Inspiration
One may write a perfect research document, but it is data representation skills that make the data visuals look easy to read for the reader. GraphLint was developed based on professional guidelines put forth by Professor Joanna Wolfe in her article "Reinforcing visualizations".
What it does
GraphLint analyzes bar graphs and data tables in your .odt document, such as a lab report, and gives you suggestions on how to improve the presentation of these charts.
How we built it
We split into two teams: one to program the interface (JavaScript, HTML5, CSS) and the integrating channels (Meteor and Flask), and another to complete the backend programming (Python).
Challenges we ran into
We are all amateur programmers and two of us are 112 students, but it was a really intense and fun learning experience since we never touched a lot of this stuff before but could still make something useful. Jumping from strings in 112 to lists and dictionaries and children and trees was a huge leap but it was amazing to see it work out.
Accomplishments that we're proud of
We made the backend and the frontend work perfectly. The only problem was integrating them.
What's next for GraphLint
If GraphLint succeeds, the next direction would be to allow GraphLint to analyze even more professional rules (it was built in less than 24 hours so we could only apply it to certain rules) and analyze more chart types (besides bar graphs and tables).
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