It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.
You can still access the UC Berkeley Library's services and resources. Here's how.
Wondering about tool options? QGIS is a free open source desktop GIS that runs natively on all operating systems. UC Berkeley students, staff, and faculty are also eligible to receive a one-year license for Esri desktop products and have access to ArcGIS Online. Find out more on the Tools tab.
Lots of geospatial data are available online, either through the library or other sources. Explore the GIS Data pages to find the data you need.
If you are teaching a class with a GIS or mapping component, I can help with a remote instruction session on topics such as finding and evaluating spatial data. Get in touch!
This is the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). Also, Supported by ESRI Living Atlas Team and the Johns Hopkins University Applied Physics Lab (JHU APL).
Ready-to-use demographic and other data from authoritative sources, Esri user community, and business partners. Also includes a collection of datasets, applications, and other useful content for planning and response. These materials will be updated with new content as it becomes available.
Novel Corona Virus (COVID-19) epidemiological data since 22 January 2020. The data is compiled by the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) from various sources.
Sources include the World Health Organization (WHO), DXY.cn. Pneumonia. 2020, BNO News, National Health Commission of the People’s Republic of China (NHC), China CDC (CCDC), Hong Kong Department of Health, Macau Government, Taiwan CDC, US CDC, Government of Canada, Australia Government Department of Health, European Centre for Disease Prevention and Control (ECDC), Ministry of Health Singapore (MOH). Fields available in the data include Province/State, Country/Region, Last Update, Confirmed, Suspected, Recovered, Deaths.
The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. This time series data is compiled from state and local governments and health departments.
A structured dataset quantifying 166 countries’ economic responses to the COVID-19 pandemic. Quantified policies include fiscal stimuli, monetary stimuli, interest-rate cuts, and interventions to control the countries’ balance of payments. Draws mainly from the International Monetary Fund’s COVID-19 Policy Tracker — which describes the policies in free-form text — and supplements it with additional research.
Descartes Labs is releasing mobility statistics (representing the distance a typical member of a given population moves in a day) at the US admin1 (state) and admin2 (county) level. A technical report describing the motivation behind this work with methodology and definitions is available at descarteslabs.com/mobility-v097. We intend to update the data in this repository regularly.
Reports that chart movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential. International coverage.
Reports are published daily and reflect requests for directions in Apple Maps. Change in routing requests since January 13, 2020 can be visualized in the browser. You can also download the complete data set, which features daily changes in requests for directions by transportation type for all available countries/regions, sub-regions, and cities.
Note about methodology:
Read Kieran Healy's excellent blog post (https://kieranhealy.org/blog/archives/2020/04/23/apples-covid-mobility-data/) about working with the Apple Maps data and her takeaway: "As a rule, when you see a sharp change in a long-running time-series, you should always check to see if some aspect of the data-generating process changed—such as the measurement device or the criteria for inclusion in the dataset—before coming up with any substantive stories about what happened and why."