The Oracle Advisor
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There are many prominent unsolved problems the world faces today. There are also many young people interested in these fields. In order to solve these issues in the future, the world needs more motivated and interested students with solutions. We hope that our platform can connect students and researchers to start their passions early and foster mentor relationships.
What it does
Our project is called Oravise, an oracle advisor. Oravise is a peer to peer scholarly website connecting individuals curious about unsolved world problems across academic fields including astronomy, computer science, mathematics, medicine, and other important subjects with researchers in those respective fields. The website allows users to select an academic researcher from a list given the users chosen subject, subcategory, and unsolved problem and connect with them.
How we built it
We scraped Wikipedia's list of unsolved problems webpage, putting the questions into a JSON file. Additionally, to obtain scholarly researchers through Google Scholars we tried to use a public API, however, it was depreciated, so instead, we created our own API using BeautifulSoup4. We then parsed these results into a Mongodb database. On the front end we used flask to create the website using a model, view, and controller structure along with Bootstrap.
Challenges we ran into
Due to the formatting inconsistency across the Wikipedia pages, the collection of our data took longer than expected even with scraping. Additionally, because we tried to use a public API that was depreciated, so we had to create our own API, which pushed our timeline back. Our group also had vastly different skillsets of frontend and backend development.
Accomplishments that we're proud of
Our model will connect a new wave of researchers with current academic researchers to develop solutions to the world's unsolved problems. Furthermore, bringing together the entire project was definitely a big task for us as we all came from different backgrounds. In the future, Oravise could be used to breed a new generation of motivated students with world-class mentors helping feed that passion.
What we learned
We learned how to create own our API using Python and BeautifulSoup4. We also learned how to use flask for web development. Both of these tools allowed were pivotal aspects to creating our model.
What's next for Oravise
In the future, we would like to incorporate a wider range of subjects and researchers into our model, ultimately allowing any student to be able to get advice from a researcher.