The Idea

Ludovico Ariosto’s Orlando Furioso is an absolute masterpiece of italian renaissance epic poetry with knights and ladies and more lines than the Iliad and Odyssey combined. Keeping track of all the characters and their relationships throughout the epic is difficult to say the least and my copy was filled with post it notes where I would try to draw out a network of the different connections, only to have to constantly start over as it got to complicated. It was clear that a digital visualization of the character network was the best solution.


I didn’t have time to implement this until the summer, when I was interning at a FinTech company. The interns were given career development advice that emphasized the importance of building and maintain a network of connections. Another intern, Jack, and I were joking about how it would be fun to visualize these connections when I remembered thinking about an Orland Furioso network visualization.

This combination of FinTech networking and epic poetry led to us building Spiderweb, a versatile site that allows you to upload a database of people and their connections which it will process and visualize as a graph network. The site then allows further analysis of these networks through the use of filtering by different categories.

Ariosto's Knots

After building Spiderweb with Jack, I forked the project to create Ariosto’s Knots which is hard coded to only display the Orlando Furioso character data base I’ve compiled, with help from some friends who took the Orlando Furioso class with me the semester before. The name references the literary motif throughout the poem where characters relationships or loyalties are often compared to knots, or nodi in Italian, that lead to some difficult binds.

Creating a fixed site for the Orlando Furioso chart allows that data to be shared with anyone interested in using the site as a tool for easier analysis of the poem.

"Legano i cor d'indissolubil nodi" Ariosto VIII.1

Clicking on a character displays the description

Building the Site

To build the site Jack and I used React for the front end and python for the back end. I handled the front end, design, and backend API connection while Jack build the server to store the uploaded data in a dataframe and process for filtering. We used render.com to host our backend, although the free service often leads to a slow loading time. Our site is open source with the code available on the github linked at the top of this page.

Going forward we plan to continue building out the site for more complex filtering, grouping, and analytics.