engineering
Agriculture and Land
Environment and Ecosystem
Public Health and Surveillance
Human Dimensions
Hydrosphere and Cryosphere
Disease and Injury
Atmosphere and Biosphere

Then we started scraping data from those 7 sites using the Puppeteer framework of Javascript. The frontend of the website Data Nexus was built using React.js. All the scraped data (over 30000) was stored in a JASON file, which was distributed according to the common category. A search tab is made to search the required data to be accessed.

Now considering the rise in Global warming we thought of bringing interactive greenhouse gasses visualization to our website using Python and Chart.js. We used Python to Scrape data from all those websites addressing greenhouse gas emissions country-wise to help future researchers do a comparative study of greenhouse gas emissions. Then Using that data we used the ARIMA machine learning model for time series forecasting for future prediction of greenhouse house gases like CO2.

Benifits & VISION

Anyone interested in researching or exploring the data related to Space and Earth can access through this website in a friendly manner.

The website can be used to understand the CO2 emissions through the available timeline and do a comparative study. It can also be used to predict the future risk of GreenHouse gas emissions like CO2 to be aware and apply preventive measures and policies against the rise of greenhouse gas emissions to protect every component of the Planet.

Tools Used

Javascript, React.js, Chart.js, Puppeteer framework

Python, Pandas, ARIMA model, matplotlib

Github code

Link - https://github.com/aashishpanthi/spaceapps

Under MIT Lincence

References

NASA Space Apps 2023

Debug Army