#Data4COVID19 Round-Up: 1 October
Welcome to The GovLab’s #Data4COVID19 Round-Up. This temporary, weekly curation will provide you with notable updates to the #Data4COVID19 data collaborative repository and other information meant to facilitate data stewardship in the ongoing pandemic. Have an interesting novel coronavirus-related project worth sharing? Send it to us at datastewards@thegovlab.org so we can consider it as an addition.
Summer of Open Data
The Open Data Policy Lab (an initiative from The GovLab with support from Microsoft) and its partners BrightHive, Open Data Institute, Open Data Charter, and Digital Trade & Data Governance Hub concluded its Summer of Open Data, a three-month project to jump start an exploration into the Third Wave of Open Data that focuses on purpose-driven reuse of data, cross-sector data collaboration, subnational open data efforts, and data responsibility by design.
The final panel, led by BrightHive’s Matt Gee, brought together Vanessa Brown (National Student Clearinghouse), Felix Schapiro (Commonwealth of Virginia), and Daniel Jarratt (Infinite Campus) to talk about the COVID-19 pandemic and its effects on the workforce. The full conversation is available via video and a summary can be found here.
In the coming weeks, we will publish materials synthesizing lessons learned from across the series toward advancing the Third Wave of Open Data. Until then, we welcome everyone to visit the Summer of Open Data hub on the Open Data Policy Lab’s Medium site. There, you can find a complete list of blogs, videos, and speakers.
What’s New in the #Data4COVID19 Repository
The #Data4COVID19 repository added seven more entries this week, expanding to 358 in total. Projects now span:
- East Asia and Pacific: 19 (+0)
- Europe and Central Asia: 67 (+1)
- Latin America and the Caribbean: 13 (+0)
- Middle East and North Africa: 1 (+0)
- North America: 80 (+3)
- South Asia: 3 (+0)
- Sub-Saharan Africa: 18 (+0)
- Global: 113 (+3)
While there remains 15 requests for data and 28 challenges or calls for proposals.
Each week, we will highlight a few of those recent additions to the repository that you might have missed. These examples illustrate innovative methods, appear demand-driven, or otherwise demonstrate an attempt to translate insights into action. We also aspire, to the extent possible, to make the selections geographically diverse. A project’s inclusion does not indicate endorsement by The GovLab or confirmation of its success in meeting its goals.
This week’s entries involve data-driven prediction, situational awareness, and causal analysis. The first, a US-focused effort, seeks to compile various data sources to identify US counties likely to see probable COVID-19 outbreaks. The latter two look at online social media platforms to better understand how information spreads and what impact it might have on its recipients’ trust in science and public institutions.
COVID-19 Outbreak Detection Tool: Using machine-learning methods, researchers at Massachusetts General Hospital, Harvard Medical School, Georgia Tech and Boston Medical Center developed a tool to detect and predict outbreak spread at a county level in the United States. The tool relies on officially reported COVID-19 cases and deaths as well as factors like mask mandates, social distancing policies, and the CDC’s Social Vulnerability Index. Data updates two-to-three times per week and the tool visualizes all findings on a publicly available county map of the United States.
COVID-19 Reddit Algo-Tracker: The Citizens and Technology Lab at Cornell University has developed a service monitoring the algorithms on the social media platform Reddit, taking snapshots every two-to-three minutes. During the COVID-19 pandemic, Cornell is using its service to better understand communication during the pandemic, collecting posts that use coronavirus-related, English-language terms. The work will inform the Citizens and Technology Lab’s collaborations with Reddit communities. It will also help the lab understand the role ranking algorithms play on public discourse. Results from the collection are displayed with visualizations available on the tracker’s website.
Nextstrain SARS-CoV-2 Research: Nextstrain is an inter-institutional, open source project to track the evolution of pathogens around the globe to aid in epidemiological research and outbreak response. Amid the ongoing COVID-19 pandemic, the Nextstrain research team has analyzed data on SARS-CoV-2 by region and published regular updates on its genomic epidemiology work.
You can also find additional resources related to data stewardship and data collaboration here.
