Curating Solutions to Disparate Museum Collections Using Nodal Networks
A data visualization of the connections between various subjects in Lake Forest College Art Department’s collection utilizing nodal network visualization software, Gephi, and Python.
How does one measure the degree of connections within a museum’s collection?
These sets of data visualizations give an insider look into the collection housed within the Sonnenschein and Allbright galleries. These visualizations were coded in the programming language python, utilizing the plotly library as well as the nodal network program Gephi. The data was drawn from the collections database, including what information was known to us, such as title, artist, medium, donor, and date of creation and donation. The color palette for the visualizations was chosen to increase accessibility for those with colorblindness. In this case, the connections are found within the donors.
Sonnenchein and Albright Galleries (2023)
This nodal network visualization is an abstract view of the different pieces, labeled by ID, and how they each feed into the type of piece donated. It was made using a visualization software, Gephi. A way to dive into this visualization is to look at the subject and work your way out. The closest points are often those most relevant to each other.
This scatter-plot visualization is of the collection's donations from 1960-2023. The visualization illustrates the frequency of pieces donated in a given year.
This visualization, called a sankey diagram, is meant to show the flow of types of pieces donated to the donators who gave them. Pay attention to who gave large donations.
