A Data Exploration App for Archival Assessment Data

I used Streamlit to create an app for exploring collections assessment data* exported from ArchivesSpace, an open-source collections management system for archives.

It’s not related to an ML project, but I wanted to share with the community to show how the Streamlit framework can be a valuable tool for people doing data-centric work in the cultural heritage sector.

The functionality and layout are very basic, and I had to use fake data due to the variability of the ArchivesSpace assessment module. (This is also why there’s no file upload option: every archive that uses ArchivesSpace adds its own custom variables to the survey tool.)

I can think of several possible improvements, like the capability to detect different categories of variables to support file uploads, or adding a text search box to the search results table. This is my foray into Streamlit, so I tried to keep it simple for now.

If you’re curious about why I think there’s a need for an app like this one, you may want to check out a blog post I wrote here.

Thanks for reading. Feedback is welcome!

*Collections assessments are a type of survey tool that libraries, archives, and museums use to collect data about the stuff on their shelves (and drives). They use this data to inform a variety of operations, from prioritizing materials for preservation to developing fundraising strategies.

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