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Visualize LA: Working with the data

Visualize LA is a hub for using Los Angeles based USC Library collections as data.

Description

There are many ways to begin to work with and use the metadata provided. This depends greatly on what the metadata offers, technical expertise, subject area knowledge, and other factors. 

This page provides a small and focused selection of ways to approach and use the metadata. It is not exhaustive and the aim is for a general audience who has never worked with collections as data.

Also please check out our workshop series which has specific workshops on tools and data: https://libraries.usc.edu/locations/vkc-library/workshops

The README

One of the first things to consider when working with metadata is documentation.

A simple README file is one of the best ways to help you document, work with, and get to know your metadata. Most importantly though it will help you keep track of changes that you make to a file, questions that you have, problems that you encounter, and discoveries that you make. It can also be used to document how you use a file with a another tool or software. 

Data Exploration - Tableau

Tableau - https://www.tableau.com/academic/studentsIs a powerful platform that can be used for visualizing data. We have used it with many of our collections. One of the most interesting ways to use Tableau is as an image viewer. If you have a field with with an image URL you can create different types of viewers that can instantly give access to large collections. For example, USC's Wayne Thom collection is approximately 10,000 images. Using Tableau we were able to offer a one page snapshot view of every single image, grouped by category, represented as small boxes. When the box is hovered over it reveals the image with some corresponding metadata.

Data Exploration - Palladio

Palladio - https://hdlab.stanford.edu/palladio/

If you have a CSV file Palladio provides one of the easiest and fastest ways to start working with and exploring your data. CSV files should ideally have anywhere between 2,000 to 6,000 rows. More rows of data may slow down Palladio. It is recommended to simply clip your CSV file and work with a smaller subset if your file is large. 

Data Exploration - CARTO

CARTO - https://education.github.com/pack (Education pack from GitHub includes CARTO)

CARTO is a mapping platform that lets you focus on data and exploring and visualizing it easily. If you need a quick map that needs to be online CARTO is one of the best options available for students. 

Workshop

The following workshop walks through some simple use cases using Palladio and Tableau.

Request Data or Consultation

If you would like to make a request for materials please use the following form:

If you are not sure or want to learn more please contact us directly for a consultation:

arutkows@usc.edu or stacyw@usc.edu