This is a periodic newsletter of the interesting things we’ve seen and what we are thinking about in open source policy analysis.
California releases open-source COVID-19 modeling tool. The state of California has open sourced CalCAT, the state’s COVID-19 monitoring and modeling tool built with R Shiny. The tool provides current snapshots of COVID-19 throughout the state and short-term forecasts and longer-term forecasts based on models developed by the state government, RAND, and Johns Hopkins University. Link, GitHub
University of California System and Springer finalize open-access research deal. The University of California System and Springer Nature have finalized a deal that will allow researchers to publish free-to-read articles in over 2,700 journals between 2020 and 2023. This agreement comes in the midst of ongoing discussions and disputes between universities and publishers to promote free access to open-source research. Link
An open-source traffic simulator. A/B Street is a new open-source traffic simulation tool that allows users to see the effects of changing land usage, lane placement, and traffic regulation on traffic congestion and traffic flow. The software was built to allow members of the public to contribute to urban planning issues. Link
Open-source crash modeling for the city of Boston. The city of Boston has partnered with the organization Data4Democracy to build InsightLane, an open-source crash modeling tool. The tool has already expanded to support data from Washington, DC; Buffalo, New York; and Melbourne, Australia. The project uses city-provided crash data and OpenStreetMaps to illustrate high-risk and dangerous areas of cities for pedestrians, cyclists, and drivers. GitHub
Edited by Matt Jensen, Peter Metz and Jacob Chuslo