Open Data: Where to start?

Looking for datasets? Check out the Where's the Data? page.

1) Visualize / tell stories with data

Lightweight data tools:

These are web-based tools that require no installation.

• Northwestern Knight Lab:
• Palladio
• DataBasic.io
• Carto

Mid-weight data tools:

These are tools that require installation, but that are relatively quick to get up and running.

• Tableau Public
• Google Fusion Tables
• Metabase
• Open Refine
• Microsoft Excel
• Microsoft Power BI

Heavyweight data tools:

These are tools that require installation, and may require more time investment to learn special syntax or skills. Some of them are also specialized tools for handling non-standard data types.

• R / RStudio / R Shiny
• Python (Anaconda)
• Plotly
• QGIS: An open source toolkit for manipulating and displaying spatial data.
• Gephi: For network/graph data visualization and analysis

2) Help curate/create open data

• OpenStreetMap: Visit LearnOSM for an introduction to the OpenStreetMap project, or check out the beginners' guide to learn how to start contributing to OpenStreetMap.

• Humanitarian OpenStreetMap: The Humanitarian Open Street Map Team (or "HOT") facilitates special mapping efforts for high-needs areas that have undergone natural disasters or other humanitarian crises.

• Wikipedia: Check out the Wikipedia tutorial on the official Wikipedia website. Or, visit Harvard Law School Library's guide on how to contribute to Wikipedia and Wikimedia Commons. There's also a nice WikiHow article outlining some of the contribution tasks you can engage in.

• "Where can you contribute to open data? Yes, you!"

3) Can't find the data you're looking for? Scrape your own data!

• Python Web Scraping Tutorial Using BeautifulSoup [Dataquest]: https://www.dataquest.io/blog/web-scraping-tutorial-python/

• Web Scraping Tutorial in R: https://towardsdatascience.com/web-scraping-tutorial-in-r-5e71fd107f32

4) Then what?

• Write your legislator
• Write a letter to the editor
• Author a blog post