This page curates everything from open government data to visualization tools to data standards to algorithmic implementation. The only common thread is that all these data/data-products share a commitment to civic interest.
I’ll do my best to highlight organizations that are doing important and exciting data work, but be sure to drop me a line if you think something’s missing.
Curated by Deblina Mukherjee
Curators are not responsible for all of the entries in their categories.
Would you like to become a curator of the Civic Tech Field Guide? Drop us a quick note.
Platforms that allow a variety of people to contribute data to a common collection.
Formats designed to structure data, which then enables interoperability, analysis, and software development.
Tools and platforms that visually present & analyze information, like:
Dashboards present and visualize key data, including trends and hotspots, in a single glance. The most common example in this subgenre are municipal dashboards, which display data indicators across a city for operators or citizens to monitor.
Network visualizations are interactive visualizations of networks, such as mapping the social networks of the political elite.
Data science is used to “unify statistics, data analysis, machine learning and their related methods” to “understand and analyze actual phenomena” using data. (Hayashi, Chikio, 1996. “What is Data Science? Fundamental Concepts and a Heuristic Example“).
The role of place is obviously hugely important in civic technology Mapping tech collects, plots, and displays geographic data.
Civic maps collect and display data geographically to coordinate action, plot resources, or make an argument for change.
Mapping platforms are the underlying platforms and tools that draw the maps, such as OpenStreetMap and Google Maps, that you can use.
Accessible databases of civic and media archives.
A Civic Data Primer
Data exists at an interesting and complicated intersection of the computational and the social. “Data” supports the claims we make in essays, and “data” is the fodder of algorithms. We can collect and use data to hold governments accountable just as soon as governments and companies can use data to surveil us. The breadth of definitions and assumptions and processes and literacies that surround “data” – some of which cut directly to the core of scientific inquiry and social life – render the word both dizzying and endless.
- Logic Magazine’s Ben Tarnoff on defining and democratizing data
- The “Algorithm” and “Data Visualization” sections of Software Studies: A Lexicon (although the whole book is worth a read)
- Dr. danah boyd of Data & Society’s Critical Questions for Big Data
- Dr. Chris Wiggins’ course at Columbia called data:past,present,future
- Dr. Ruha Benjamin’s Race After Technology: Abolitionist Tools for the New Jim Code
- Yasodara Cordova for Harvard’s Berkman Klein Center on different protections for different types of data