Datatura is based on the Nucleus challenge as well as personal experience with various data platforms such as Kaggle.

What it does

With the platform, researchers and labs can easily store data about their equipment, who can use it and when it is available. Furthermore, we are developing an easy-access database solution (the frontend is still in the works) to allow researchers to draw in data from other studies so that Mark, who is developing a machine learning algorithm to de-noise MRI scans can use data already collected by Steve and Bill who both worked on identifying bone fractures. This will exponentially decrease the amount of time spent collecting data and increase the time for thinking.

How we built it

Our backend is built using Django with an SQLite database. We strove to create as many connections between different data points as possible (e.g. equipment is linked to measurements to facilitate calculation of uncertainty) so that researchers later on can identify exactly what they need from the platform. Our frontend is based on JavaScript, JQuery, HTML, CSS and Bootstrap which gives it the distinct 'bootstrap-y' look (I have nothing more to say). We also used MapBox to serve clean and efficient maps to our users.

Challenges we ran into

No one in our team felt entirely comfortable working on the frontend which is why we wasted so much time on that. Because of this, we decided that we wouldn't go for the best UI award as it would have been too easy ;).

What we learned

We learned even more about the various pains of HTML and CSS and were reminded why that isn't our specialty.

What's next for Datatura

We hope to stand up a complete authentication system for the front end (which shouldn't take long) and finish the front end of the data storage platform.

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